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Omar E. Mora

Omar E. Mora

Professor

Civil Engineering Department, College of Engineering

Email

oemora@cpp.edu

Phone number

909.869.2656

Office location

Building 9 - Room 421

Office hours

T TH | 8:30 AM - 10:30 AM

Who I Am

My name is Omar E. Mora, and I am a Professor in the Civil Engineering Department at ½ûÂþÌìÌÃ. I have a background in land surveying and geomatics engineering, with degrees from ½ûÂþÌìÌà (B.S.), Purdue University (M.S.), and The Ohio State University (Ph.D.). I'm also a licensed Professional Land Surveyor in California and hold FAA certification to operate drones commercially.

My research focuses on Unmanned Aircraft Systems (UAS), photogrammetry, Light Detection and Ranging (LiDAR), deep learning, and geospatial solutions for civil, construction, and environmental engineering.

I’m an active member of several professional organizations, including ASPRS, CLSA, NSPS, and ASCE, which help me stay engaged with the latest developments in the field.

I’m an educator shaped by the mentors who believed in me and guided my path. Their influence sparked not only my passion for teaching but also a deep commitment to giving back. I carry their legacy forward by sharing my knowledge, supporting others, and working to inspire the same sense of curiosity, confidence, and purpose in the next generation that my mentors inspired in me.

When I’m not in the classroom, you’ll usually find me hanging out with family and friends or enjoying some sports. I love playing soccer and cheering on my favorite teams like AC Milan, Cruz Azul, and the Columbus Crew. I’m also a big fan of the Los Angeles Lakers, Kings, Dallas Cowboys, Chicago White Sox, and The Ohio State Buckeyes so there’s always a game on my radar!

Besides sports, I enjoy going for walks, staying active with some exercise, gardening, and trying out new foods whenever I can. I’m pretty approachable and always up for a good chat, so don’t be shy. Always open to a friendly hello when you see me.

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, ½ûÂþÌìÌÃ, 2007

Licenses & Certifications

  • PLS, Professional Land Surveyor in the State of California
  • sUAS, Federal Aviation Administration Part 107 Remote Pilot Certificate
  • Certified TOP Remote Pilot, Level 1 & 2 by the Association for Uncrewed Vehicle Systems International (AUVSI)

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

Journals
  • Cheng, W., Rogovoy, K., Sharifiilierdy, S., Mora, O., Lu, R., & Cheng, Y. (2024). Enhancing Daily Crash Count Prediction using Deep Learning with Window Size Selection and Seasonality Predictor Integration. Transportation Research Record, 2679(3), 1037-1053.  (Original work published 2025)
  • 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, 2677(1), 1564-1581.  (Original work published 2023)
  • Truong, L. N. H., Mora, O. E., Cheng, W., Tang, H., & Singh, M. (2021). Deep Learning to Detect Road Distress from Unmanned Aerial System Imagery. Transportation Research Record, 2675(9), 776-788.  (Original work published 2021)
  • McMahon, C., Mora, O. E., & Starek, M. J. (2021). Evaluating the Performance of sUAS Photogrammetry with PPK Positioning for Infrastructure Mapping. Drones, 5(2), 50.
  • Mora, O. E., Langford, M., Mislang, R., Josenhans, R., & Chen, J. (2020). Precision performance evaluation of RTK and RTN solutions: a case study. Journal of Spatial Science, 67(3), 473–486. 
 
Other Publications
  • 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, , 2023.
  • Perez, F. J., Nguyen, D. V., & Mora, O. E. (2022, September 12). Vision-based calibration study for structural displacement measurement. 1st ½ûÂþÌìÌà Civil Engineering Conference, 1(1), 65–72.
  • 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, , 2022.
  • 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, , 2022.
  • Perez, F. J., & Mora, O. E. (2022). A vision-based system for structural displacement measurement. Proceedings of the 7th World Congress on Civil, Structural, and Environmental Engineering (CSEE'22), ICSECT 127, 1–8.