Photo of Eugene Vinitsky
Principal Investigator
Eugene Vinitsky is a Professor of Civil and Urban Engineering at NYU and a member of the C2SMARTER consortium. His primary research interest is figuring out how to make developing multi-agent controllers, planners, and intelligence as easy as possible by developing new learning algorithms, software, and tools. He looks for applications of these techniques in civil engineering problems and autonomy. He received his PhD in controls engineering from UC Berkeley.
Photo of Daphne Cornelisse
PhD Student
Daphne's main interest lies in building agents that are both competent and human-compatible, particularly in the fields of autonomous vehicles and transportation. To this end, she intends to incorporate principles from human learning and generalization into multi-agent RL. Her goal is to discover the essential ingredients that will allow agents to demonstrate sophisticated behavior and anticipate the actions of others in their environment.
Photo of Aditya Makkar
PhD Student
Aditya’s research interests are in building autonomous agents that learn by interacting with the environment through the lens of sequential decision making. A focus of his research is to understand the interaction of several agents and study emergent intelligent behaviours. He is particularly interested in the settings of non-stationary environments and incomplete observations—like in multi-agent RL. He also has an interest in and finds inspiration from stochastic control, probability theory and statistics.
Photo of Sam Kazemkhani
Masters Student
Sam Kazemkhani
Sam is Sam.
Photo of Aarav Pandya
Masters Student
Aarav Pandya
Aarav is pursuing a Master's in Computer Engineering at NYU. He's interested in building autonomous agents capable of exhibiting complex behaviours to simplify human lives. His areas of interest include long-horizon planning, multi-agent problems, safe RL, and more within the realm of self-driving cars. Currently, he's concentrating on developing simulations that optimize scalability, facilitating rapid design and training of RL agents.
Photo of Alex Tang
Alex Tang
Alex is a Computer Science undergrad who is interested in reinforcement learning and unit testing for RL. He hopes to gain experience with the research process and delve deeper into RL techniques.