curriculum vitae
General Information
| Full Name | Izzat Ullah, Syed |
| Contact | sizzatullah [at] islander[dot]tamucc[dot]edu |
| Languages | English (fluent), Urdu/Hindi (fluent), Arabic (beginner) |
Relevant Hobby Projects
- ○ Multi-robot systems
- ○ Regulatory policies and risk-aware motion planning
- ○ Hybrid "machine learning" and "formal methods" based autonomy solutions
- ○ Simulation and hardware implementation of fully autonomous robots
Education
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2022 - 2025(expected)
Texas A&M University-Corpus Christi – Ph.D. in Computer Science
- Advised by Prof. Jose Baca
- GPA: 3.75 (4.0 scale)
- Research Topic: Risk aware multi-robots motion planning in dynamic unkown environments, focusing collision avoidance, knowledge sharing, and transfer learning
- Thesis committee: Jose Baca (Chair), Carlos Rubio Medrano, Pablo Rangel, Tianxing Chu
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2017 - 2019
Lahore University of Management Sciences (LUMS) – M.S. in Electrical Engineering (Robotics & Control)
- Advised by Prof. Abubakr Muhammad
- GPA: 3.16 (4.0 scale)
- Thesis: Vision-Based Autonomous Mapping & Obstacle Avoidance for a Micro-Aerial Vehicle (MAV) Navigating Canal
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2012 - 2016
Balochistan University of I.T, Engineering and Management Sciences (BUITEMS) – B.S. in Electrical(Communication) Engineering
- Advised by Engr. Syed Owais Athar
- GPA: 3.83/4.0 (Pass with Distinction)
- Senior Project: Object Tracking with Digital Video Based Surveillance System over Wi-Fi Network
Prefessional Experience
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2022 - now
Graduate Research Assistant at Texas A&M University-Corpus Christi
- Corpus Christi, TX, USA
- Developing risk-aware motion planning for a multi-robot system comprising ground and aerial vehicl
- Employing a hybrid approach that combines traditional motion planning methods for safety and machine learning techniques for adaptive behavior in dynamic, unknown, or partially observed environme
- Designing and optimizing collision-free trajectories, accounting for both static and dynamic (cooperative and non-cooperative) obstacl
- Leveraging knowledge sharing and transfer learning to enhance robot collaboration and accelerate learning in new environme
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2019-22
Team Lead at National Center of Robotics & Automation
- Led a team of ten researchers in conducting research on a search and rescue, and socially assistive robots
- Contributed to the development of an autonomous snake-like robot for search and rescue missions. Employed formal methods and Deep Reinforcement Learning for survivor detection and exploration
- Part of the team to develop an assistive social robot, communicating with contextually relevant information in different environments using Natural Language Processing
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Summer 2019
Visiting Researcher at The Robotics Research Lab, TU kaiserslautern, Germany
- Created a realistic canal-like environment in Unreal Engine (UE4) and Microsoft Airsim for testing autonomous drone navigation systems
- Implemented advanced motion and trajectory planning algorithms, ensuring autonomous drone navigation with collision avoidance
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Spring 2019
Research Assistant at National Center of Robotics & Automation
- Conducted comprehensive investigations and testing of various Motion Planning and Obstacle Avoidance algorithms to ensure the safe and reliable navigation of drones in dynamic environments
- Explored and implemented pointcloud data fusion methods, integrating stereo camera and 2D LiDAR data, enhancing environment perception, and boosting drone navigation accuracy and reliability
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Spring 2018
Teaching Assistant at Lahore University of Management Scinces (LUMS)
- Courses: Robot Motion Planning, Probability, and Mobile Robotics
- Assisted instructor in designing the courses, construct tests, prepare materials, and grade assignment
Relevant Hobby Projects
- ○ Implemented UAV obstacle avoidance in Unreal Engine (UE4) using deep reinforcement learning, elevating autonomous navigation and safety
- ○ Designed and simulated an agricultural field robot with autonomous navigation and mapping capabilities, geared towards precision agriculture
- ○ Implemented control and navigation systems for an autonomous vehicle, utilizing the CARLA simulator and the Robot Operating System (ROS) for realistic virtual testing
- ○ Developed an autonomous restaurant serving robot, simulated in Gazebo and ROS, demonstrating advanced automation and service delivery solutions
Computing skills
- ○ Programming & Scripting languages: C++, Python, Matlab, Shell (Bash)
- ○ Robotics Frameworks: Robot Operating System (ROS), Gazebo, CoppeliaSim, Unreal Engine, MoveIt!, and OMPL
- ○ Artificial Intelligence: Machine Learning, Deep Learning, Deep Reinforcement Learning, Bayesian Methods
- ○ Frameworks: PyTorch, NumPy, SciPy, Pandas, MatplotLib
- ○ Optimization Toolboxes: Matlab Optimization toolbox, CVX (Matlab), Gurobi
- ○ Software & Tools: VICON, OptiTrack Motive, LabVIEW, Proteus, MS Office
- ○ Commercial Robots: Crazyflie 2.1 ecosystem, ROBOTIS Turtlebot3, UR3 robot arm
- ○ Version Control: Git/GitHub
- ○ CAD: SolidWorks, Blender, Inventor, and MS Visio
- ○ Operating Systems: Linux (Ubuntu), MacOS, Windows