Nived Rajaraman

PhD Student
UC Berkeley

About Me

I am a rising 5th year PhD student at UC Berkeley, jointly advised by Jiantao Jiao and Kannan Ramchandran, affiliated with the BLISS and BAIR labs. I was previously an intern with Nevena Lazic and Dong Yin at Deepmind and with Ravishankar Krishnaswamy at MSR India.

I work on a variety of topics in the theory of machine learning with a general focus on the statistical and computational aspects of adaptive decision making problems and reinforcement learning. More recently, I have been interested in the application of these techniques in pushing our understanding of large language models. My research has largely focused on using mathematical frameworks to explain curious practical phenomena and ultimately provide intuitions missing in existing approaches.

I am currently an organizer of the BLISS seminar and CLIMB seminar at Berkeley. Shoot me an email if you are interested in giving a talk at either venue!

In a previous life, I was a dual degree student at the Department of Electrical Engineering, IIT Madras. I am fortunate to have had Andrew Thangaraj as my thesis advisor and to have worked closely with Rahul Vaze.


April 2023: I taught a guest lecture for Statistical Machine Learning (ECE 6254) at Georgia Tech.

April 2023: I presented our work on pruning for matrix sensing at Georgia Tech.

January 2023: I presented our recent work on nonlinear bandits at Google Research India and MSR India.

November 2022: I will be at Neurips 2022. Hit me up if you will be around!

October 2022: I gave a talk on nonlinear bandits at the WNCG group at UT Austin.

October 2022: I will be participating in AIDS LifeCycle 2023. You can support me by clicking here. Every little bit counts!


  1. Nived Rajaraman, Yanjun Han, Jiantao Jiao, Kannan Ramchandran

  2. Nived Rajaraman, Devvrit, Aryan Mokhtari, and Kannan Ramchandran

  3. Dong Yin, Sridhar Thiagarajan, Nevena Lazic, Nived Rajaraman, Botao Hao, and Csaba Szepesvari

  4. Gokul Swamy*, Nived Rajaraman*, Matt Peng, Sanjiban Choudhury, J. Bagnell, Steven Z. Wu, Jiantao Jiao, and Kannan Ramchandran (* = equal contribution)
    NeurIPS 2022

  5. Nived Rajaraman, Devvrit, and Pranjal Awasthi
    NeurIPS 2022

  6. Amirali Aghazadeh, Nived Rajaraman, Tony Tu, and Kannan Ramchandran

  7. Nived Rajaraman, Yanjun Han, Lin Yang, Jingbo Liu, Jiantao Jiao, and Kannan Ramchandran
    NeurIPS 2021

  8. Nived Rajaraman, Yanjun Han, Lin F. Yang, Kannan Ramchandran, and Jiantao Jiao

  9. Nived Rajaraman, Lin F. Yang, Jiantao Jiao, Kannan Ramchandran
    NeurIPS 2020

  10. Swanand Kadhe, Nived Rajaraman, O. Ozan Koyluoglu, and Kannan Ramchandran
    ICML Workshop on FL for User Privacy and Data Confidentiality (2020); CCS Workshop on Privacy-Preserving Machine Learning in Practice (2020); ISIT (2021)

  11. Ravishankar Krishnaswamy, Devvrit, and Nived Rajaraman (equal contribution)

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