UC Irvine

Name: Aaron Barth
Title: Supermassive black holes in active galaxies
Description: Supermassive black holes are found in the centers of essentially all large galaxies, and the growth of these black holes during active accretion phases can have a major influence on the host galaxy environment. My group carries out observational research on diverse problems related to determining the masses of black holes in galaxy nuclei, understanding the physics of gaseous accretion onto black holes, and examining the relationships between the black holes and the host galaxies that they inhabit. Examples of research topics for summer projects include variability and reverberation mapping of active galaxies, modeling the structure of AGN host galaxies, measurement of AGN host galaxy kinematics to study gaseous outflows or determine black hole masses, and carrying out measurements to determine the masses of black holes in quasars from their spectral properties.
Preferred qualifications: Some familiarity with Python, and knowledge of astronomy at least at the level of an introductory college-level course.

Name: Albert Siryaporn
Title: Physics of living systems
Description: Our lab investigates the dynamics of living organisms. Bacteria is one of the best systems in which to pursue this question due to its relative simplicity and the wealth of available tools. We explore how physical properties of a system (i.e., shear stress, advection, diffusion) impact the development of bacteria across multiple length scales, from single cell units into multicellular organisms. Our projects seek to understand the role of physical properties in the development of dense biofilm communities. 
We design and fabricate microfluidic devices, perform cellular manipulation, and measure cellular dynamics using optical microscopy and computational analysis. The lab connects experiment and theory through the development of models and simulations.
Preferred qualifications: Preferred coursework minimums: Intro chemistry, intro chemistry lab, Intro physics

Name: Anyes Taffard
Title: Research on ATLAS at the Large Hadron Collider
Description: Prof Taffard is an experimental Particle Physicist performing research with the ATLAS experiment at the Large Hadron Collider (LHC). Her research focuses on searches for new physics using the Higgs boson as a new tool for discovery. These searches may shed light on dark matter and the mechanism behind electroweak symmetry breaking that could explain why the Standard Model Higgs is so light.
To achieve her long term physics goals, her group contributes to the experiment’s operation efforts and detector improvement projects. These include projects aimed at the ongoing Run-3 data taking (2022-2025) as well as the High-Luminosity LHC (HL-LHC: 2029-2040) running periods. In particular, her group is involved in improving the trigger capabilities of ATLAS for the HL-LHC data taking. The ATLAS trigger permits to select the events of interest for data analysis and thus is a critical component to achieve the ATLAS physics program. These projects make use of the state of the art technologies using FPGA and GPUs to implement highly performant and fast algorithms (including machine learning algorithms) to perform particle identification.
The student will get involved in either data analysis or trigger projects.
Preferred qualifications: Applicants should have experience in programming (python and/or C++) as well as data analysis. Applicants should have interests in particle physics experiments and analysis of data from the LHC. Interests in learning how to use FPGA/GPUs are welcomed. The project will be scaled to the experience level of the student and provide sufficient background to effectively execute the project over the summer program.

Name: Huolin Xin
Title: High-energy cathodes for lithium-ion batteries
Description: The Cal-Bridge scholar will work on an R&D project for a high energy cathode that powers next-generation EVs. The works is relevant to environment justice and making our future sustainable.
Preferred qualifications: Being able to work in the lab.

Name: Javier Sanchez-Yamagishi
Title: Two-dimensional nanoelectronics
Description: Big picture goal: study the quantum electronic properties of new materials. We study quantum materials that are only a few atoms thick made of carbon (graphene), bismuth, and other elements. This requires making devices and measuring their electrical properties at cryogenic temperatures and at high magnetic fields. This research establish the basic understanding of new materials that could be used in future electronic devices in phone or computers.
Specific projects: Help develop new methods to make nanoelectronic devices and study their properties. Projects include working with laser cutters to make microscopic devices, designing and machining components, simulating nanoelectronic systems on the computer, designing and soldering electronic circuits, building a laser microscope from scratch, or programming in Python to automate experiments.
Preferred qualifications: experience with making things (construction/design/electronics/robotics/art) and/or programming.

Name: Jianming Bian
Title: Cold Electronics and Machine Learning for neutrino experiments
Description: We are looking to hire Summer Research Assistants to help the DUNE/NOvA neutrino physics group at UCI with an ongoing research study:
Responsibilities: Task 1. cryogenic electronics tests and performance study for liquid-argon neutrino detectors (amplification and digitization ASIC chips), Task 2. machine learning for particle identification and energy reconstruction in neutrino experiments
Preferred qualifications: Python

Name: Jin Yu
Title: Computational Biophysics Research on Mininature Biomolecular Machinery
Description: Biomolecular machinery play important roles in cellular functions with high efficiency and accuracy, despite of thermal fluctuations and environmental complexity. Based on molecular mechanics, statistical physics, and stochastic methods, we are particularly interested in deciphering operation mechanisms of those microscopic machinery, particularly, in genetic and epigenetic regulations where human diseases such as cancers are highly impacted. Students may work on an essential part of a molecular engine or regulatory domain by modeling and simulating comparatively small pieces of protein and DNA/RNA systems from fundamentals, conducting visualization and data analyses, and connecting physical laws to biomolecular implementations.
Preferred qualifications: The researches are highly interdisciplinary. Understanding general physics and/or chemistry, motivated in studying living systems, good at quantitative skills, and comfortable working with computer softwares are all preferred.

Name: Jing Xia
Title: Optical Investigation of Novel Materials for Quantum Computers
Description: The aim is to use our unique high-precision optical and electrical probes to study novel phases in condensed matter systems. Some of these phases are characterized by spontaneous symmetry breaking while others possess topological order. We are particularly interested in topological insulators, topological superconductors, 2D materials, and quantum Hall systems. Their novel properties may be exploited for robust quantum computers.
Preferred qualifications: none

Name: Michael Ratz
Title: Fermion masses and modular forms
Description: Modular flavor symmetries are a promising approach to flavor. This project aims at relating modular forms to properties of mass matrices of elementary particles.
Preferred qualifications: his project requires a strong mathematical background and analytical skills

Name: Shirley Li
Title: Understanding neutrinos with next-generation neutrino experiments
Description: Neutrinos are among the least understood elementary particles. They have a strange behavior called neutrino oscillation – neutrinos can change their flavors while propagating. The discovery of neutrino oscillation confirmed that neutrinos have masses, which was not predicted by our theoretical framework. Since its discovery, there have been intense efforts to understand how neutrinos oscillate and to shed light on the nature of neutrinos. With the next generation neutrino oscillation experiments projected to reach unprecedented precisions, the need for theoretical modeling of how neutrinos interact with matter, a key step to detect neutrinos in these experiments, has also intensified. In this project, the student will investigate how to incorporate experimental data to improve the modeling of neutrino-matter interactions, therefore allowing better measurements of neutrino properties from future experiments.
Preferred qualifications: none

Name: Steph Sallum
Title: Imaging Planet Formation with the Keck Telescopes
Description:  This project would involve using high angular resolution imaging data from Keck Observatory to understand how planets form and evolve. The Cal-Bridge Scholar would work with observations of protoplanetary disks - the disks of dust and gas that remain after the star formation process, and the sites of planet formation - from the 10-m Keck telescopes. The project would involve using these images to understand the conditions of planet formation on solar-system scales, both by searching for actively-forming planets, and by understanding the conditions in the protoplanetary disk at about the Sun-Jupiter orbital distance. In addition to working with imaging data, the Cal-Bridge Scholar would participate in observing, and would join an active research group addressing many open questions in planet formation. 
Preferred qualifications: python programming skills and basic familiarity with terminal use

Name: Thomas Scaffidi
Title: Hydrodynamics of Quantum Matter
Description: Imagine preparing a set of qubits in a simple product state, and time evolving it under a given Hamiltonian which couples them. The state of the system is going to become more and more complex as entanglement building up. If one wanted to store information about the system on a classical computer, the number of bits required would increase exponentially with time. Yet, after a while one expects the system to reach a thermal equilibrium, that should be describable in terms of a few macroscopic quantities, like temperature. In the field of quantum dynamics, the goal is to understand this extremely rich process, from the microscopic quantum chaos at short times, to the emergent hydrodynamics at long times. Hydrodynamics is a universal description of fluids which emerges at length and time scales much larger than those that govern microscopic, atom-level processes. While it has been useful in almost all fields of physics, its applications in solid state physics have been fairly restricted. Recently, however, important strongly correlated systems have been found which exhibit universal transport properties which cannot be explained by a single particle picture, and for which a non-perturbative approach like hydrodynamics is warranted. The opportunity provided by these systems is twofold: it enables the study of novel regimes of transport with unique properties, and it also generates exotic types of hydrodynamic theories which would not occur otherwise ``in vacuum''.
The project concerns a new regime of electronic transport in which electrons behave like a viscous fluid, and for which the ubiquitous Ohm’s law is replaced by the much richer Navier-Stokes equation. Interest in this regime was recently amplified by a series of experiments in 2D materials like graphene. The goal of the project is to calculate from first-principles the precise form of the scattering operator between electrons in realistic models for novel quantum materials, in order to predict hydrodynamic behavior and discover novel phenomena. In practice, this involves the derivation of scattering properties using perturbation theory and the calculation of high-dimensional integrals using a variety of numerical methods.
Preferred qualifications: Experience with numerical physics (in python, julia or other languages) is a plus.

Name: Vivian U
Title: From Galactic Cores to the Cosmic Web -- A Study of Galactic Winds with HST and JWST
Description: Galaxies, the basic building block of the universe, are considered "cosmic ecosystems" because of the energy transfer processes that regulate the life cycle of their constituents: stars, gas, black holes, and dust. These "feedback" processes, such as winds and shock waves, are thought to be important in how they move things around and subsequently govern the evolution of galaxies throughout cosmic history, but the detailed physics are poorly understood at small scales. Since July 2022, the James Webb Space Telescope (JWST) have opened up a new window for exploring the astrophysical processes previously obscured by dust in the infrared with an advanced instrument suite. Specifically, our group has capitalized on the JWST capabilities to observe a sample of nearby galaxy mergers where the interaction of close galaxy pair enhances the black hole activity and feedback, making them some of the most energetic phenomena in the local universe. We also have complementary optical data from the Hubble Space Telescope (HST) and Keck Telescope that probe the galactic scale winds beyond the field of view of JWST.
In this project, the Cal-Bridge scholar will have the opportunity to learn data processing and analysis of astronomical data such as images, spectra, or integral-field data from HST, JWST, or Keck Telescope. The student will learn to display astronomical data in existing image-viewing softwares, write and execute Python codes to analyze line emission captured in the data, make maps to identify regions of interest within the galaxy mergers, and generate histograms and scatter plots to present the data. The anticipated results will be presented in an upcoming AAS meeting.
Preferred qualifications: The project is most suited for an astronomy, physics, or computer science major. While Python programming experience (including the use of Jupyter notebooks and basic command line environment) may be useful, it is not required. These are skills that the student is expected to learn during the project.

Name: Jack Xin
Title: Interacting Particle Methods for Parabolic-Hyperbolic Chemotaxis Systems
Description: The project aims to develop interacting particle method (IPM) for computing parabolic-hyperbolic Keller-Segel type chemotaxis systems with applications to angiogenesis. The IPM method computes evolution of particle positions obeying a coupled system of stochastic differential equations. It is mesh-free and self-adaptive by design. We shall benchmark it with analytical solutions and finite difference method in one and two space dimensions in the large particle number limit, then (if progress permits) apply it to sharp interface motion (tumor growth) in three space dimensions.
Preferred qualifications: Matlab or Python programming skills, basic knowledge of probability and stochastic process

Name: Nathan Kaplan
Title: Sizes of partitions with a given set of hook lengths
Description: Integer partitions have been a topic of extensive interest from the mathematical community for hundreds of years, including important results of Euler, Hardy, Ramanujan, and others. A partition of a positive integer n is a way of writing n as a sum of positive integers where the order does not matter. For example, there are five partitions of 4: 4, 3+1, 2+2, 2+1+1, 1+1+1+1.
A partition of n comes with a multiset of n positive integers called its multiset of hook lengths. These numbers play an important role in the correspondence between partitions of n and representations of the symmetric group on n elements. If you ignore repetition of these numbers you get the set of hook lengths of the partitions. This set has some algebraic structure— it is the complement of a numerical semigroup. A numerical semigroup is a subset of the nonnegative integers N_0 that is closed under addition, contains 0, and has finite complement in N_0. There is a huge literature about numerical semigroups, and a key idea of this project is to use ideas from the theory of numerical semigroups to study questions about partitions.
It is not so difficult to see that there are only finitely many partitions with a given set of hook lengths. The goal of this project will be to investigate their sizes. Here is an example of a question that we will study.
Q: Let S be a numerical semigroup and let H = N_0 \ S be its complement. What is the smallest partition whose set of hook lengths is equal to H?
Preferred qualifications: It would be helpful if students have taken an abstract algebra course (but it is not required). This project will be most interesting to students who are eager to learn more about combinatorics and number theory, but no background in those subjects is required. No programming experience is required, but we will be doing a lot of calculations and working through examples using a computer algebra system as a tool, so it would be helpful if a student is interested in learning to write programs.

Name: Volodymyr Minin
Title: Nowcasting and forecasting of infectious disease dynamics
Description: My research group works with the California Department of Public Health on a variety of projects aimed at providing quantitative tools for situational awareness to policy makers. The Cal-Bridge scholar will evaluate performance of our forecasting and nowcasting using historical data and/or implement improvements to these methods.
Preferred qualifications: Exposure to statistical inference, ideally more than one intro Stat class, R programming, some math classes would help too (e.g., ODEs, probability)

Name: Aparna Chandramowlishwaran
Title: Foundational Neural PDE Solvers
Description: Neural PDE solvers strive to approximate the solution of partial differential equations using neural network models. On high-dimensional multi-scale problems, neural solvers have potential advantages in terms of performance and complexity compared to traditional numerical solvers. Neural solvers have been successfully demonstrated in several scientific fields including climate science, heat transfer, and material science. These impressive results showcased the building blocks of the current state-of-the-art in scientific machine learning. Nevertheless generalization to different input conditions, geometries, and scales is a challenging problem. This project's goal is to design and train foundational models for neural PDE solvers that can generalize to a larger-class of problems than possible today.
Preferred qualifications: Strong foundations in Python, PyTorch and Machine Learning is required. Knowledge of PDEs and SciML is optional but a bonus.

Name: Chen Li
Title: Using Texera to support collaborative data science
Description: Texera ( is an open source system we have been developing in the past seven years. We will study how to use the system to support collaborative data science.
Preferred qualifications: Java, Python, and frontend programming skills.

Name: Ian Harris
Title: Security in Embedded Systems
Description: [not provided]
Preferred qualifications: basic programming

Name: Iftekhar Ahmed
Title: Using ChatGPT for Automated Refactoring of Energy-Efficient Software Tests
Description: Software energy consumption reached 15% of the world's total energy consumption in 2020, and it is predicted to be responsible for 20% of global energy usage by 2025. Software applications consume energy while being used as well as being developed. However, as one of the main development activities, the energy efficiency of software testing has not received much attention from researchers and developers, even though millions of lines of test code that are being executed daily consume a considerable amount of energy. One of our previous research has shown the relationship between the presence of various types of test smells in test cases and how that impacts the energy efficiency of software testing by consuming more energy than required. In this project, we focus on refactoring those energy-greedy test smells automatically.
Researchers have started leveraging advanced Large Language Models (LLMs) to automate various Software Engineering tasks. Recently, a powerful LLM, ChatGPT, has received much attention from researchers. It was trained using reinforcement learning that aligns better human intentions. Studies have shown that ChatGPT is promising in outperforming existing state-of-the-art LLMs in many Software Engineering tasks. In this project, we investigate the feasibility of ChatGPT in refactoring energy-greedy test smells.
Students will design various prompts for ChatGPT to generate refactorings given a smelly test. Students will use different prompt engineering techniques to improve the generated test case quality. Students will also incorporate additional information other than the given test case that may be helpful for ChatGPT to refactor the test case.
The outcome of the project will be a toolset for refactoring test smells with ChatGPT. These tools can be integrated into the development workflow with ease. Students will develop the skill of using prompt engineering techniques and applying them to ChatGPT and other LLMs. Students will also learn the basics of software testing and Natural Language Processing (NLP).
Preferred qualifications: 1. Comfortable programming using Python 2. Basic experience with machine learning.

Name: Matthew Harding
Title: Alternative Credit
Description: One set of projects at my lab concerns the economic analysis of the behavior of lower-income individuals who rely on the alternative loan market. This includes payday loans or car title loans etc. We are investigating ways in which individuals search for these loans and what the impacts are once they obtain these loans. Often this may lead to debt spirals where they cannot repay the original loans and get another loan at a high interest rate and so on. Very quickly one small loan ends up as a major loan which they fail to pay back pushing people further into poverty. There are numerous policies that impact this market and it is a very dynamic environment eg borrowing behavior changed during and after the covid crisis. In addition to economic analyses and research we are also maintaining a public facing website for this effort providing information on this to the general public.
Preferred qualifications: data skills and programming in R or Python

Name: Solmaz Kia
Title: Vision-based robot motion planning
Description: This project involves using the object detection algorithm YoLov5 for robot motion planning in an environment with obstacles. Yolo will be utilized to identify and localize the obstacles. Then the student will design a motion planning algorithm to find the shortest path for a robot to travel from a given initial point to a goal point. The student will have access to the vision and the robotic system in the lab to design and execute this project. Given the student's background and interest the mission can be adjusted but the project will involve combining vision-based object detection with safe robot motion planning. The student will receive support from the PI and her graduate students to accelerate the pace of learning how to use software and program for robots.
Preferred qualifications: Familiarity with Python or Matlab programing will be a plus

Name: Wayne Hayes
Title: Computational Science - from cells to galaxies
Description: Students should visit for available projects in my lab.
Preferred qualifications: Comfortable with Linux