Research Team
Aryaman Kumar
Urban Automation TeamM.Eng. Computer Science
Cornell University
Aryaman Kumar focuses on building intelligent software systems that combine AI, machine learning, and scalable software engineering to solve real-world problems.
He is an M.Eng. computer science student at Cornell, where he also serves as a CS 1110 TA and M.Eng. Career Peer Advisor. Before Cornell, he studied computer science, mathematics, and economics at Rutgers University and gained industry experience in AI and machine learning. Most recently at Zensar Technologies, he built an agentic AI system using LLMs, RAG, vector databases, LangChain, and LangGraph, developing multi-agent workflows and backend APIs. His previous work at Tech Mahindra involved fine-tuning and optimizing LLMs, including quantization and QLoRA. His interests center on agentic AI, ML systems, distributed systems, and building reliable AI-powered software at scale.
“I’m especially interested in agentic AI, ML systems, and developing AI applications that can operate reliably in real-world environments, so I’m excited to see how those areas connect with the urban digital twin project.”
Focus areas
Projects
Heatscape NYC
Urban heat intervention planner — 10,081 populated cells scored on 43 indicators and matched to the cooling intervention their context supports.
Project overview
URIS Mapper
A causal diagram platform — build a loop map, let it find the reinforcing and balancing structures, and ask what a change would propagate to.
urismapper.com