David Sathiaraj is the Director of Data Science at Trabus Technologies where he leads an AI/ML and Data Science team. He is also an Adjunct Professor at Point Loma University and San Diego State University. Prior to that he held a faculty position in Data Science at Louisiana State University. His areas of research include applying AI/ML and Data Science on diverse domains such as Environmental Informatics, Maritime Transportation, Healthcare, Predictive Maintenance and Political Science.
Education
- Ph.D., Computer Science and Engineering, Louisiana State University
- M.S., Computer Science, Louisiana State University
- M.S., Industrial Engineering, Louisiana State University
- B.E., Mechanical Engineering, Osmania University
Courses Taught
- Data Science Project I - MTH4142
- Project for Data Analytics Minor I - MTH4162
Experience in Field
- Director of Data Science, Trabus Technologies, San Diego, CA, 2020-Present
- Adjunct Professor, Point Loma Nazarene University, 2022-Present
- Adjunct Professor, San Diego State University, 2021-Present
- Associate Director, NOAA Southern Regional Climate Center, Louisiana State University, 2013-2019
- Asst. Professor, Louisiana State University, 2015-2019
Dissertations, Presentations, and Publications
- An AI-Based Methodology for Digitizing Historical Tabular Data with High Accuracy, N Woolsey, E Rohli, D Sathiaraj, 2025 IEEE International Conference on Information Reuse and Integration and …, 2025
- Smart sensor system and method for threat detection and response based on detection of a vocal phrase, R Sanchez, A Salindong, D Sathiaraj, N Woolsey, SR, Moldovsky, A Tec, ..., US Patent App. 19/092,824, 2025
- Improving System Sustainment through an Integrated Modeling Schema Coupled with Effective Execution of the Lifecycle Sustainment Plan, J Bradley, W Baker, A Salindong, D Sathiaraj, T Lemerande, Acquisition Research Program, 2025
- Smart sensor system for threat detection, R Sanchez, A Salindong, D Sathiaraj, N Woolsey, SR Moldovsky, A Tec, ..., US Patent 12,271,971, 2025
- Artificial-intelligence-based prediction of storage capacities in water reservoirs, D Sathiaraj, EV ROHLI, N Woolsey, US Patent App. 18/439,496, 2024
- A Fast Cloud Technique For On-Demand Generation of High-Resolution Climate Interpolations, N Woolsey, E Rohli, D Sathiaraj, AGU Fall Meeting Abstracts 2023 (595), IN23B-0595, 2023
- Ripple Effects of Fall 2022 Lower Mississippi River Drought and Impacts on Supply Chains and Inland Water Transportation, E Rohli, A Smith, D Sathiaraj, AGU Fall Meeting Abstracts 2023 (1254), GC33I-1254, 2023
- Predictive analytical system and method, D Sathiaraj, US Patent 11,790,244, 2023
- RippleGo-An AI-based Voyage Planner for US Inland Waterways, D Sathiaraj, A Smith, E Rohli, C Hsieh, A Salindong, N Woolsey, A Tec, 2023 IEEE Conference on Artificial Intelligence (CAI), 372-373
- Rohli, Eric, Nicholas Woolsey, and David Sathiaraj. "Near-term forecasting of water reservoir storage capacities using long short-term memory." Environmental Data Science 2 (2023): e30.
- Sathiaraj, David. "Predictive analytical system and method." U.S. Patent No. 11,790,244. 17 Oct. 2023.
- Celano, Joseph, David Sathiaraj, Eric Ho, Andrew Nolan Smith, and Eric Vincent Rohli. "Artificial-intelligence-based waterway information system." U.S. Patent Application 18/128,839, filed July 27, 2023.
- Sathiaraj, D., X. Huang, and J. Chen. "Predicting climate types for the Continental United States using unsupervised clustering techniques." Environmetrics 30.4 (2019): e2524.
- Sathiaraj, David, Thana-on Punkasem, Fahui Wang, and Dan PK Seedah. "Data-driven analysis on the effects of extreme weather elements on traffic volume in Atlanta, GA, USA." Computers, Environment and Urban Systems 72 (2018): 212-220.
- Sathiaraj, David, William M. Cassidy Jr, and Eric Rohli. "Improving predictive accuracy in elections." Big data 5, no. 4 (2017): 325-336.
