curriculum vitae

Texas A&M University-Corpus Christi – Ph.D. in Computer Science (Robotics & Artificial Intelligence)

• Advised by Prof. Jose Baca
• GPA: 3.75 (4.0 scale)
• Research Topic: Uncertainty-Aware Probabilistic Forecasting of Non-Cooperative Dynamic Obstacles for Safe Autonomous Aerial Navigation
• Thesis committee: Jose Baca (Chair), Carlos Rubio Medrano, Pablo Rangel, Tianxing Chu

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

Balochistan University of I.T, Engineering and Management Sciences (BUITEMS) – B.S. in Electrical(Communication) Engineering

• GPA: 3.83/4.0 (Ranked 2nd out of 140 students, Silver Medalist)

Graduate Research Assistant at Texas A&M University-Corpus Christi

• Corpus Christi, TX, USA
• Developed POF+MADER, a novel UAV trajectory planner integrating real-time probabilistic obstacle filtering with optimization-based planning, achieving 39% collision reduction in simulation and 25% in hardware trials with Crazyflie drones.
• Developed and released SynTraG, an open-source parametric 3D synthetic trajectory generator combining kinematic primitives and stochastic modeling to emulate non-cooperative aerial behaviors, enabling robust training and standardized benchmarking of UAV trajectory forecasting models.
• Built transformer-based multi-modal forecasting system that predict long-horizon trajectories of non-cooperative, non-linear dynamic obstacles for safer UAV navigation in complex environments.
• Authored 4 research papers (1 journal paper under final review and 1 other submitted, 1 conference paper published, and 1 other accepted to be published) on trajectory planning, obstacle avoidance, and multi-modal learning for robotics.

Team Lead at National Center of Robotics & Automation

• Led team of 10 researchers developing search and rescue robots using formal methods and deep reinforcement learning, coordinating research efforts and managing project timelines.
• Contributed to assistive social robot project utilizing natural language processing for context- aware human-robot communication in varied environments.
• Published 2 conference papers on deep reinforcement learning-based snake robot control and autonomous navigation.

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 in challenging outdoor scenarios.
• Implemented advanced motion and trajectory planning algorithms, ensuring autonomous drone navigation with collision avoidance
• Published 1 conference paper on autonomous navigation of UAVs in a cluttered canal-like environment.

Research Assistant at National Center of Robotics & Automation

• Evaluated motion planning and obstacle avoidance algorithms (RRT*, A*, dynamic window approach) for safe drone navigation in dynamic environments.
• Developed point cloud fusion pipeline integrating stereo camera and 2D LiDAR data, improving environment perception and navigation accuracy.

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

• Python (PyTorch, NumPy, SciPy, Pandas, scikit-learn), C++, MATLAB, Shell Scripting, CMake, Bash

• ROS/ROS2, Gazebo, CARLA, Microsoft AirSim, Unreal Engine, MoveIt, PyBullet

• Deep Learning, Reinforcement Learning (DQN, PPO, SAC), Transformer Architectures, Graph Neural Networks (GNNs), Probabilistic Modeling, Multimodal Learning, Time-Series Forecasting, Computer Vision

• A*, D*, RRT*, PRM, Model Predictive Control (MPC), Trajectory Optimization, Multi-Agent Planning, Feedback and Digital Control Systems, Optimization (CVX, Gurobi, CVXPY)

• SLAM, Sensor Fusion, IMUs, LiDAR, RGB-D and Stereo Cameras, Vision-based Localization

• Crazyflie Drones, TurtleBot3, Leo Rover, UR5 Manipulator, VICON and OptiTrack Motion Capture Systems

• Docker, Git, Linux (Ubuntu), SolidWorks, LabVIEW, OriginLab, LaTeX, CI/CD Pipelines

Ph.D. Research Fully Supported by NSF Grant

IEEE ICRA 2025 Attendee

• Atlanta, GA

1st Place Engineering Research

• 11th Annual MSGSO Research Symposium

3rd Place Engineering & Computer Science

• 18th Annual TAMUS Pathways Research Symposium

IEEE RAS Summer School on Multi-Robot Systems (Participant)

• Czech Technical University

British Council STEM Training Grant (£20,000)

• Secured funding to train higher education faculty in STEM teaching and research practices

Fully Funded Academic Excellence Scholarship for Entire Master's Degree

• Lahore University of Management Sciences (LUMS)

Silver Medalist in B.S. Telecommunication Engineering

• BUITEMS

DRL-Based Obstacle Avoidance for UAVs

• Built end-to-end deep reinforcement learning pipeline in Unreal Engine and Microsoft AirSim achieving 95% collision-free navigation in complex indoor environments. Implemented PPO and SAC algorithms with curriculum learning.

Autonomous Restaurant Robot

• Developed ROS/Gazebo-based serving robot with optimized path planning (A*, dynamic win- dow approach), achieving good navigation success rate in simulated restaurant environment with dynamic obstacles.

Multi-Agent Urban Navigation

• Created CARLA/ROS simulation environment for testing autonomous navigation algorithms with realistic traffic patterns, pedestrian behaviors, and urban infrastructure constraints.

Agricultural Robot Navigation

• Designed autonomous robot in ROS/Gazebo with sensor fusion (camera, IMU, GPS) for field mapping and crop row following with centimeter-level accuracy.

Reviewer

• IEEE ICRA (2024, 2025), IEEE/RSJ IROS (2025), IEEE RA-L, IEEE Access, Journal of Climbing and Walking Robots, MDPI (Drones)

Mentorship

• Mentor for undergraduate research students (2022–present); Robotics outreach programs for high school students (2023–present)