I recently graduated with a BS in Computer Science from Stanford University and am now continuing as a MS student. Currently, I am doing research under Prof. Christopher Ré as part of the Hazy Research Lab.
My research focuses on developing efficient, interpretable methods for large language models, with three core directions:
Benchmarking & Evaluation — Developing rigorous methods to assess foundation model capabilities, including WONDERBREAD, a benchmark for evaluating multimodal models on business process management tasks.
Model Routing — Creating efficient approaches for inference-time model selection, such as Smoothie, a label-free approach for LLM routing.
System Design — Building scalable multi-model architectures that maximize both efficiency and performance in real-world deployments.
I’m excited to explore research opportunities and collaborations in both academic and industry settings. Feel free to get in touch via email to discuss research or collaboration!
Research Publications
Block Parallelism for Efficient Distributed Long-Context Diffusion Language Model Training Tarun Suresh*, Pranshu Chaturvedi*, Hangoo Kang*, Parth Shroff, Ishan S. Khare, Hermann Kumbong, Azalia Mirhoseini. Under Review, 2026. paper | blog | code 
An Information Theoretic Perspective on Agentic System Design Shizhe He, Avanika Narayan, Ishan S. Khare, Scott W. Linderman, Christopher Ré, Dan Biderman. International Conference on Learning Representations (ICLR), 2026. paper | blog | code 
Smoothie: Label Free Language Model Routing Neel Guha*, Mayee F. Chen*, Trevor Chow, Ishan S. Khare, Christopher Ré. Conference on Neural Information Processing Systems (NeurIPS), 2024. paper | blog | code 
WONDERBREAD: A Benchmark for Evaluating Multimodal Foundation Models on Business Process Management Tasks Michael Wornow, Avanika Narayan, Ben Viggiano, Ishan S. Khare, Tathagat Verma, Tibor Thompson, Miguel Angel Fuentes Hernandez, Sudharsan Sundar, Chloe Trujillo, Krrish Chawla, Rongfei Lu, Justin Shen, Divya Nagaraj, Joshua Martinez, Vardhan Agrawal, Althea Hudson, Nigam H. Shah, Christopher Ré. Conference on Neural Information Processing Systems (NeurIPS), 2024. paper | website | code 
