Nikhil Prakash
(he/him/his)
PhD Student
Research interests
- Machine learning
- Mechanistic interpretability
- Natural language processing
Education
- MS in Computer Science, Northeastern University
- BS in Telecommunication Engineering, RV College of Engineering — India
Biography
Nikhil Prakash is a PhD student in the Khoury College of Computer Sciences at Northeastern University, advised by David Bau.
Prakash’s research focuses on uncovering the internal mechanisms of deep neural networks to improve human–AI collaboration and mitigate risks of misalignment. Currently, he is studying cognitive abilities — such as reasoning and theory of mind — in large language and vision models. He has published his work in leading venues, including ICLR, ICML, NeurIPS, IUI, and Computational Linguistics.
Outside of work, Prakash enjoys playing chess and table tennis, watching documentaries and anime, and learning about culture and history.
Recent publications
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Language Models use Lookbacks to Track Beliefs
Citation: Nikhil Prakash, Natalie Shapira, Arnab Sen Sharma, Christoph Riedl, Yonatan Belinkov, Tamar Rott Shaham, David Bau, Atticus Geiger. (2025). Language Models use Lookbacks to Track Beliefs CoRR, abs/2505.14685. https://doi.org/10.48550/arXiv.2505.14685 -
NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals
Citation: Jaden Fried Fiotto-Kaufman, Alexander Russell Loftus, Eric Todd, Jannik Brinkmann, Koyena Pal, Dmitrii Troitskii, Michael Ripa, Adam Belfki, Can Rager, Caden Juang, Aaron Mueller, Samuel Marks, Arnab Sen Sharma, Francesca Lucchetti, Nikhil Prakash, Carla E. Brodley, Arjun Guha, Jonathan Bell , Byron C. Wallace, David Bau. (2025). NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals ICLR. https://openreview.net/forum?id=MxbEiFRf39 -
Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking
Citation: Nikhil Prakash, Tamar Rott Shaham, Tal Haklay, Yonatan Belinkov, David Bau. (2024). Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking ICLR. https://openreview.net/forum?id=8sKcAWOf2D -
iClarify – A Tool to Help Requesters Iteratively Improve Task Descriptions in Crowdsourcing
Citation: Nouri Z., Prakash N., Gadiraju U., Wachsmuth H. (2021b). “iClarify - A tool to help requesters iteratively improve task descriptions in crowdsourcing,” in Proceedings of the 9th AAAI Conference on Human Computation and Crowdsourcing (HCOMP). -
Conceptualization and Framework of Hybrid Intelligence Systems
Citation: Nikhil Prakash and Kory W. Mathewson, "Conceptualization and Framework of Hybrid Intelligence Systems", arXiv:2012.06161 (2020).