Research Team
Latika Sreenath
Urban Automation TeamM.Eng. Computer Science
Cornell University
Latika Sreenath works at the intersection of AI, optimization, and user-facing software, with a focus on turning intelligent systems into products that solve practical problems for users.
She is an M.Eng. computer science student at Cornell, focused on building AI-driven systems that are both technically effective and useful in real-world settings. Most recently, she spent the summer at Dell Technologies, where she worked on the PPDM software engineering team and explored how agentic AI and automation can optimize engineering workflows, including developing an agent to streamline parts of the software deployment process. Her experiences have strengthened her interest in combining AI with thoughtful product design and optimization to make complex systems easier and more efficient to use. Outside of academics and engineering, she enjoys playing badminton, drinking coffee, and spending time with friends.
“I’m looking forward to using AI and geospatial data to build intelligent tools that make complex information more accessible and actionable.”
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