Kavosh Asadi

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I am an AI scientist whose career goal is to understand computational principles underlying intelligence. More specifically, I study agents that interact with a sequential environment to improve their behavior through trial and error. This agent-environment interaction is referred to as the reinforcement learning problem.

I have a PhD and an extensive background in the theoretical and empirical foundations of reinforcement learning. I have published more than a dozen papers at top-tier AI conferences such as Neurips, ICML, ICLR, AAAI, and ACL. On the academic side, I am really interested in understanding the optimization problem that arises in the context of learning the value function. On the aplication side, I am quite interested in the developing assistive AI agents that interact with humans and learn from feedback to provide better service. My aspiration is to make AI agents that co-exist with and help us live our best lives.

The best way to reach me for career-related stuff is by shooting me an email at my first name @alumni.brown.edu. I am genuinely interested in forming meaningful connections with fellow AI scientists, engineers, students, etc, so feel free to reach out even if we never met in person.

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