About
My research focuses on autonomous driving and autonomous racing, with emphasis on real-time control, robust perception, and reinforcement learning for safety-critical decision-making. I develop ROS2-based autonomy stacks that combine global path tracking, local obstacle avoidance, LiDAR perception, and safety mechanisms for real-world robotic systems.
My current interests include safe autonomous systems, sim-to-real transfer, learning-enabled control, embodied AI, and foundation-model approaches for high-level robotic reasoning.
Professional Experience
West Virginia University — Ph.D. Student & Graduate Research Assistant
Conducting research in autonomous driving and racing using ROS2, LiDAR-based perception, reinforcement learning, and sim-to-real deployment on Roboracer platforms.
High Institute of Engineering and Technology — Teaching Assistant
Supported teaching in mechatronics and engineering courses, supervised student projects, and contributed to academic instruction in programming, mathematics, and systems topics.
Jelecom for Technical Training Company — Software Engineer
Worked in software engineering and technical training, supporting applied computing workflows.
Selected Projects
Representative work in learning-enabled control, racing autonomy, and sim-to-real robotic systems.
RL-Based Tuning of Pure Pursuit for Autonomous Racing
Developed a reinforcement learning framework to jointly tune lookahead distance and steering gain in Pure Pursuit, with sim-to-real validation on Roboracer platforms.
Safety-Gated Arbitration for Global–Local Control
Designed a learning-enabled arbitration framework that combines global raceline tracking with local obstacle avoidance under safety constraints.
Sim-to-Real Roboracer Deployment with LiDAR Perception
Built ROS2-based autonomous racing systems integrating LiDAR perception, Pure Pursuit, Gap-Follow, safety bubbles, and speed limiting for physical Roboracer vehicles.
Embodied AI and Foundation-Model Exploration
Exploring how LLMs, VLMs, and related foundation-model approaches can support high-level reasoning and decision-making in safety-critical autonomous systems.
Publications
Published journal articles, accepted workshop papers, and current manuscripts.
Published Journal Articles
Journal article on reinforcement learning for adaptive Pure Pursuit in autonomous racing, with emphasis on controller tuning, racing performance, and sim-to-real deployment.
Research on video super-resolution using wavelet multi-scale convolutional neural networks for improved reconstruction quality.
Accepted Workshop Papers
Workshop paper on learning a dynamic lookahead policy for Pure Pursuit in autonomous racing, with relevance to adaptive control and sim-to-real deployment.
Workshop paper on robust and safety-aware arbitration between global path tracking and local obstacle avoidance under LiDAR sensing errors.
Education
West Virginia University
Lane Department of Computer Science and Electrical Engineering.
Mansoura University
Thesis: Multi-Frame Super-Resolution using Wavelet Multi-Scale Convolutional Neural Networks.
Mansoura University
Graduation Project: Wireless Brain-Controlled Humanoid System.
Technical Skills
Core tools and topics used across my research, development, and deployment workflows.
Teaching & Outreach
Teaching Experience
- Modelling and Simulation
- Algebra and Differential Calculus
- Analytical Geometry and Integral Calculus
- Ordinary Differential Equations
- Partial Differential Equations
- Computer Programming
Outreach
Arabic-language AI content creator on YouTube since 2020, producing educational content in artificial intelligence, machine learning, mathematics, and programming.
Contact
Mohamed Elgouhary
Email: mohamed.elgohary.ai@gmail.com
Academic Email: mae00018@mix.wvu.edu
Location: Morgantown, WV, USA
Affiliation: Lane Department of Computer Science and Electrical Engineering, West Virginia University
Profiles
Google Scholar: scholar profile
LinkedIn: linkedin.com/in/elgouhary-ai
GitHub: github.com/Mohamed-Elgouhary
YouTube: youtube.com/@Elgouhary-AI
CV: Download PDF