Available Projects

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Summer 2024 Projects

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College of Business

Technology and Operations Management

• Dr. Honggang Wang 
  
  • Project 1 Description: Deep Learning for Pulmonary Fibrosis Progression
    Imagine one day, your breathing became consistently labored and shallow. Months later you were finally diagnosed with pulmonary fibrosis, a disorder with no known cause and no known cure, created by scarring of the lungs. If that happened to you, you would want to know your prognosis. That’s where a troubling disease becomes frightening for the patient: outcomes can range from long-term stability to rapid deterioration, but doctors aren’t easily able to tell where an individual may fall on that spectrum. Your help, and data science, may be able to aid in this prediction, which would dramatically help both patients and clinicians.
    In this project, you’ll predict a patient’s severity of decline in lung function based on a CT scan of their lungs. You’ll determine lung function based on output from a spirometer, which measures the volume of air inhaled and exhaled. The challenge is to use machine learning techniques to make a prediction with the image, metadata, and baseline FVC as input.
    
  • Project 2 Description: Large Language Modes and Detection of AI Generated Text
    Can you help build a model to identify which essay was written by middle and high school students, and which was written using a large language model? With the spread of LLMs, many people fear they will replace or alter work that would usually be done by humans. Educators are especially concerned about their impact on students’ skill development, though many remain optimistic that LLMs will ultimately be a useful tool to help students improve their writing skills.
    At the forefront of academic concerns about LLMs is their potential to enable plagiarism. LLMs are trained on a massive dataset of text and code, which means that they are able to generate text that is very similar to human-written text. For example, students could use LLMs to generate essays that are not their own, missing crucial learning keystones. Your work on this project can help identify telltale LLM artifacts and advance the state of the art in LLM text detection. By using texts of moderate length on a variety of subjects and multiple, unknown generative models, we aim to replicate typical detection scenarios and incentivize learning features that generalize across models.
  • Mode: Hybrid
    • This will mostly consist of remote collaboration with students. With the option to meet in person as needed.
  • Responsibilities: Students have interest and motivation to study on the proposed research. They will find and read recent literature in AI and their applications . Students will enjoy learning some fundamental Python programing and data processing skills.
  • Preferred Skills: Genuine interests in AI modern technologies, and basic Python coding.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Deep understanding of AI/AI models and their impact in healthcare and many other areas.

College of Engineering

Aerospace Engineering

• Dr. Subodh Bhandari 
  • Project Description: Cal Poly Pomona is currently working on many projects related to unmanned aerial vehicles (UAVs). The projects use the very active UAV Lab at Cal Poly Pomona, which is a state-of-the-art facility with more than 40 UAVs and associated equipment and sensors. The project will involve many aspects of UAV research such as increased autonomy of UAVs, designing, building, and testing novel UAV platforms including e-VTOL, the development of obstacle detection and avoidance capabilities that enable the UAVs to fly safely without colliding with mobile vehicles and static objects in their flight path, increased autonomy, intelligent control, coordination between multiple UAVs, collaboration between UAVs and ground robots, increased robustness, safety, and integrity. The project also include research on widespread applications of UAVs such as search and rescue, fire detection and monitoring, precision, agriculture, 3-D mapping for topographic changes, target recognition, etc. This will require selection and integration of appropriate sensors, instrumentation, programming, simulation, flight testing, data collection, data analysis, aircraft system identification (determination of UAV parameters using flight data), etc.
  • Mode: In-Person
  • Responsibilities: Literature review, meeting with the advisor, project work, which includes UAV design, fabrication, and testing, project design (instrumentation, system integration, simulation, flight testing), programming, data collection, flight data analysis, parameter identification, algorithm development including computer vision-based techniques for object detection, tracking, and sense & avoid.
  • Preferred Skills: Background in one or more of the following: a) Engineering, b) Physics, c) Math, or d) Computer Science
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project:  Understanding and knowledge of dynamics and control of UAVs, designing, building, and testing UAVs, automation, instrumentation, sensor integration, simulation, flight testing, exposure to modern engineering tools and programming, ability to work in a multidisciplinary team environment, improved oral and written communication skills, etc.

Civil Engineering

• Dr. Jeyoung Woo 
  
  • Project Description 1: In STEM (science, technology, engineering, and mathematics) education, faculty and other educators measure students' learning based on their academic coursework performance. This assessment does not include the student’s ability to perform project management (PM). In most STEM-related courses, a project is an essential component where students work with peers to apply their academic learning to real-world, scenario-based problems. Yet, students are often assigned to a group project or a senior design (Capstone) project without prior training in project management fundamentals, such as defining or managing scope, cost, time, communication, and monitoring. During the summer break, the participating STARS student (scholar) will develop training modules that can be adapted to any STEM course with the following five categories, 1) scope management, 2) cost management, 3) time management, 4) communication, and 5) monitoring the progress. Also, the student will analyze trends of project management education in the STEM disciplines.
    
  • Mode: In-Person
  • Responsibilities: A student(s) will conduct a literature review about project management components, will develop a survey questionnaire, and will analyze the survey responses. Also, the student will develop a training module for the in-class exercise.
  • Preferred Skills: College-level reading, no prior research experience is needed.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project:  Identify factors from the publications, design a survey to answer the research questions, and document the findings. Time management through the progress meeting, goal setting, and micromanagement.

 

• Dr. Jeyoung Woo 
  
  • Project Description 2: The State of California has the largest education system in the United States, but there is no Associate Degree for Transfer in Engineering. Since there is no standardized path for the course articulation, each 4-year university determines which engineering courses from particular colleges will be accepted for credit. The participating STARS student (scholar) will assist the Principal Investigator (PI) with a literature/publication review, a case study of other state’s ADT in Engineering (such as Texas, and Florida), a data analysis, and a journal article/conference proceeding writing to decrease the gaps in engineering education for transfer students and increase their success.
    
  • Mode: Hybrid
  • Responsibilities: A student(s) will conduct a literature review about project management components, will develop a survey questionnaire, and will analyze the survey responses.
  • Preferred Skills: College-level reading, no prior research experience is needed.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project:  Identify factors from the publications, design a survey to answer the research questions, and document the findings. Time management through the progress meeting, goal setting, and micromanagement.

  

• Dr. Jinsung Cho
  • Project Description: Clash Detection (CD), one of Building Information Modeling (BIM) techniques on jobsites, improves project efficiency by minimizing time spent on resolving deviations between construction and design. Many clashes from diverse combination of structural components (i.e. beams, joists, and girders) and mechanical, electrical and plumbing (MEP) components (i.e. ducts and pipes) are found through different clash detection software, such as Autodesk Naviswork Manage. Countless clashes detected in many commercial and residential buildings are resolved by design change solutions agreed upon in coordination meetings involving the different construction projects parties. This project develops a framework for clash detection patterns using Artifitial Neural networks (ANNs). The framework developed detects the patterns of clash detection solutions based on cost data, and focuses on coordination of mechanical (i.e. ducts) and plumbing systems (i.e. pipe). The cost of each scenerio is estimated and analyzed using ANN to determine the patterns of most cost effective clash detection solutions. To validate the framework developed, more than 100 Naviswork Manage files reporting various clashes are collected from a construction project case study and are analyzed to detect patterns of clashes, and suggest the most cost effective design solution scenario. The major contribution of this project is that the ANN frameowrk developed could be further applied on other residential building projects with analogous scale to our case study, and could be further revised in the future to encompass commercial buildings.  
  • Mode: In-Person
  • Responsibilities: 
    • Tuesday and Thursday U-hour
    • Monday and Friday Morning
  • Preferred Skills: Prefered Civil Engineering and Construction, or (Mechanical Engineering) but any students who are interested in Building Construction.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Efficient building construction management, Building Information Modeling concept, simunalation and artificial neural network.

 

• Dr. Mehrad Kamalzare
  • Project 1 Description: Develop more cost-effective Drywell Systems in LA County:
    Learn more accurate infiltration test methods for estimating the capacity of drywells and utilize correction factors that rely on a defensible technical analysis.
    The current infiltration testing and drywell design methods provided by the Los Angeles County Department of Public Works do not always provide accurate estimates of the capacity of production-scale drywells. In many cases, it appears that the predicted capacities are much lower than actual drywell capacity, resulting in more drywells than needed and significantly higher construction and long-term maintenance costs. In other cases, the uncertainty in the measurements results in predicted capacities are higher than actual drywell capacity, resulting in fewer drywells that needed. This project focus on developing more cost-effective drywell systems by more accurately predicting the drywell performance using innovative, pre-construction methods.
    
  • Project 2 Description: Numerical modeling of railroad structures and analyze various stress-strain relationships in Ballast layer:
    The two main purposes of the project are 1. to describe and analyze the typical materials currently used under the ballast and sub-ballast for the railways, and 2. present a sustainable alternative with prospect materials that can replace the virgin raw sub-ballast materials.The starting point of the current analysis is to summarize a number of available papers related to railway geometry, structure, materials, as well as related performed tests results, and analysis of the conclusions.
    This developed numerical model will be used to predict the behavior of the real railroad in various part of the country.
    
  • Mode: Hybrid
    • Most meetings will be conducted virtually, with a few in-person sessions on campus.
  • Responsibilities: Conducting literature review; Perform close collaboration with the LA County public works to identify appropriate study-sites in the County; Working closely with the faculty to study and identify appropriate locations to of drywells in various watersheds; Close collaboration with the faculty and other students in the research team to obtain documentation regarding Drywell Operations. Potentially, conducting Infiltration Testing and Flow Rate Monitoring; Potentially, accompanying faculty and other team members for field visits to document the County's operation and maintenance activities. Preparing report for potential journal or conference publication; Participating in various meetings with officials from government and management from different cities in the LA County, among others. 
  • Preferred Skills: 
    • Familiarity with MS Office
    • Good communication skills
    • Punctuality
    • Reliability
    • Being organized in various tasks
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: 
    • Teamwork skills
    • Conducting organized research
    • Communications with official government entities
    • Engineering skills in the Geotechnical and Water Resources engineerings
    • Project management

 

• Dr. Ghada Gad
  • Project Description: The goal of this project is to benchmark the existing use of alternative project delivery methods (PDMs) in local transportation agencies of different types and sizes in California while considering the characteristics of each alternative PDM and the authorizations enabling its implementation, as well as provide recommendations for key factors to consider in alternative PDM selection and implementation by California’s local transportation agencies. There is limited research though that focuses just on California’s use of alternative PDMs, its associated pros and cons, legislations/authorizations, and project performance. There is a wide variation in the use of alternative PDMs among project sponsors in California (local governments, regional transportation agencies, or transit agencies) under varied authorizations. For example, Caltrans has delivered to date more than 45 CM/GC transportation projects; seven Design-Build (DB) projects, 13 ID/IQ projects, and two projects were selected to be developed using Progressive DB. The Los Angeles Metropolitan Transportation Authority (Metro) has been using DB on projects as major as such as The Purple Line Extension and are pursuing PDB and CM/GC for the first-time. With such varying types of transportation agencies in California and with each having specific authorizations for the use of alternative PDMs, it becomes harder for policy and decision-makers to navigate the pros and cons of these PDMs, the variations in the authority to use each of them, and to assess how these methods are being selected and how they improve project delivery and provide value to the public in California.
    
  • Mode: Hybrid
    • Meetings will be conducted virtually and in-person.
  • Responsibilities: Reading literature, summarizing them, collecting data, analyzing data, writing papers, and meeting with faculty.
  • Preferred Skills: Oral and Written Communcation Skills
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Research methods selection and application, data collection and analysis

 

• Dr. Ali Sharbat
  • Project Description: Water is one of the most critical elements for sustainable development. One of the significant challenges for the future of life on this planet after climate change is to ensure access to a sustainable clean water source. California has experienced a severe droughts during the past decade that had significant effects on the economy of the state. In 2017, people of LA County (i.e. the most populated county in the USA) voted for Measure W. Measure W is a very progressive program focused on securing sustainable water for the people of California. Measure W creates the Safe, Clean Water Program, a comprehensive action plan to increase local water supplies, clean up contaminated water to protect public health and the environment, and prepare our region for drought. Every year more than 100 billion gallons of rainwater flow down our gutters and out to the ocean. Measure W will modernize Los Angeles County’s outdated water infrastructure to capture and save more rainwater, enough for more than 2.5 million people. Cal Poly Pomona is the second largest CSU campus and is located in LA county and could significantly benefit from this funding program and research opportunity.
    My research team at Cal Poly Pomona is developing a feasibility study and action plan to evaluate possibilities of using Measure W funds in improving Cal Poly Pomona's stormwater management master plans. Employing Measure W, Cal Poly Pomona will be able to capture all available stormwater on site and prevent sending this valuable asset to the ocean. My team and I will conduct a literature review to identify approaches of similar projects and determine key steps to effectively implement the idea on campus. The outcome of this study could be standardized and employed by other industrial or institutional campuses. 
    
  • Mode: Virtual
    
    • Librbary work
    • Field survey(s) and data collection (using a guide provided by the advisor)
    • Data analysis (using a guide provided by the advisor)
    • Attending virtual meetings with peers
    • Attending virtual meetings with project advisor
    • Team-work on preparation of progress reports and the final report
  • Responsibilities: A typical work consists of library work, field work, and team meetings. We will be flexible and will develop our weekly schedules based on all team members' feedback.
  • Preferred Skills: Teamwork
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project:
    • Writing skills
    • Technical communication skills
    • Microsoft Office
    • AutoCAD skills
    • Water quality laboratory analysis techniques

Electrical & Computer Engineering

• Dr. Anas Salah Eddin
  
  • Project Description: Building an Autonomous Racing Model
    Introduction:
    Are you interested in autonomous driving and robotics? We have an exciting research project designed specifically for undergraduate students like you! Join us in building and testing an F1TENTH autonomous racing model, and gain practical experience in perception, planning, and control systems.
    Objectives:
    - Build an F1TENTH autonomous racing model: Assemble a 1/10th scale autonomous vehicle and equip it with sensors for environment perception.
    - Develop perception algorithms: Implement object detection, lane detection, and obstacle avoidance algorithms to enable the model to understand its surroundings.
    - Design planning and control systems: Create algorithms for path planning and control, allowing the model to navigate the racing track autonomously with optimized speed and safety.
    - Test and evaluate: Conduct thorough testing and evaluation of the model's performance, analyzing its speed, accuracy, and reliability in various scenarios.
    Methodology:
    - Explore existing research: Study the current knowledge and best practices in perception, planning, and control systems for autonomous driving.
    - Hands-on hardware setup: Assemble the F1TENTH vehicle, integrate sensors, actuators, and communication interfaces, ensuring a functional setup.
    - Software development: Implement perception algorithms and design planning and control systems to bring the autonomous racing model to life.
    - Testing and evaluation: Create diverse test scenarios, collect data, and assess the model's performance, making iterative improvements as needed.
    Expected Outcomes:
    - Functional autonomous racing model: Build and configure a 1/10th scale vehicle equipped with sensors and communication interfaces.
    - Implemented perception, planning, and control systems: Develop algorithms enabling the model to autonomously navigate the racing track and make informed decisions.
    - Performance evaluation and improvements: Test and evaluate the model's capabilities, identifying areas for enhancement and refining its speed, accuracy, and reliability.
    Conclusion:
    Take part in this unique undergraduate research opportunity and delve into the fascinating world of autonomous driving! By building and testing an F1TENTH autonomous racing model, you will gain valuable skills and hands-on experience in perception, planning, and control systems. Join us on this rewarding journey and prepare yourself for a future career in the dynamic field of autonomous driving.
    
  • Mode: Hybrid
    • Students will be doing simulation in a virtual environment. Once the tasks are running effectively in the virtual environment, they will have the opportunity to run that code on an F1tenth model car on campus.
  • Responsibilities: 
    • Hardware setup and calibration: Assemble and calibrate the F1TENTH vehicle, ensuring proper functionality.
    • Software development: Work on perception, planning, and control algorithms to enhance the model.
    • Testing and debugging: Run the model, evaluate performance, and make necessary adjustments.
    • Data collection and analysis: Collect sensor data, analyze results, and identify strengths and weaknesses.
    • Collaboration and brainstorming: Engage in collaborative discussions, problem-solving, and idea exchange.
    • Documentation and reporting: Maintain thorough documentation of progress, including code and test results.
    • Continued learning: Stay updated with the latest advancements in autonomous driving through self-study and research.
  • Preferred Skills: While no specific prerequisites are required, we have a preference for students with some programming background, particularly in languages such as Python or other similar languages. We also strongly encourage students who are interested in learning programming and have a passion for autonomous driving to apply.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: PParticipants will acquire valuable skills in programming, robotics, sensor integration, perception algorithms, path planning and control, as well as hands-on experience in testing and evaluation. Additionally, they will develop collaboration and teamwork abilities through active engagement in the project.

 

• Dr. Mohamed Aly
  
  • Project Description: Introducing a groundbreaking advancement in aerial technology: our project revolutionizes the concept of edge computing by enabling a swarm of drones to dock in mid-air, creating a scalable, flying computing cluster. This innovative approach harnesses the agility and flexibility of drones, allowing for on-the-fly assembly of powerful computing nodes. Imagine the possibilities: rapid deployment of processing power exactly where and when it's needed, without the constraints of terrestrial infrastructure. This cutting-edge technology promises to redefine disaster response, environmental monitoring, and live event coverage, by providing unprecedented computational capabilities directly at the edge of action. Join us in shaping the future of autonomous aerial systems and edge computing, where the sky is not the limit, but the beginning.
    
  • Mode: Hybrid
  • Responsibilities: A typical day for students participating in the project focused on creating a landing mechanism for drones to form a scalable edge computing cluster would be dynamic and multidisciplinary, blending theoretical learning with hands-on experimentation. Here's a breakdown:
    **Morning Session: Theoretical Learning and Strategy Planning**
    - The day begins with a briefing session, where students gather to discuss the day's objectives and review any new findings or adjustments needed for the project.
    - This is followed by a theoretical learning session led by project mentors or guest experts, covering topics related to drone technology, edge computing, and the principles of aerial docking mechanisms. This could also include discussions on the computational challenges and the potential applications of such a technology.
    - Students then break into smaller groups to brainstorm and plan the day's practical tasks, focusing on specific aspects of the project such as software development, mechanical design, or testing protocols.
    **Midday: Hands-on Work and Experimentation**
    - After the planning session, students engage in hands-on work in their respective areas. This could involve:
    - Coding and simulation work for the drone's docking algorithms and edge computing tasks.
    - Designing and fabricating parts of the docking mechanism using 3D printers or other tools in a maker space.
    - Conducting tests with drones in a controlled environment or simulation to evaluate docking mechanisms and computing cluster performance.
    **Afternoon: Collaboration and Problem-Solving**
    - Post lunch, the focus shifts to collaborative problem-solving and integration efforts. Students from different groups come together to integrate their work, ensuring the software and hardware components are compatible and function as intended.
    - This session may involve troubleshooting, where students identify and address issues encountered during the integration process. It's a critical time for learning and applying problem-solving skills in a real-world context.
    **Evening: Reflection and Documentation**
    - The day concludes with a reflection session, where students share their progress, challenges, and learnings. This is a valuable time for peer feedback and mentor guidance.
    - Students also document their work, updating project logs or preparing reports. Documentation is crucial for tracking the project's progress and ensuring continuity of work across different phases.
    Students are encouraged to engage in open communication, peer learning, and creative thinking throughout the day. The project offers a unique blend of learning opportunities, from the technical aspects of drone and computing technology to the soft skills of teamwork, project management, and innovation.
    
  • Preferred Skills: Just to be motivated and at least ability to work with Python or C
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Able to learn fast and work within a team.

 

• Dr. Tamer Omar
  
  • Project Description: Frontier Technologies cybersecurity Research Lab (Research Lab Website)
    • Project 1 Description: Extension of Network Coverage using UAVs and SDRs for Disaster Recovery:
      This project aims at presenting a potential solution to the lack of connectivity available for individuals located inside of a disaster-impacted region. The project explores the construction of a mobile base transceiver station that uses Software Defined Radios (SDRs) and equipped into an Unmanned Aerial Vehicles (UAVs). the lab hosts the Universal Software Radio Peripheral (USRP) used to create the virtual interfaces required to create the backup communication systems. Students program the USRPs using lab view software to create the required relay stations for such application to restore the wireless networks in case of disasters.
      
    • Project 2 Description: Flow Control Build and Destroy Federated Learning Approach for Securing-SDNs:
      Software-defined networking, or SDN, is a new concept developed to shift the current paradigm of network infrastructures by providing a central control layer and improves network management and implements programmability for flexibility. This project aims at analyzing the effects of different network and host based attacks such as Distributed Denial of Service attacks (DDoS) on an SDN environment. Students investigate approaches to detect and mitigate these attacks and use the flexibility of OpenFlow, a common SDN protocol, to secure this new networking trend.
    • Project 3 Description: 5G Self Organized Network (SON) Simulator/Emulator:
      This project has both a software-based approach and a hardware-based approach.
      1. Software based SON simulator aims to model a 5G mobile service providers' core network, access network, and self-healing controller. This consist of modeling and designing a 5G network environment and creating a management system to oversee and maintain the network autonomously. The project will be designed/implemented using C++ to implement network core classes, C# to implement the network simulator Graphical User Interface (GUI), and MATLAB to implement the access network radio frequency signaling. The simulator will create and configure accurate networking scenarios that to determine the potential self-healing solutions in case of network failures or congestion. Figure 1 shows a snap shot of the simulator code with all developed classes and a sample network of seven cells used to present the simulated network. WNSL host the simulator application developed by CPP students.
      2. Hardware based SON focus on using a 5G network implemented at CPP to support 5G research projects. The implemented network core network, gNodeB's, and user phone are the hardware infrastructure used to research SON approaches to test and improve network performance with different network loads such as Wireless Sensor Network and Internet of Vehicles traffic. The 5G implementation is the first in CPP and the hardware can be used in multiple IoT/embedded system applications.
    • Project 4 Description: Autonomous/Remote Pilot less Unmanned Ground Vehicle (UGV) Racing Command Center:
      This project aims at creating a race between autonomous and a remotely controlled UGVs through wireless link using car (VRX) simulator. The remote pilot less team will use a VRX racing simulator and IoV (Internet of Vehicle) technology to support driving the remote pilot less UGV. IoV technologies relying on wireless communication to send car and driving controls from the VRX simulator to an API (Application Program Interface). The API server is connected to the internet and thus transferring the data that is being collected from the simulator to the vehicle. The server will act as a cloud service to communicate the data to the vehicle and return the outdoor driving conditions back to the simulator. The simulator controls the vehicle by using a communication link (modem) attached to the vehicle and operated by Sprint. 
  • Mode: Hybrid
    • The hybrid structure involves both working in the lab to utilize hardware equipment that can be only accessed on campus, and virtual zoom progress meetings for discussing project milestones, advising students, and reporting the project progress. Asynchronous project implementations are possible for projects that may require software development and cloud application access. The percentage of the hybrid mix between the On-campus vs online components depends on each project objective and its available resources.
  • Responsibilities: The students will perform one the following activities in a typical day according to the phase of their research project:
    • A day during literature review phase : Students will be collecting data and improving their understanding about a research topic by conducting literature surveys and collecting user and system requirements
    • A day during system design phase - Students will be designing a solution to a problem in hand after finishing their research survey using a new creative approach.
    • A day during technical implementation phase - Students will be develop and Implement the new approach using software and hardware devices if needed and integrate them into operating running
      
  • Preferred Skills: None.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Student will be able to perform literature surveys, develop system design, perform system implementation and integration, conduct systems testing, and engage in research writing and technical documentation

Electromechanical Engineering Technology

• Dr. Farbod Khoshnoud
  
  • Project Description: Bronco Robot University Tour Guide: BillyBOT
    This is a robotic project as a mobile platform that can travel around the campus autonomously, and interact with people and answer questions via artificial intelligence. This is an ongoing project currently with some of the current STARS students. We started this project in the Fall 2023. The project is going well and we can discuss further about the project if you are interested with the students involved or myself. 
    
  •  Mode: In-Person
  • Responsibilities: Mechatronics, controls, robotics, dynamic systems. 
  • Preferred Skills: Familiarities with mechatronics, controls, robotics, dynamic systems
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Mechatronics, controls, robotics, dynamic systems

College of Pharmacy, Western University of Health Sciences

Pharmaceutical Sciences

• Dr. Kabirullah Lutfy
  
  • Project Description: We are interested in the role of certain peptides in the brain in binge eating, food devaluation, and food reward, We measure behavioral changes as well as molecular changes using some molecular approaches as western blots, real-time PCR, etc.
  • Responsibilities: Students will be assessing food intake in animals, measuring their body weight and conducting real time PCR or western blotting.
    
  • Preferred Skills: Molecular Biology techniques and prior work with rodents are preferred but not required
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Learning about behaviors of mice and certain molecular techniques.
    

College of Science

Biological Sciences

• Dr. Andrew Steele
  
  • Project Description: We are running three projects in our lab, so students may end up contributing to one or more of the following:
    1) Preparation, purification and characterization of novel adeno-associated viral vectors for gene therapy.
    2) Genetic studies to define a dopamine circuit required for linking scheduled feeding to circadian activity cycles.
    3) Genetic studies to define a dopamine circuit required for diet-induced obesity.
    All these studies involve mouse work.
    
  • Mode: In-Person
  • Responsibilities: Microscopy, tissue sectioning, staining, mouse work
  • Preferred Skills: Molecular and cellular biology is helpful, as is neuroscience coursework
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Antibody staining, microscopy, basic animal handling, possibly survival surgery

 

• Dr. Frances Mercer
  
  • Project Description: The student will perform parasite cytotoxicity assays and trogocytosis assays to evaluate whether white blood cells called neutrophils can attack a parasite we work with in the lab.
  • Mode: In-Person
  • Responsibilities: Students make their own schedules and have mandatory meetings with me to discuss experimental plans and data analysis. All students must undergo and extensive hands-on training by me before beginning independent work.
  • Preferred Skills: Immunology, Flow Cytometry, cell culture, cell differentiation, parasite culture
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Flow Cytometry, microscopy, scientific writing and presentation

 

• Dr. Juanita Jellyman
  
  • Project 1 Description: Effects of Maternal High Fat Diet on Offspring Metabolic Function. Students will assess appetite and metabolic function in lambs whose mothers ate high fat diet. They will help to feed sheep, clean out pens, and measure physiological variables. Some weekend work alongside other students may be needed as animals need to eat every day.
  • Project 2 Description: Effects of exposure to THC on offspring growth. Students will work with small animals (chick embryo or mouse) to measure growth and cardiovascular function (heart rate, blood pressure etc). Some weekend work may be needed if animals need to be weighed. .
  • Mode: In-Person
  • Responsibilities: Animals need to be fed daily and feed intake measured. Animals are weighed once / week.
  • Preferred Skills: No specific skills needed. Physiology/Anatomy classes are a plus.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Animal handling skills, data collection, analysis and presentation. Training in ethical use of animals in research and teaching.

Chemistry & Biochemistry

• Dr. Gregory Barding
  
  • Project 1 Description: We are using GC-MS to explore how rice plants can survive extended periods of drought and submergence. To do this, we are using chemical tracers to probe the various biochemical pathways that are activated and deactivated in response to drought and flood. Using GC-MS, we can visualize how these pathways are active and then hypothesize how survival can be enhanced. So far, students have built the chambers necessary to expose the plants to the chemical tracer, helped grow the plants and harvest both the roots and shoots for GC-MS analysis. Continued work will include data evaluation,
    hypothesis adjustment, and further experimental design to better understand these projects.
  • Project 2 Description: Biofuel quantitation. We are using NMR to determine the quantities of butanol and butyric acid produced during fermentation with anaerobic bacteria. Students will use specific NMR methods to deconvolute complex NMR spectra and better quantify the production of the gasoline replacement butanol. Continued work will include experiment design, selection of the appropriate NMR experiment, hypothesis adjustment, and data evaluation.
  • Mode: In-Person
  • Responsibilities: A typical stay for students may involve treatment of samples followed by
    analysis using GC-MS, HPLC, or NMR. Students may also spend time exploring the data provided by NMR and GC-MS analysis and performing various statistics and comparisons to
    adjust our hypothesis and design new experiments. These are all steps that students may learn while pursuing these projects.
  • Preferred Skills: Almost all techniques will be taught in-house as the needs arise. The only skills/courses required for these projects is the completion of the general chemistry series with labs, otherwise I will train the students as the projects progress.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Students will learn how to:
    1. Interpret and analyze data collected on state-of-the-art instrumentation in the Chemistry and Biochemistry department.
    2. Use state-of-the-art instrumentation
    3. Basic statistics applicable to biological systems
    4. Collaborate across disciplines (working closely with biologists and biochemists)

 

• Dr. Chantal Stieber
  
  • Project Description: Students will conduct inorganic chemistry research to make catalysts and ligands for reduction of pollutants such as CO2. Students will do hands-on laboratory chemical synthesis, characterization and analysis. Students will learn to use instrumentation such as X-ray crystallography, infrared spectroscopy, nuclear magnetic resonance, electron paramagnetic resonance and more. Students will also learn standard chemistry software and scientific writing. In-person, hybrid, and remote research options available.
  • Mode: In-Person
  • Responsibilities: 
    1. Come into lab, and plan experiments
    2. Setup lab experiments
    3. Analyze data and write reports while running experiments
    4. Finish lab experiments, purify, characterize
    5. Analyze data, write in notebooks, and plan for next day.
  • Preferred Skills: No prior knowledge needed, just an interest to learn some fun chemistry.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Inorganic and organic synthesis, Laboratory notebook writing, Data analysis, Scientific writing, Scientific presentations, Inorganic and organic spectroscopy

 

• Dr. Matt Copabianco
  
  • Project 1 Description: MoS2 Quantum Dots as a Photosensitizer for TiO2.
    Dye-sensitized metal oxide solar cells have been employed as a method of transforming the light emitted from the sun into electricity but suffer from photodegradation and require complicated syntheses. To combat this issue, I propose to use MoS2 quantum dots (QDs) as photosensitizer since it also has superb light absorption and tunability but does not decompose under sunlight or require a complicated synthesis.
  • Project 2 Description: Pollutant Degradation Using MoxW1-xS2.
    Industrial waste has deposited organic pollutants into our water supply, which necessitates efforts in developing catalysts with the ability to degrade these pollutants. MoS2 is a material previously used for this purpose, however, modified versions, such as MoS2 in a heterostructure, have been shown enhanced photodegradation. My proposed work aims to use a mixed-transition metal dichalcogenide, MoxW1-xS2, as a catalyst for efficient model pollutant degradation of Rhodamine B and methylene blue.
    
  • Mode: In-Person
  • Responsibilities: A typical day will include running experiments and then working together to understand the results that were obtained for the day.
  • Preferred Skills: 
    • CHM 1210/L
    • CHM 1220/L
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: 
    • Materials synthesis
    • Materials chemistry
    • Spectroscopy (UV-Vis, raman, fluorescence)

• Dr. Taylor Thane
  
  • Project Description: The goal of this project is to develop new organic chemistry reactions. Metal-catalyzed cross-coupling reactions are powerful tools for constructing new carbon-carbon bonds and have advanced the field organic chemistry by allowing the organic chemist to rapidly build complex molecules. We are interested in developing new nickel-catalyzed cross-coupling reactions that quickly convert simple starting materials into more complex molecules. Nickel is an earth abundant metal that has a broad range of reactivity which allows us to use wider range of simple starting materials including molecules with carbon-oxygen and carbon-nitrogen bonds. Students working on this project will develop new nickel-catalyzed cross-coupling reactions by examining different starting materials and nickel catalysts for these reactions. Students will learn advanced organic chemistry techniques including air-free reaction set up. Students will also learn how to think critically to problem solve challenges that arise, analyze their data, and clearly communicate their results in written and oral formats.
    
  • Mode: In-Person
  • Responsibilities: With PI supervision, students will learn to read scientific literature related to their projects, plan experiments, keep an organized notebook, setup reactions, purify and characterize new molecules, analyze data, think critically about future experiments, and meet with other lab members to share and discuss data gathered.
  • Preferred Skills: Completion of organic chemistry lecture and lab series is preferred.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Students will learn topics and techniques related to organic synthesis including metal catalysis, photocatalysis, purification, spectroscopy, data analysis. Students will also learn to read relevant literature, general lab maintenance, related safety procedures, and scientific communication skills.
    

 

• Dr. Alex John
  
  • Project Description: The project deals with the development of new catalysts. These are molecules which help speed up chemical reactions, and sometimes even help do reactions that are otherwise impossible. The catalysts targeted in this study are based on metals such as molybdenum, vanadium, nickel, and palladium. These catalysts are used for performing specific reactions. Specifically, in this project we are trying to convert plant-derived molecules into simple hydrocarbons which represent the molecules found in petroleum. This approach of making chemicals would help us reduce our dependence on petroleum which is non-renewable, and its processing releases a lot of greenhouse gases. 
  • Mode: In-Person
  • Responsibilities: Students will read literature, plan reactions, set-up reactions for synthesizing organic compounds and metal complexes. Analyze products using various spectroscopic techniques. Analyze characterization data, and document findings. Evaluate metal complexes for catalytic potential and data analysis. . 
  • Preferred Skills: A general understanding of chemical reactions (General Chemistry). Knowledge of Organic chemistry would be beneficial.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Synthesis and purification of organic ligands and metal complexes, separation techniques such as extractions and chromatography, chemical analysis using various spectroscopic techniques such as IR, NMR, Mass-spec, UV-Vis etc., communication skills (written/oral).

 

• Dr. Adaickapillai Mahendran
  
  • Project Description: Our group’s research interest folds into two areas, a) developing novel histone deacetylase 6 (HDAC6) selective enzyme inhibitors for cancer treatment. and b) Understanding the chemistry, biological effects, and toxicity profile of oxidation products of phytocannabinoids.
    • Project 1 Description: Development of novel HDAC6 selective inhibitors:
      HDAC6 has been identified as a potential target for cancer therapy. Current FDA-approved HDAC inhibitors, including suberoylanilide hydroxamic acid (SAHA), Panobinostat, and Belinostat contain hydroxamic acid functionality to chelate co-enzyme Zn2+ ion. Strong chelation of this hydroxamate group leads these drugs to be non-selective and toxic. Thiohydroxamic acid is a compound similar to hydroxamic acid, but its chelation properties and selectivity profiles are not fully explored. In our lab, we synthesize, characterize, and study the metal binding properties of model thiohydroxamic acid molecules. Then we study its bioactivity against HDAC enzymes and its selectivity profile with collaboration. Our long-term goal is to develop novel HDAC6 selective inhibitors (eg. thio-HPOB) similar to known compounds HPOP and HPB.
    • Project 2 Description: Oxidation of phytocannabinoids and its biological effects:
      Phytocannabinoids, including delta-9-tetrahydrocannabinol (Δ9-THC) and cannabidiol (CBD), are well known for their medicinal uses. It is also known that with prolonged exposure of these cannabinoids to sunlight, they lose their properties as they get oxidized. Cannabidiolquinone (CBDQ) is one such oxidized compound inclined to undergo further reactions with nucleophiles. It is not fully understood the biological effects of these quinone intermediates and their addition products. We are interested in the chemical oxidation process of phytocannabinoids, specifically THC and CBD. We are also interested in the mechanism of this oxidation process, supported by DFT calculations. With our biology collaborators, we study their bioactivity against different enzymes and cell-lines.
  • Mode: In-Person
  • Responsibilities: 
    1. Review literature
    2. Plan and set-up reaction
    3. Perform organic reaction
    4. Separation and purification of compounds
    5. Characterize the compounds using NMR, LC-MS, IR and HPLC techniques.
    6. Maintain lab note-book and write scientific report
  • Preferred Skills: Organic chemistry 1 (CHN3140/L) preferred
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: The students will lean, how to:
    1. Review literature
    2. Plan and set-up reaction
    3. Perform organic reaction
    4. Separate and purify compounds
    5. Characterize compounds using NMR, LC-MS, IR and HPLC techniques.
    6. Maintain lab note-book and write scientific report

 

• Dr. Zoe Marr
  
  • Project Description: Students will conduct organic/materials chemistry research to make photoactive metal organic frameworks (MOFs) with potential applications in drug delivery and dosimetry. Students will have the opportunity to do chemical synthesis, characterization, and analysis. Students will also learn characterization techniques such as X-ray crystallography, nuclear magnetic resonance spectroscopy, and UV-vis spectroscopy. Students will also learn how to solve crystal structures.
  • Mode: In-Person
  • Responsibilities: A typical day would primarily consist of synthesis and characterization of the desired molecules/crystalline material.  
  • Preferred Skills: No previous skills required but having taken organic chemistry would be beneficial.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Air-free organic synthesis, solvothermal MOF synthesis, new characterization techniques, crystallography, practice scientific writing and presentation skills.

 

• Dr. Frances Flores
  
  • Project 1 Description: Structure/Reactivity study of Ferrocenyl Chalcones. A mechanistic study of the nucleophilic attack process with amine nucleophiles. The aim is to measure the rates of beta attack vs. carbonyl attack, in order to learn more about the bioactivity processes of natural products. The rates will be monitored via UV-Vis spectrophotometry. This study can be tailored to fit a summer term or an academic year term.
  • Project 2 Description: Structure/Reactivity study of substituted curcumin, the main component of the natural product Turmeric. One aim of this project is to increase the water solubility of curcumin and its analogs while maintaining its bioactivity. The project involves synthesis of the curcumin derivatives, and characterization via UV-Vis, NMR and IR spectroscopy, as well as a preliminary kinetic study of the hydrolysis of the synthesized derivatives. This study can be tailored to fit a summer term or an academic year term.
  • Mode: In-Person
  • Responsibilities: Students in my lab are responsible for the synthesis and characterization of the reagents and products, so under my supervision, they set up and execute their experimental protocols, procedures and characterization as appropriate. In terms of characterization, they learn to operate the FT-IR spectrometers, and the students receive training to operate the department's NMR spectrometer. In fact, they must pass department certification before they are allowed on the machine. For those carrying out kinetic work, they learn to operate the Uv-Vis spectrophotometer, as well as the stopped-flow spectrophotometer. Our students are required to attend weekly group meetings, during which students present their progress and take questions from the group. Outside of that I meet individually with each student (or student team if they're paired on a particular project) on a weekly basis to discuss details of the project and to identify goals to achieve by the next scheduled meeting.  
  • Preferred Skills: General chemistry required. First semester organic lecture and lab is beneficial.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: The students in my lab gain experience in good laboratory practices, including safety training, hands-on experience in handling chemical reagents, as well as hands-on experience with typical instruments commonly used in research laboratories. More importantly, the students will gain experience and exposure to the organic chemistry that they learn in class. Working in my research lab trains them to think like a chemist on a daily basis, to use the chemistry learned on a daily basis, both of which will translate to the students having a higher probability of success in their chemistry courses.

Computer Science

• Dr. John Korah
  • Project Description: **Parallel and Distributed Algorithms for Large and Dynamic Data Science Problems**
    With the advent of the Internet of Things revolution and disruptive internet applications, there has been a massive increase in the amount of real time data that are available to users. Real time data has proven to be a challenge for current data science analysis techniques as the data has a narrow time window beyond which it becomes stale. Therefore, it is critical that the analysis is performed, and results provided to the user within strict time constraints, often in the matter of few seconds. Most of the current data analysis techniques were developed with the assumption that the underlying data is static or semi-static. However, with the rate of data ingestion continuing to increase, there needs to a fundamental change in the way such massive real time data is accessed and processed. In this research project we will focus on problems in big data analytics where parallel and distributed processing is an effective technique for generating resource and time bound analysis.
    In this research, we will explore partial data processing techniques for parallel/distributed processing platforms (e.g. cluster computing). Specifically, we aim to look at design algorithm that have the anytime properties. Algorithms with anytime properties can be interrupted during execution and generate a usable result at the point of interruption. Most importantly, it can generate results of increasing quality when provided with large computational resources. In this project, the student will have the option to choose a specific problem from three application domains 1) Machine learning based anomaly detection in cyber security, 2) Real time search techniques for images, and 3) Machine learning based methods for precision agriculture. We will explore designing and implementing parallel/distributed algorithms for the selected problem and study the performance advantages of using such algorithms.
    As part of the research project, the student will undertake a literature survey of key algorithms used in the problem and existing processing frameworks. The student will work with the mentor to explore and identify one or more specific algorithms that show potential for use with partial processing. The student will then formulate anytime versions of the algorithms and generate preliminary performance analysis. The student will work with the mentor to design experiments to validate the anytime designs. The student will have the opportunity to develop problem solving skills and to display creativity during the algorithm design phase of the project. Finally, the algorithm(s) will be implemented, and experimental validation performed on one or more parallel/distributed platforms. The student will prepare a report for the literature survey and a final report detailing the algorithm design, development, validation and conclusions. The student will also present the results at the Annual Research, Scholarship, and Creative Activities Conference, and possibly at other conference venues.
  • Mode: Hybrid
    • Virtual: Literature survey, software development and experimental validation.
    • In-Person: Weekly meetings that include project discussions and research mentoring.
  • Responsibilities: As part of the project, the students will undertake the following activities:
    • The student will have initial meetings with the mentor to discuss the research project and formulate goals and objectives. These goals and objectives may be refined over the course of the project.
    • The student will meet with the mentor on a weekly basis to go over the progress of the project. The mentor will provide feedback and course corrections as needed.
    • The student will work with other students in the mentor’s research team on the overall research problem while gaining initial experience with relevant programming tools.
    • The student is expected to progressively transition into working in an independent capacity while getting feedback from the mentor.
    • The student will also take part in the mentor's research group meetings to gain background knowledge in the overall Big Data analytics area and share his/her findings with the group and get feedback.
      
  • Preferred Skills: Prior exposure to programming is important to work on the project.
    • The following or similar courses provide a good background in programming:
      • CS1300 - Discrete Structures
      • CS1400 - Introduction to Programming and Problem Solving
      • CS2400 - Data Structures and Advanced Programming
    • The following course(s) or similar course(s), although not required, would be useful for the project:
      • CS3310 - Design and Analysis of Algorithms
      • CS 4650 – Big Data Analytics and Cloud Computing
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: During the project, the student is expected to acquire the following skills, techniques and knowledge:
    • Problem solving and critical thinking skills required to identify the research problem and to formulate and validate the solution.
    • Proficiency in developing parallel and distributed applications and the ability to use parallel and distributed computing platforms such as cloud computing platforms.
    • Acquire proficiency in a programming language (e.g. python) and experience with using machine learning libraries.
    • Acquire the experience of formulating algorithms designs for data analytics with large and dynamic data.
    • Acquire the skills to design and run experiments to validate the algorithm designs under varying time and resource constraints.
    • Acquiring critical formal writing skills by completing the literature survey report and final project report. 

• •  

• Dr. Hao Ji
  • Project 1 Description: Object detection which allows for the recognition, detection, and localization of multiple objects in images or videos, has many practical applications. In this project, we plan to develop an automated method leveraging synthetic data to train object detection models for custom objects. Students participating in this project will gain experience in synthetic data generation and training deep learning models for object detection tasks. 
  • Project 2 Description: Pose estimation, a fundamental task in computer vision, involves analyzing images or sensor data to infer the position and orientation of objects relative to a known coordinate system or reference point. In this project, we plan to develop an approach utilizing images or videos from multiple viewpoints to accurately estimate object poses in various environments. Students participating in this project will gain practical experience in processing images or videos, implementing, and fine-tuning deep learning models specifically designed for pose estimation tasks.
  • Project 3 Description: Krylov subspace techniques have demonstrated remarkable effectiveness in solving large-scale linear systems and optimization problems. In this project, we plan to develop, analyze, and implement efficient Krylov subspace methods to accelerate computations behind a range of machine learning and computer vision tasks. Students participating in this project will gain practical experience in designing high-performance numerical algorithms for machine learning and computer vision.
  • Mode: In-Person
  • Responsibilities: Students will work on this project in the Computational Intelligence Lab at CPP, where high-end GPU desktops and research equipment will be provided for students to research activities. Meetings will be arranged in each week to discuss research ideas and guide project progress.
  • Preferred Skills: 
    • For both Project 1 and Project 2, knowledge in deep learning is essential.
    • For project 3, proficiency in numerical methods and linear algebra, particularly Krylov subspace methods, is crucial.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: 
    • For Project 1 and Project 2, practical skills in training deep models for object detection and pose estimation, respectively.
    • For project 3, skills and knowledge in designing high-performance numerical methods for computer science applications.

 

• Dr. Ericsson Santana Marin
  • Project Descriptions: Despite the increasing investments in cyber-defense research, cybersecurity remains a huge and growing challenge. With the advent of the darkweb, the offensive community has been quietly and covertly industrializing itself at a pace that defenders cannot keep track of. Now, highly secure sites allow anonymous communities of malicious hackers to exchange ideas, techniques, and buy/sell malware and exploits worldwide, exposing organizations to an unprecedented number of threats. Without visibility into this new offensive industrial base, defenders do not know what is in the production pipeline and cannot properly prepare. As usual, they only react, trying to mitigate damages that range from unavailability of services until loss in reputation, revenue, or data. This dominant viewpoint of cyber-defense that solely focuses on defenders’ environment does not consider the other side of this security battle: the attackers. Current research has been demonstrating how the hackers’ digital traces existing in malicious hacker communities yield valuable insights into evolving cyber-threats. They can signal a pending offensive well before malicious activity is detected on a target system. To conduct cutting-edge cyber-threat intelligence research that will impact academia and industry, CALSys is offering the following projects:
    • Project 1 Description: Hacker data collection. We are working here on a multi-component system for cyber-threat intelligence gathering from the darkweb. By building a cyberinfrastructure at Cal Poly Pomona, we focus on collecting malicious hacking-related information from forum discussions and marketplaces product/service offerings to shine persistent light on the emerging technologies and capabilities of cyber-attackers. The work involves the design of Web crawlers, parsers, and machine learning classifiers to get credible hacker data and persist it in a relation database. This will be the largest public criminal repository that will power on security intelligent data-driven tools for cyber defense.
    • Project 2 Description: CAPTCHA Solver: To automate data collection from the darkweb, a spider needs to automatically fetch and download HTML pages. Malicious hacker sites, especially those existing in the Tor network, often use CAPTCHAs to avoid Web scrapers. This project uses image segmentation and deep learning to solve the alphanumeric text embedded in the CAPTCHA images so that our spiders can collect hacker data in real-time without humans in the loop.
    • Project 3 Description: Hacker Site Recommender. Currently, our research team is manually searching for criminal hacking websites to enlarge our database. This project uses machine learning to automate the site search process by first investigating .onion links embedded in forum posts by hackers. Then, we analyse the links' surrounding text, the previous and subsequent messages, and the landing pages to classify whether the listed website is potential target for scraping.
      
  • Mode: Hybrid
  • Responsibilities: We usually meet once/twice a week in person to discuss research ideas, challenges, accomplishments, and milestones. Apart from that, students can work remotely on their projects and will have online support from our project managers. We also use Discord for project coordination/support and GitLab as a source code repository and version control.
  • Preferred Skills: Intermediate Python programming skills are required. Knowledge of machine learning/data mining is recommended.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Depending on the project choice, students will learn how design and implement Web crawlers, parsers, classifiers, and how to persist/obtain data in/from a relational database. The machine learning classifiers will be able to identify criminal hacking content direct from the darkweb, solve CAPTCHAs, or recommend web sites.

Kinesiology & Health Promotion

• Dr. Mai Jara
  
  • Project Description: Interested in movement analysis for people with disabilities?
    The purpose of the project is to strengthen the safety of motorized mobility scooter drivers and to enhance the mobility experience of the elderly and people with mobility disabilities using these transportation modes.
    In this study, we will be analyzing the movement patterns from motorized scooter users with various disabilities and investigating how to prevent mobility scooter accidents using real-time environment data to tackle the challenges of dynamic road conditions.
    You don't need any previous experience in research. We will provide the orientation and training to be part of the research team.
    
  • Mode: Hybrid
    • Virtual: Meetings, data analysis and organization.
    • In-Person: Data collection will take place on site at Casa Colina.
  • Responsibilities: Data collection will be on Wednesday & Friday at Casa Colina Hospital in Pomona, Data analysis on your own time throughout the semester, and the literature review at your own time throughout the semester.
  • Preferred Skills: For research, we need dedicated committed students. Students need good communication and collaboration skills and follow instructions (reading and verbal).
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Knowledge in:
    • Properly assisting individuals with a disability with movement
    • Mobility scooter use
    • Assessment Implementation
    • Excel data input and analysis
      

Physics & Astronomy

• Dr. Breanna Binder
  
  • Project Description: The Rubin Observatory is going to revolutionize astronomy by repeatedly imaging the night sky every night. Searching for variable astrophysical objects is a key goal for Rubin, which will see "first light" this summer and begin its scientific observations in early 2025. Unlike our Sun, many stars reside in binary star systems -- and sometimes, from our perspective, these stars eclipse each other. In this project students will be simulating eclipsing binary star systems and generating synthetic Rubin observations. These simulated observations will prepare them for the "real thing" once the Rubin Observatory is operational.
    
  • Mode: Hybrid
  • Responsibilities: Students will be working either in the CPP Astronomy & Astrophysics Research Lab or on their own personal computer. The project will involve a significant amount of coding in Python (Jupyter Notebooks run via Google Colab). Students will work closely with the faculty member and will regularly collaborate with members of the Rubin Observatory staff. The student is also expected to perform a literature review and become familiar with the new Rubin Observatory.
  • Preferred Skills: An introductory astronomy course and some experience with Python is preferred, but not required.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Student will become proficient at Python. Students will learn the basic physics of eclipsing binaries, how to construct simulated light curves, and how to fit models to these synthetic data.

Don B. Huntley College of Agriculture

Agribusiness and Food Industry Management

• Dr. Yunkyung Lee
  
  • Project 1 Description: Market dynamics of plant-based protein: This research examines the potential market and economic impacts for plant-based protein meat as a substitute for animal-based protein, specifically understanding the factors driving the expansion of the pea-protein market. The study segments the market along the supply chain, from input producers, manufacturers, to consumers, and identify the market dynamics and explore opportunities stimulating the growth of the plant-based protein market. We design the survey to understand consumers’ preferences from consumer experiments and conduct them at CPP by using Qualtrics. Then, we gather, organize, process and present the data by using statistical program which will be disseminate into workshops and conferences. This effort enriches the dataset and enables a comprehensive analysis of market dynamics between the meat and plant-based protein industries.
  • Project 2 Description: Environmental footprint of agricultural production: This research explores the economic and environmental impact of agricultural production (i.e., crops, fruits, vegetables, or other manufactured food products) using the statistical software program, called open LCA. From this research, students will gain experience in devising life cycle assessment (LCA), analyzing data and conducting analyses to support decisions for environmentally sustainable business practices. Furthermore, this can be extended toward policies related to food and resources and develop the new policy for future changes, engaging agricultural producers with more sustainable production practices.
  • Mode: Virtual
  • Responsibilities: 
    • A typical day for the students would include one or the combination of the following:
      1. Literature search
      2. Consumer survey design
      3. Data collection in Qualtrics
      4. Analysis data
      5. Project progress meetings
      6. Poster presentation.
    • As a faculty mentor, I will have a meeting with a student once a week (mostly via zoom) to ensure the students get training and assistance as needed during the project. Students will also be guided to conduct relevant literature searches. Students are welcome to work asynchronously and flexibly as per their academic schedule during the summer of 2024 to complete the initial literature review and consumer experiment plan as well as data analysis and presentations. However, the component of the project would include:
      1. Weekly meetings with the faculty mentor to discuss project updates and next steps.
      2. Consumer survey design
      3. Data collection
      4. Analyze the data using statistical programs
    • Overall, 30-40 hours/week of work is required for the students to complete the project successfully.
      
  • Preferred Skills: 
    • Soft skills (good communication, problem solving, teamwork)
    • Beginner level knowledge of agricultural economics (microeconomics)
    • Data analysis (basic expertise in Excel at least)
      
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project:
    •  Literature search
    • Consumer survey design
    • Data collection in Qualtrics
    • Analysis data using statistical software
    • Market analysis of agricultural products
    • Economics 

Animal and Veterinary Science

• Dr. Essam Abdelfattah
  
  • Project Description: Castration, a routine management practice in beef production. Several studies have reported that castration induces pain, and distress that reduce production. Castration by banding is the second most frequently utilized method in cattle industry after surgical castration which includes application of a heavy elastic band around the neck of the scrotum. While banded castration tends to result in fewer complications in comparison to surgical castration, it is associated with chronic pain that can persist for a minimum of 42 days. The specific objectives of this study are to evaluate the effect of pain management in band castrated beef calves on 1) growth performance (body weight, withers, and hip heights); 2) calf behavior using accelerometer leg sensors; and 3) pain indicator.
  • Mode: In-Person
  • Responsibilities: The students who will participate in this project will be in charge of the following tasks:
    • Collecting literature reviews on the study topic.
    • Assisting the faculty with data collection from calves at the beef unit. There will be daily data collection regarding the behavior and health of calves. Therefore, I prefer students who feel comfortable around animals and have previous experience working with animals.
    • Assisting the faculty with study design.
    • Assisting with data entry into Microsoft Excel spreadsheets.
    • Assisting with data analysis.
    • Creating a poster and presentation for the symposium.
  • Preferred Skills: Students that feel comfortable working around animals, particularly calves, preferred. Experience with animal care, handling, and observation is required for this type of research. Students should be able to communicate their findings clearly and effectively with the faculty.
    
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: The students who participate in this project will gain experience in observing animal behavior, collecting health-related data, obtaining blood samples from animals, managing and caring for animals, conducting laboratory work with the ELISA technique, and managing data.

Apparel Merchandising & Management

• Dr. Helen Trejo
  
  • Project Description: Research will involve exploring wool as a viable material for footwear uppers. This will include using US wool yarns, developing a woven textile, textile testing to evaluate mechanical properties, and creating a prototype to convey proof of concept. This will include hands-on experience with textiles, developing a research paper, and an academic presentation.
  • Mode: Hybrid
    • Virtual: Based on weekly meetings ans timeline provided by faculty, student will work on their own/in a team to prepare a research paper and presentation to meet the program requirements.
    • In-Person: Hands-on textile development and/or prototyping based on student and faculty availability (Bldg 45, Room 129).
  • Responsibilities: Reviewing academic literature, hands-on experience in textile development, and testing (microscope analysis, mechanical tests).
  • Preferred Skills: None
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Knowledge of textile weaving, textile testing (microscopy, mechanical tests), academic reading, writing, presentation.

 

• Dr. Jiangning Che
  
  • Project Description: Agricultural waste, which is often underutilized, contains natural colorants with the potential for textile dyeing applications. Research focusing on California's agricultural byproducts as sources of natural colorants can benefit both the agricultural and fashion industries, offering a creative and sustainable solution for the utilization of agricultural waste products. By extracting dyes from these byproducts, textiles can be dyed to achieve desired hues, strengths, and acceptable permanence. The primary objective of this research aims to explore textile dyeing using agricultural wastes to achieve fashion-forward colors. The goal of this research is to achieve coloration applications with a broad color spectrum and the largest color gamut, featuring colors with rich depth and brightness, alongside the highest colorfastness. We will target on Almond, Orange, Pomegranate, and Avocado Wastes.
  • Mode: In-Person
  • Responsibilities:
    • Come to the lab, and plan experiments
    • Setup experiments
    • Analyze data and write reports
    • Finish lab experiments
  • Preferred Skills: Preferred apparel and textile knowledge, having a can-do mindset
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: 
    • Literature review
    • Dyeing method
    • Experimental design
    • Material labelling
    • Data gathering
    • Data analysis
    • Scientific writing
    • Textile testing

 

• Dr. Md Arif Iqbal
  
  • Project Description: With the rise of fast fashion, social media activism for sustainable fashion consumption has been an important issue in the global fashion supply chain. Recently, the social media influencers have become the very important player in shaping the consumption behavior of the Gen Z population. As sustainability became an important topic for the Gen Z population, the influencers in social media have an influence on these young consumers for their sustainable consumption behavior. It is imperative to study how social media influencers influence Gen Z consumers regarding their fashion consumption. This study will employ a content analysis and qualitative approach to investigate and understand the motives and perspectives of social media influencers in terms of sustainable fashion consumption. The main research question is how the social media influencers are impacting the behavior of the young consumers in the context of sustainable fashion consumption and what internal and external drivers impact the relationship of the influencer and Gen Z consumers while influencing their behavior towards sustainable fashion. The contents of two social medias especially TikTok and Instagram will be analyzed (content analysis). The thematic analysis will be conducted, and hermeneutic interpretation will be performed based on the analysis of the data. The grounded theory approach will be performed to establish the relationship among the themes found from the data analysis and will further be used for better explanation and interpretation of the data.
  • Mode: Hybrid
    • Only 2 in-person meetings, the rest of the project will be conducted remotely.
  • Responsibilities: Faculty mentor will train the students for conducting qualitative research. In the first two weeks, students will work on a literature review, and work on understanding the research concept. Data collection and analysis are the most challenging part of this project. Usually, the morning time will be time for reading articles, making annotated bibliography, and afternoon times will be the exploration of the data and coding the data. The faculty mentor will be supporting the students in all the tasks.
  • Preferred Skills: Students need good time management skill and a passion for research.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Students will gain the hands on experience of a qualitative research. They will learn the data analysis techniques in qualitative research. They also gain valuable knowledge about sustainability and consumption behavior of the fashion products.

Nutrition and Food Science

•  Dr. Bonny Burns-Whitmore
  • Project Description: This project will consist of interested students inputting collected data from human subjects onto spreadsheets, developing a hypothesis, developing a literature review associated with their data, performing the statistical analyses in Fall 2024, and presenting their research. The research examines strategies to decrease cardiovascular (CVD) risk factors by examining diet, participant blood risk factors, and body composition. We expect to "Expand Human Knowledge through New Scientific Discoveries," (discovering possible risk factor relationships for cardiovascular disease) and address "Economic Growth" (possible increase in foods associated with decreased risk for CVD), and National Challenges," (CVD and obesity).
    • Project 1: Vegetarian Study
    • Project 2: The Avacado Study
    • Project 3: The Coconut Oil Study
  • Mode: Hybrid
    • The project will consist of both in-person and virtual components, including weekly virtual meetings via Zoom.
  • Responsibilities: 
    • Meet with me for 30-60 minutes (check in, progress on research)
    • Input data
    • Meeting with other collaborators
    • Doing library research (for literature review)
  • Preferred Skills:
    •  Required: CITI certification to work with Human Subjects (Human Subjects 101)
    • Skills: The research assistants need to be able to utilize data, input data into excel, follow directions, meet weekly for meetings.
    • Coursework: A nutrition course (human or animal)
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Student will learn how to formulate hypotheses, perform literature searches, learn how to do statistical analyses, learn how to interpret results, learn how to organize data into tables, graphs, etc, put their data into a poster/oral presentation

 

•  Dr. Belal Hasan
  • Project Description: My research group is developing plant-based meats through extrusion process. It is a new category of products that are suitable for diversity of cooking styles and traditional cuisines. The current meat alternatives in the market are focused on patties and nuggets. However, these products are more suitable for western cooking style and can not serve for other cooking styles such as deep frying, braising and stewing. We have developed products that can stand long cooking time and high temperatures. It is clean label made of plant protein powders and water. The challenge is to establish cooking instructions and train the next generation of chefs.
    The specific objectives are:
    • To develop meat analogues at different water content using a lab scale extruder for optimized formulation and operation parameters.
    • To determine the effects stew cooking for prolonged time and using condiments on the mechanical properties including hardness and cohesiveness.
    • To establish cooking guide for training chefs to prepare plant-based stews inspired by global dishes.
      
  • Mode: Hybrid
    • Virtual: Need to meet students 5-6 times virtually to establish the fundamental knowledge and writing their summarized literature review from reading public and scientific articles. Need 2 virtual meetings to design the experiments and get familiar with the equipment that would be used in the lab.   
    • In-Person: 12-14 lab sessions that can vary in time depending on work. Can be about 3-5 hours.
  • Responsibilities: What the students should expect for every week:
    1. Work on literature review to gain the fundamental knowledge
    2. Summarize what the students are learning and discuss it in the weekly meeting
    3. Weekly meeting for 90 minutes to share the results, observations and design the next experiments
    4. Lab work, 18-20 hours of hands-on training on meat analogues and culinary art.
  • Preferred Skills: Committed to learn willing to learn, willing to share and work in team.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: Basic knowledge about physichochemical properties of foods such as mechanical properties, viscosity, basic cooking scales.

 

•  Dr. Fatheema Begum Subhan
  • Project Description: Community-Based Nutrition Intervention to Improve Diet Quality and Diabetes Management Among People with Type 2 Diabetes
    The prevalence of diabetes in the US has increased significantly. According to CDC 2020 data, 34 million Americans have been diagnosed with diabetes. More importantly, people of minority communities have large nutrition and health disparities, with a significantly high prevalence of diabetes, heart diseases, etc. In addition to pharmacotherapy, Medical Nutrition Therapy is the cornerstone in managing chronic diseases and preventing the progression of the disease comorbidities. However, many people of minority communities face several barriers to accessing health care services such as language barriers, lack of insurance, lack of knowledge to navigate the health system, and lack of culturally competent care. Hence it is imperative to offer community-based programs to make these services available and accessible to minority communities to improve their quality of life and reduce their risk of chronic diseases.
    Overall goal: To implement and evaluate the effectiveness of a nutrition intervention tailored towards the minoritized population in Pomona, California to improve their diet quality and diabetes management. Specific objectives: (1) To evaluate the efficacy of nutrition intervention in promoting better nutrition choices (as recommended by USDA dietary recommendations). (2) To evaluate the improvement in diabetes self-efficacy. (3) To evaluate improved health outcomes such as blood glucose control, lipid, and blood pressure management. (4) To describe the perceived strengths, limitations, effectiveness, and satisfaction of dietary intervention by study participants.
    Dr. Subhan has started conceptualizing and planning the Nutrition Education Curriculum for this work. With the help of a STARs Program Summer trainee, she will be working on developing the educational materials and resources required for the nutrition education intervention. The trainee will also be involved in implementing and evaluating the nutrition education program.
  • Mode: Hybrid
    • Virtual: Work on the development of resources, conduct literature searches, meetings, etc.
    • In-Person: Meetings (as needed), help with project implementation (such as hosting education seminars, food demos, etc) at a local not-for-profit organization in Pomona.
  • Responsibilities: 
    1. The student will research and collect relevant nutrition information from a variety of reliable resources
    2. The student will prepare educational materials including handouts, presentations, and other resources needed to offer a nutrition education program.
    3. The student will be involved in offering educational activities, food demos, and taste testing to enable participants to food preparation methods and provide an opportunity to incorporate them into their meals.
    4. Participate in evaluating the effectiveness of the program using questionnaires, body measurements, and conduct blood tests for Hemoglobin A1c and lipids using the finger prick method
  • Preferred Skills:
    • Coursework – Nutrition major students in their junior or senior year who have completed the following courses can apply: NTR 3350, NTR3450/A
    • Bilingual – English and Arabic (as they will help in translating the educational material)
    • Proficient in using MS office- Students should be comfortable using MS word and PowerPoint as we will using these platforms to prepare our resources and conduct classes
    • Basic food preparation skills – Students should be comfortable demonstrating simple recipes such as salad, smoothies, wraps, and other creative ideas to encourage students to try new foods, and teach simple healthy preparation methods Familiarity with other resources such as CANVA or other online platforms to conduct fun interactive activities will be an added advantage
    • Research Skills – Familiarity in conducting anthropometric assessments (weight, height, body circumference) will be an advantage
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: This project will provide hands-on experience to students to develop and enhance the following skills:
    • Research and analytical skills
    • Enhance their writing skills
    • Leading group education session
    • Conducting food demos and sharing healthy food preparation techniques

Plant Science

•  Dr. Eshwar Ravishankar
  • Project Description: Controlled Environment Agriculture (CEA) offers potential for year-round production, while also minimizing labor usage, water use and mitigates the risk of pests while optimizing growing conditions to maximize yield. In California, farmland is being lost every year due to urban and suburban development and CEA systems can act as a valuable contributor to the local production of nutritious microgreens for a balanced diet. However, till date urban CEA have not been proved as a sustainable urban food production method for local food systems. This project retrofits a shipment container at AGRIscapes in Cal Poly Pomona (CPP). The container was equipped to monitor and control abiotic plant growth factors such as light, temperature, carbon dioxide, and relative humidity using energy efficient LEDs, air conditioner, and humidifier with a dedicated controller added for indoor climate control and monitoring. This study aims to quantify the costs involved in providing inputs such as water, and irrigation use, electricity, CO2, and labor for achieving a target yield of microgreens in a nominally operated indoor production environment. Project deliverables will include the production of optimal yield of microgreens while ensuring cost efficient practices in CEA systems and compare production costs with existing market values to provide valuable insights into urban CEA practices.
  • Mode: Hybrid
  • Responsibilities: 
    • A typical day for the students would include one or the combination of the following:
      1. Literature search
      2. Experimental design
      3. Data collection in indoor container farm.
      4. Analysis
      5. Project progress meetings
      6. Poster presentation.
    • As faculty mentor, I will be available Monday through Friday in person/remotely to ensure the students get hands-on training and assistance as needed during the project when they are working in the lab or greenhouse. Students will also be guided to conduct relevant literature search. The in-person component of the project would include:
      1. Weekly meetings with the faculty mentor to discuss project updates and next steps.
      2. Experimental design
      3. Data collection.
  • Preferred Skills: Soft skills:
    • Problem-solving skills
    • Attention to detail
    • Good communication skills (written and oral)
    • Collaboration and teamwork
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: 
    • Plant biology and physiology
    • Imaging Techniques
    • Basic programming
    • Horticulture lab technoques
    • Presentation skills
      

Mineral and Energy Economy Research Institute of the Polish Academy of Sciences

Energy Economics

• Dr. Pablo Benalcazar
  
  • Project Description: TThe deep decarbonization of the power, heating, and cooling sectors is one of the world’s greatest challenges, as it entails intricate and diverse tasks that will have profound economic and social ramifications. Until now, researchers have explored a wide variety of technological pathways, but there is still much work to be done in terms of decarbonizing national and local energy systems.
    In this project, we will investigate the application of an electricity capacity expansion model (computer model) to simulate the mid- to long-term evolution of a power system, considering both current and future climate scenarios. Furthermore, the student(s) involved in this project will have the opportunity to gain a fundamental understanding of energy system models and optimization.
    During the first part of the project, the student(s) will conduct a literature survey of strategic methods for decision support within the power and heating industry. In the second part of the project, under the guidance of the faculty mentor, the student(s) will employ an optimization-based capacity expansion model to assess decarbonization scenarios at a country level.
    Upon successfully completing the project, the student(s) will be offered an opportunity to expand their research skills by developing a manuscript in the style of a scientific paper.
    
  • Mode: Virtual
  • Responsibilities: This project requires the student(s) and the faculty mentor to collaborate remotely. Additionally, the student(s) must be able to attend regularly scheduled virtual meetings. During the meetings, the research team will define weekly goals and discuss the progress of the project.
    The student(s) participating in the project will conduct a literature review of frameworks and methods commonly used for capacity expansion planning and long-term power system transformations. The student(s) will design and implement a comprehensive plan for developing decarbonization scenarios. Additionally, under the guidance of the faculty mentor, the students will undertake the following activities: data collection, statistical analysis, scenarios conceptualization, and model implementation.
  • Preferred Skills: 
    • The student(s) should have a strong interest in energy systems engineering and be enthusiastic about research.
    • This project is interdisciplinary; however, the student(s) should feel comfortable with linear algebra (MAT 2240, MAT 2250, or similar course) and have completed some introductory physics courses (PHY 1510/L and PHY 1520/L).
    • The project will require the student(s) to solve optimization problems and build energy systems models using a domain-specific modeling language for mathematical optimization. Therefore, the student should have completed some courses in computer programming.
  • Skills/laboratory techniques/knowledge that the students will gain from participating in this project: 
    • The student(s) will develop and strengthen the soft skills needed to complete research projects.
    • The student(s) will acquire proficiency in a programming language.
    • The student(s) will understand the process of energy systems modeling (e.g., problem definition, solution development, implementation, and verification).
    • The student(s) will acquire an academic background and hands-on experience in developing tools for decision support in energy planning.