Let's Immerse With Yassine

• 18% faster delivery
• 12% lower energy use
• Interactive analytics

Built a web-based simulation modeling autonomous drone deliveries under dynamic weather and demand, capturing realistic last-mile logistics behavior. Designed adaptive route optimization and scheduling algorithms that reduced average delivery time by 18% and energy consumption by 12% compared with baseline heuristics, and developed interactive analytics dashboards to visualize fleet performance in real time.

• Dynamic uncertainty
• Benchmark study
• Poster presentation

Led undergraduate research on learning-augmented path planning under dynamic uncertainty, presenting the work in poster form through a benchmark-driven study of safety, efficiency, and robustness trade-offs. The project combined interactive visualization, algorithm analysis, and controlled experiments to evaluate how replanning frequency and heuristic design affect navigation performance in changing environments.

• Model predictive control
• Human-aware navigation
• Uncertainty

Built a thesis project focused on learning-augmented model predictive control for human-aware robot navigation, examining how predictive control, uncertainty, and social navigation constraints interact in dynamic environments. The work ties together autonomy, decision-making under uncertainty, and intelligent systems with an emphasis on methods that remain reliable beyond idealized settings.