I'm a fourth-year student at UC Berkeley, studying Computer Science and Applied Mathematics.
I conduct ML research. I work with Sergey Levine in deep reinforcement learning, and with Ben Brown in interpretable machine learning.
I teach probability. Next spring, I'm teaching Stat 140: Probability for Data Science , a course I co-developed two years ago.
My first name is pronounced Dibbo or Dih-bo. On legal documentation, I go by Dibya Jyoti Ghosh.
- I have decided to return to UC Berkeley for my PhD, after taking a year to do a residency at Google Brain Montreal!
- Our work on actionable representations (ARCs) has been accepted to ICLR 2019.
- I was chosen as a finalist for the CRA Outstanding Undergraduate Researcher Award
- Our work on Variational Inverse Control with Events (VICE) has been accepted to NeurIPS 2018.
- At PASC 2018, I gave a talk on interpretable generative models for multi-omics data in the Use of AI to Analyze Complex Biological Systems mini-symposium. Slides coming soon!
- I started a blog called The RL Probabilist. All my previous articles have been transferred there.
- At ICLR 2018, I presented a poster on Divide-and-Conquer Reinforcement Learning.