Biography

I am Rishabh Jain, a Computer Science undergraduate at Iowa State University passionate about artificial intelligence, computer vision, and sustainable engineering applications. As an Undergraduate Research Assistant at the Institute for Transportation, I developed SignalVerse, a GPT-4-powered assistant that enhances transportation research efficiency using Generative AI and Retrieval-Augmented Generation. I also built computer vision models with YOLO and OpenCV to analyze real-time vehicle behavior, improving traffic analysis accuracy. Additionally, I designed automation pipelines integrating OCR and NLP models with AI chatbots and analytics systems to optimize research workflows. My work has led to two publications, including a first-authored paper on traffic signal management. I aim to advance sustainable, data-driven solutions through interdisciplinary AI research bridging computing and civil infrastructure.

Academic Status

Undergraduate Student - 3rd

Research Area/Department

Computer Science; Data Science; Engineering; Machine Learning/AI

Major/Specialty

Computer Science

Degrees Earned or in Progress

Bachelor of Science in Computer Science, Expected May 2027, Iowa State University

Academic Preparation

Data Structures and Algorithms, Machine Learning, Computer Vision, Artificial Intelligence, Software Engineering, Database Management Systems, and Probability & Statistics.

Research/Publications

I have conducted research at Iowa State University through the Institute for Transportation and FAST-TrAC. My work focuses on applying AI, computer vision, and data-driven methods to transportation and infrastructure systems. Selected Publications: 1. Author, CTRG 2025 (Accepted) – SignalVerse: Harnessing LLMs to Revolutionize Traffic Signal Management 2. Co-Author, Remote Sensing, MDPI 2025 – Uncrewed Aerial Vehicle-Based Automatic System for Seat Belt Compliance Detection at Stop-Controlled Intersections These projects involved implementing LLMs, computer vision algorithms, and automation pipelines to improve traffic analysis, infrastructure monitoring, and safety compliance.

Research/Academic Interests

My research interests lie at the intersection of artificial intelligence, computer vision, and sustainability. I focus on using deep learning and data-driven modeling to make infrastructure systems smarter and safer. I am particularly interested in how AI can enhance transportation efficiency, climate resilience, and real-time decision-making.

Computational and Data Science Areas

Applied Computer Science; Artificial Intelligence and Intelligent Systems; Civil Engineering; Computer Science; Informatics, Analytics and Information Science; Visualization and Human-Computer Systems

Motivation

I’m applying to the Sustainable Research Pathways program because I want to contribute to sustainable, AI-driven solutions that improve how we design and operate real-world systems. As an undergraduate researcher at Iowa State University’s Institute for Transportation, I have worked on projects combining computer vision, data science, and infrastructure engineering to analyze vehicle behavior and optimize traffic safety. Through this experience, I saw how technology can directly impact public well-being and sustainability. I hope to collaborate with scientists through SRP to deepen my understanding of large-scale computational modeling and responsible AI applications. My goal is to bridge computing and civil systems to support smarter cities, efficient energy use, and safer transportation. Participating in SRP would give me exposure to interdisciplinary research and mentorship from experts across national labs. I aspire to become a researcher who merges technical innovation with sustainability goals to drive smarter, safer, and more equitable infrastructure systems.

Lightning Talk Title

Exploring AI and Generative Models for Intelligent Systems

Keywords (Maximum 20 words)

Artificial Intelligence; Generative Models; Machine Learning; Java; Computer Vision; Data Analytics; OCR; RAG; Python; SQL; Tableau; Cloud Computing; Autonomous Systems