Nitish Nagesh

I am interested in trustworthy and explainable AI for health applications.

As a Ph.D. candidate in Computer Science at UC Irvine, I specialize in fairness-aware causal inference and large language models for health applications. My research has been published in top-tier venues like IEEE Medicine & Biology and Elsevier Smart Health, American Heart Association, and the American Diabetes Association.

I am the recipient of UC Irvine’s Beall Family Entrepreneur Award, the TU Munich Young Academy Scholarship, and the Best Outgoing Student award in Electrical Engineering at R.V. College.

I have expertise in Python, R, SQL, PyTorch, TensorFlow, and LangChain.

Outside of work, I enjoy science communication and mentoring people from diverse backgrounds.

selected publications

arXiv

FairCauseSyn: Towards Causally Fair LLM-Augmented Synthetic Data Generation

Nitish Nagesh, Ziyu Wang, and Amir M Rahmani

arXiv preprint arXiv:2506.19082, 2025

Bib

@article{nagesh2025faircausesyn,
  title = {FairCauseSyn: Towards Causally Fair LLM-Augmented Synthetic Data Generation},
  author = {Nagesh, Nitish and Wang, Ziyu and Rahmani, Amir M},
  journal = {arXiv preprint arXiv:2506.19082},
  year = {2025},
}

Smart Health

ChatDiet: Empowering personalized nutrition-oriented food recommender chatbots through an LLM-augmented framework

Zhongqi Yang, Elahe Khatibi, Nitish Nagesh, and 4 more authors

Smart Health, 2024

Bib

@article{yang2024chatdiet,
  title = {ChatDiet: Empowering personalized nutrition-oriented food recommender chatbots through an LLM-augmented framework},
  author = {Yang, Zhongqi and Khatibi, Elahe and Nagesh, Nitish and Abbasian, Mahyar and Azimi, Iman and Jain, Ramesh and Rahmani, Amir M},
  journal = {Smart Health},
  volume = {32},
  pages = {100465},
  year = {2024},
  publisher = {Elsevier},
}

Towards deep personal lifestyle models using multimodal N-of-1 data

Nitish Nagesh, Iman Azimi, Tom Andriola, and 2 more authors

In International conference on multimedia modeling, 2023