Hello, I’m Ishan!
I’m an M.S. student in Computer Science at Stanford University, where I also completed my B.S. in Computer Science. I conduct research with Prof. Christopher Ré in the Hazy Research Lab and Prof. Azalia Mirhoseini in the Scaling Intelligence Lab.
My research broadly focuses on understanding the fundamental bottlenecks and principles governing modern machine learning systems, and using those insights to design more efficient and capable models.
Recently, I have worked on:
Next-Concept Modeling (NCM) — a coarse-to-fine language modeling framework for fast, parallel text generation.
Principled ML Systems — studying how bottlenecks in communication and computation shape system design, including an information-theoretic framework for agentic systems and Turbo-dLLM, a block-parallel training system for long-context diffusion language models.
Model Routing & Evaluation — including Smoothie, a label-free method for language model routing, and WONDERBREAD, a benchmark for evaluating multimodal foundation models on enterprise workflows.
I love exploring principled approaches to language models and ML systems, and I’m always excited to discuss new research directions and collaborations. Feel free to reach out by email!
Research Publications
