Khalil Zbiss
PhD Candidate in Robotics & Motion Planning
About Me
I'm a Ph.D. candidate passionate about robotics, motion planning, and sensor fusion. My work focuses on designing and optimizing motion control systems for industrial robots, helping them move smarter, safer, and more efficiently. Over the years, I've collaborated with industry leaders like Ford Motor Company and published research in top journals, tackling challenges like collision-free trajectory generation, real-time motion prediction, and even motion sonification (yes, robots that "sing" their movements!).
When I'm not geeking out over robotics, I'm coding in Python, MATLAB, C/C++, or tinkering with ROS to bring new ideas to life. I've published 4 journal papers and 2 conference papers, and I'm always excited to push the boundaries of what robots can do. Let's build the future of automation together!
Skills & Expertise
Technical Skills
- Matlab - Advanced Motion Planning & Control
- Python - Robotics & Computer Vision
- C/C++ - Real-time Systems
- ROS2 & Linux - Robot Operating System
Robotics & AI
- Path Planning & Optimization
- Multi-Robot Systems
- Computer Vision & Sensor Fusion
- Machine Learning Applications
Development Tools
- CoppeliaSim-VREP Simulation
- Gazebo Simulation
- IMU Sensor Integration
- Algorithm Development
Research Skills
- Scientific Paper Writing
- Data Analysis & Visualization
- Experimental Design
- Literature Review
Languages
- English (Professional)
- French (fluent)
- Arabic (Native)
- Technical Writing
Soft Skills
- Teaching & Mentoring
- Project Leadership
- Cross-functional Collaboration
- Problem-solving
Experience
Research Assistant
- Published 4 journal papers, 1 conference paper, and 1 abstract conference paper (30+ citations)
- Designed a collision-free path-planning algorithms for multi-robot manipulators funded by Ford Motor Company for car-painting
- Developed optimal base positioning solutions for Industrial painting robots using multi-objective minimax solvers
- Modeled VRU motion prediction and developed a stability metricusing IMU sensor
- Developed a vehicle-to-bike collision detection algorithm using adaptive collision cones and Kalman filter-based sensor fusion
- Developed a Python framework for controlling and gathering data from OMRON LD mobile robots, enhancing real-time monitoring and control
Graduate Student Instructor
- Taught labs and assisted in Control Systems, Embedded Systems, Robot Manipulators, and Mobile Robots
- Created a Matlab-based lab manual for the Control Systems curriculum
- Improved student satisfaction ratings by 15%
Education
Ph.D. in Electrical, Electronics, and Computer Engineering
Focus: Robotics, Motion Planning, and Sensor Fusion
- Published 4 journal papers and 2 conference papers (30+ citations)
M.S.E in Computer Engineering
- Graduated with High Distinction
Bachelor in Computer System Engineering
Featured Work
Automatic Optimal Multi-Robot Task Allocation for car painting
29+ CitationsDesigned a computationally efficient algorithm for generating collision-free trajectories in multi-robot collaborative systems. Developed optimal base positioning algorithm for Industrial painting robots using multi-objective minimax solvers. This work was done in Collaboration with Ford Motor Company.
Motion Sonification System
Investigated sonification techniques for monitoring and controlling multi-robot systems operating in dynamic environments. Conducted experiments with OMRON LD series mobile robots.
VRU Motion Modeling
Developed a bicycle stability metric and vehicle-to-bike collision detection algorithm using adaptive collision cones and sensor fusion with Kalman Filter.
Automatic Traffic Sign Detection and Classification
Led a team of 4 to develop a computer vision CNN-based traffic sign detection system on a single-board computer (Raspberry Pi) with a camera module, achieving 92% accuracy.
Publications
Automatic collision-free trajectory generation for collaborative robotic car-painting
Novel approach for generating collision-free trajectories in multi-robot collaborative systems for automotive painting applications.
K. Zbiss, A. Kacem, M. Santillo, A. Mohammadi
A Numerical Integrator for Forward Dynamics Simulations of Folding Process for Protein Molecules Modeled as Hyper-Redundant Robots
Novel numerical integration approach for simulating protein folding dynamics using robotic modeling.
A. Kacem, K. Zbiss, A. Mohammadi
A Numerical Integrator for Kinetostatic Folding of Protein Molecules Modeled as Robots with Hyper Degrees of Freedom
Advanced numerical method for modeling protein folding using hyper-redundant robotic systems.
A. Kacem, K. Zbiss, A. Mohammadi
Automatic Optimal Robotic Base Placement for Collaborative Industrial Robotic Car Painting
Optimization framework for robotic base placement in industrial painting applications.
K. Zbiss, A. Kacem, M. Santillo, A. Mohammadi
Transforming Motion Into Sound: A Novel Sonification Approach for Teams of Mobile Robots
Novel approach for monitoring multi-robot systems through sound transformation.
A. Kacem, K. Zbiss, A. Mohammadi
Wave space sonification of the folding pathways of protein molecules modeled as hyper-redundant robotic mechanisms
Innovative sonification technique for visualizing protein folding pathways using robotic modeling.
A. Kacem, K. Zbiss, P. Watta, A. Mohammadi