I am a Transportation
& AI Engineer. I build intelligent mobility systems
that solve real-world transportation challenges.
Passionate about AI-Powered, Simulation-based, and Data-Driven Approaches to Mobility.
I am a transportation and AI engineer specializing in smart mobility and system optimization. I provide innovative, data-driven solutions to enhance urban and suburban mobility systems, with a strong focus on planning & policy development, network design, operations & service optimization, and technology-driven innovations.
My expertise spans public transit, on-demand services, shared mobility, delivery logistics, and first-mile/last-mile connectivity, all aimed at creating more efficient, accessible, and sustainable transportation networks. I leverage simulation-based approaches as well as AI methods such as machine learning and reinforcement learning to model demand, optimize services, and support decision-making in complex mobility systems.
I’m always excited about collaborations, research, and AI-driven mobility projects that reimagine how we move through cities. If you’re looking for an expert to tackle complex challenges in smart mobility, let’s connect and build the future of transportation together.
My key areas of expertise.
I specialize in developing intelligent mobility systems that enhance efficiency and reduce costs. My expertise spans multiple domains, including modeling and simulation, AI approaches, optimization algorithms, and applied research
Modelling & Simulation-Based Optimization
I use modeling and simulation-based optimization to evaluate and improve the performance of transit systems, including on-demand and shared mobility (e.g., ride-hailing, ride-sharing, delivery), public transit, and multimodal services. I work with tools such as SUMO, PTV Visum, and Vissim to support data-driven system design and operational optimization.
AI Engineering & Data-Driven Approaches
I apply AI engineering and data-driven approaches to solve complex mobility challenges such as dynamic ride-matching, demand prediction, and multimodal routing. I leverage techniques like machine learning, reinforcement learning, and graph neural networks to develop intelligent, adaptive, and efficient transit solutions.
Optimization Algorithms
I design and apply optimization algorithms to improve the efficiency, reliability, and responsiveness of mobility systems. My work includes solving complex problems such as vehicle relocation, fleet sizing, dynamic dispatching, and service coverage, using methods like metaheuristics, linear programming, and multi-objective optimization.
Research & Development
I lead and contribute to applied research in sustainable and intelligent transportation systems, focusing on the design, simulation, and evaluation of innovative mobility solutions. My work includes mentoring students, publishing in peer-reviewed journals, and collaborating with academic, public, and private sector partners to bridge the gap between research and real-world impact.
I leverage advanced tools to develop scalable, efficient, and research-driven mobility solutions.
I apply simulation platforms, AI, and optimization tools to solve complex mobility challenges and deliver practical, real-world solutions.
Building intelligent and scalable mobility systems requires blending domain expertise with data and technology, and I combine these methods to create efficient, future-ready transportation solutions.
