Eclipse MOSAIC is a Multi-Domain and Multi-Scale Simulation Framework for Automated and Connected Mobility Scenarios.

Berlin Sumo Traffic (BeST) Scenario

Data from 267 bike sharing schemes across Europe - 43 million km & 88000 bikes

Service that matches signal lane geometries to bike routes (IEEE ISC2 2022, ACM SIGSPATIAL 2023)

A comprehensive ride-pooling simulation engine featuring VRP optimization (OR-Tools), dynamic pricing algorithms and ML-based demand prediction.

Next-Generation Intelligent Decision Support System (IDSS) for Indian Railways. A "Co-Pilot" for controllers that uses a Hybrid Intelligence Architecture (Reinforcement Learning + Operations Research) to optimize train scheduling, minimize delays, and ensure safety via Explainable AI. 🚂🤖🇮🇳

This repository contains the 3D models developed for better visualization of a smart mobility system Hyperloop, first publicly mentioned the Hyperloop by Elon Musk in 2012.

An AI-driven Smart Mobility solution for India, providing EV trip planning, on-route charging stops, and CO2 emission savings calculations.

AI-powered EV charging platform with nearest station finder, CO₂ comparison, smart route planning, and AI-based EV infrastructure location analysis using Map and Weather APIs.

DeepTrafficQ is a reinforcement learning-based traffic signal control system that uses Deep Q-Networks (DQN) to minimize vehicle waiting times at a 4-way intersection. By leveraging Q-learning with experience replay and a convolutional neural network (CNN), the agent dynamically adjusts traffic light phases to optimize traffic flow.

Welcome to Lab-42 - Open-Techlab for Makers 🤖🛠️

SynapticGrid is an AI-driven system designed to make cities more efficient, sustainable, and livable by optimizing smart energy grids, waste management, and traffic flow through IoT sensors, real-time data processing, and reinforcement learning algorithms. The modular platform continuously learns and improves, helping urban environments

I'm an urban technologist and planner, trained at the **Massachusetts Institute of Technology (MIT)** with a focus on sustainable mobility and city innovation. My work blends engineering, design, data, and policy to create impactful urban solutions.

Backend API for the Smart Mobility Bike Accident Detection system (Thingy:91).

Smart Moby est une application web développée avec Symfony et MySQL dans le cadre du module PIDEV 3A à Esprit School of Engineering, visant à optimiser le transport urbain grâce à des fonctionnalités intelligentes.

Frank Wolfe Algorithm / Penn State University

ITE@UIUC Data Science Team EOH 2024 Data Visualization

Road Design Superelevation / Penn State University