Motion, Behavior and Deep Learning Research Scientist, PhD
Abduallah Mohamed, BSc EE, MSc CE, PhD ECE abduallah.adel.omar (at) gmail.com
I was part of Mobile Automation and Sensing Systems lab @(UT Austin) lead by my advisor Prof: Christian Claudel and my advisor Prof: Ahmed Tewfik while being co-advised by Prof: Mohamed Elhoseiny @(KAUST/ Stanford).
-- I solve machine perception problems using deep learning and statistical estimation tools--
Deep learning: Experience in developing real-time deep learning models solving a variety of tasks such as sensor data fusion, motion/trajectory and behavior prediction. Models run in real-time, with low memory footprint.
Deep Graph Models: Explore and manipulate deep graph models and training mechanisms to come up with more efficient models with the goal of real-time, memory optimized deep models.
Motion /Trajectory, Action and Behavior Prediction/ Forecasting: My research focuses on investigating real-time deep models for multiple agent’s motion, action and trajectory forecasting that accounts for the uncertainty in the predictions. I attempt to model the interaction between the agents using deep graph nets. Research new metrics that better evaluate the performance of such models.
Localization: Industrial experience in non-visual localization using classical and data driven approaches.
Sensors: Experience with IMUs, magnetometers and ultrasonic developing heading and tracking systems. Combining both physics and data-driven solutions.
Scholar: 600+ citations, publications at top venues CVPR, ECCV and AC/Reviewer for top venues. Co-supervise PhD students working on multidisciplinary research.
Software Engineering: Python, Deep learning libraries, C++, Matlab