Kumar Shridhar

I am a third year Ph.D. student at ETH Z├╝rich in Switzerland, supervised by Prof. Mrinmaya Sachan and Nicholas Monath from Google DeepMind.

My research and professional interests are centered around Natural Language Processing and Machine Learning in general, especially towards understanding the reasoning capabilities of LLMs. My PhD research investigates how generative LLMs reason, what factors influence their reasoning performance., and how to optimize their reasoning abilities.


During my PhD, I spent my summers as an intern at FAIR, Meta with Asli Celikyilmaz on agent-based reasoning, at Microsoft Research with Patrick Xia and Jason Eisner on improving the reasoning capabilities of LLMs by revising their output, and at Amazon Alexa AI on setting constraints on the output space of a neural network.

I have experience with fine-tuning LLMs at scale (up to LLAMA 70B), distilling reasoning capabilities from larger models (GPT-4 and chatGPT) to smaller models (LLAMA 7B, T5, GPT-2), and aligning LLMs to generate more accurate and contextually appropriate responses (PPO, RLHF).

Before starting my PhD, I gained valuable experience in researching and deploying conversational AI systems at Insiders Technology GmbH and NeuralSpace . I also worked with Prof. Marcus Liwicki and Prof. Seiichi Uchida during my masters studies.

In my free time, I enjoy playing tennis, reading about conspiracy theories, and collecting sneakers.