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Omar E. Mora

Omar E. Mora

Associate Professor

Civil Engineering Department, College of Engineering

Email

oemora@cpp.edu

Phone number

909.869.2656

Office location

Building 9 - Room 421

Office hours

M | 8:00 AM - 9:00 AM M | 11:00 AM - 1:00 PM F | 8:00 AM - 9:00 AM

Education

  • Ph.D. Geodetic Engineering, Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, 2015
  • M.S. Geomatics Engineering, Lyles School of Civil Engineering, Purdue University, 2010
  • B.S. Civil Engineering - Geospatial Engineering Option, Civil Engineering Department, California State Polytechnic University, Pomona, 2007
  • PLS, Professional Land Surveyor in the State of California
  • sUAS, Federal Aviation Administration Part 107 Remote Pilot Certificate

Teaching

  • CE 1011/1011L – Surveying Engineering & Laboratory (Undergraduate)
  • CE 2011 – Technical Communications (Undergraduate)
  • CE 2070 – Computer Programming and Numerical Methods (Undergraduate)
  • CE 3301 – Engineering Geomatics (Undergraduate)
  • CE 4301/4301L - Digital Mapping & Laboratory (Undergraduate)
  • CE 4350/4350L – Photogrammetry & Laboratory (Undergraduate)
  • EGR 4810/4820/4830 – Project Design Principles and Applications (Undergraduate)
  • CE 5990 – Applications of Geospatial Technologies for Practitioners (Graduate)

Selected Publications

  • Refereed Journals:
  1. Cheng, W., Rogovoy, K., Sharifiilierdy, S., Mora, O.E., Lu, R., & Cheng, Y., 2024. Enhancing Daily Crash Count Prediction using Deep Learning with Window Size Selection and Seasonality Predictor Integration. Transportation Research Record.
  2. Truong, L.N.H., Clay, E., Mora, O.E., Cheng, W., Singh, M., & Jia, X., 2022. Rotated Mask Region-Based Convolutional Neural Network Detection for Parking Space Management System. Transportation Research Record.
  3. McMahon, C., Mora, O.E. and Starek, M.J., 2021. Evaluating the Performance of sUAS Photogrammetry with PPK Positioning for Infrastructure Mapping. Drones, 5(2), p.50.
  4. Truong, L.N.H., Mora, O.E., Cheng, W., Tang, H. and Singh, M., 2021. Deep Learning to Detect Road Distress from Unmanned Aerial System Imagery. Transportation Research Record.
  5. Mora, O.E., Langford, M., Mislang, R., Josenhans, R. and Chen, J., 2020. Precision performance evaluation of RTK and RTN solutions: a case study. Journal of Spatial Science, pp.1-14.
  6. Mora, O.E., Chen, J., Stoiber, P., Koppanyi, Z., Pluta, D., Josenhans, R. and Okubo, M., 2020. Accuracy of stockpile estimates using low-cost sUAS photogrammetry. International Journal of Remote Sensing, 41(12), pp.4512-4529.
 
  • Other Refereed Publications:
  1. Tan, S., Mora, O.E., and Tran, C.: EVALUATING THE INFLUENCE OF SPATIAL RESOLUTION ON LANDSLIDE DETECTION: A CASE STUDY IN THE CARLYON BEACH PENINSULA, WASHINGTON, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-3-2023, 241–248, https://doi.org/10.5194/isprs-archives-XLVIII-M-3-2023-241-2023, 2023.
  2. Clay, E.R., Lee, K.S., Tan, S., Truong, L.N.H., Mora, O.E., and Cheng, W.: PERFORMANCE EVALUATION OF BUILDING FAÇADE RECONSTRUCTION FROM UAS IMAGERY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-M-2-2022, 65–69, https://doi.org/10.5194/isprs-archives-XLVI-M-2-2022-65-2022, 2022.
  3. Clay, E.R., Lee, K.S., Tan, S., Truong, L.N.H., Mora, O.E., and Cheng, W.: ASSESSING THE ACCURACY OF GEOREFERENCED POINT CLOUDS FROM UAS IMAGERY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-M-2-2022, 59–64, https://doi.org/10.5194/isprs-archives-XLVI-M-2-2022-59-2022, 2022.
  4. Perez, F.J. and Mora, O.E., 2022. A Vision-Based System for Structural Displacement Measurement. 7th World Congress on Civil, Structural, and Environmental Engineering (CSEE'22), ICSECT 127, pp.1-8.
  5. Chen, J., Mora, O.E., and Clarke, K.C.: ASSESSING THE ACCURACY AND PRECISION OF IMPERFECT POINT CLOUDS FOR 3D INDOOR MAPPING AND MODELING, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W6, 3–10, https://doi.org/10.5194/isprs-annals-IV-4-W6-3-2018, 2018.