Suvansh Sanjeev

I am a third-year PhD student on leave from the Robotics Institute at Carnegie Mellon University, where I am advised by Zico Kolter and Zac Manchester. I am interested in safe AI and large language models. I graduated from UC Berkeley, where I worked with Professors Sergey Levine and Claire Tomlin in the Berkeley Artificial Intelligence Research (BAIR) Lab on deep RL and safe learning.

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I am currently working on Brilliantly, making open-source AI projects and providing custom AI solutions for clients. Learn more about the projects Brilliantly is working on here. Recently, we launched Blitz, a demo chatbot that allows users to converse with numerical data, rather than text.

My past research worked towards bringing reinforcement learning to the real world. Most recently, I worked on gray-box methods for control of quadrotors. I have also worked on developing more natural means of task specification for deep RL to avoid the burden of manually engineered reward functions, as well as on developing data-efficient learning techniques that allow for safety guarantees throughout the learning process.

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