I am a final year Computer Science Ph.D. student at the National University of Singapore, where I am fortunate to be advised by Kuldeep S. Meel.

My main interests are in distribution testing and formal methods. Specifically, I want to explore and apply the theory of distribution testing to build faster verification tools for real-world distributions, such as samplers and generative models. More generally, I am interested in the use of formal methods (like combinatorial solving) in machine learning.

Here is my CV. You can reach me at yashppote@gmail.com.


® indicates random author ordering.


  1. Distance Estimation in High Dimensions with Subcube Conditioning
    Gunjan Kumar ® Kuldeep S. Meel ® Yash Pote

  2. Testing Self-Reducible Samplers (AAAI-24) bib, code
    Rishiraj Bhattacharyya, Sourav Chakraborty, Yash Pote, Uddalok Sarkar, Sayantan Sen

  3. On Scalable Testing of Samplers (NeurIPS-22) bib, code
    Yash Pote ® Kuldeep S. Meel

  4. Testing Probabilistic Circuits (NeurIPS-21) bib, code
    Yash Pote ® Kuldeep S. Meel

  5. On Testing of Samplers (NeurIPS-20) bib, slides, video, code
    Kuldeep S. Meel ® Yash Pote ® Sourav Chakraborty

Combinatorial Solving

  1. Partition Function Estimation: A Quantitative Study (IJCAI-21) bib, poster
    Durgesh Agrawal, Yash Pote, Kuldeep S. Meel

  2. Phase Transition Behaviour of Cardinality and XOR Constraints (IJCAI-19) bib, code, slides, video
    Yash Pote, Saurabh Joshi, Kuldeep S. Meel

DNA Data Storage

  1. Efficiently Supporting Hierarchy and Data Updates in DNA Storage (MICRO-23)
    Puru Sharma, Cheng-Kai Lim, Dehui Lin, Yash Pote, Djordje Jevdjic

  2. Managing Reliability Skew in DNA Storage (ISCA-22)
    Dehui Lin, Yasamin Tabatabaee, Yash Pote, Djordje Jevdjic

Research Group

I work in the Meel Research Group. We are situated in NUS and the University of Toronto.