Han (Paris) Zhang 章晗

I earned my Master's degree in Computer Science from Stanford University, where I was honored as a Siebel Scholar, Class of 2025.

I received my B.A. in Computer Science and Economics from UC Berkeley, where I was awarded the prestigious EECS Department Citation. During my time there, I had the privilege of conducting research in vision and language under the guidance of Prof. Trevor Darrell, Prof. Joseph E. Gonzalez, and Ph.D. candidate Lisa Dunlap.

Email  /  Google Scholar  /  LinkedIn

My research interests broadly span computer vision, with a particular focus on vision-and-language multimodalities, generative models, and the robustness and interpretability of AI systems.

We introduce CHURRO, a large-scale, multimodal OCR benchmark and dataset of historical documents, revealing that even the best large multimodal models (LMMs) struggle with historical text and demonstrating that targeted fine-tuning significantly improves their performance.

We introduce ALIA, a method which utilizes large vision and language models to automatically generate natural language descriptions of a dataset's domains and augment the training data via language-guided image editing.

We propose LADS, a method that learns a transformation of the image embeddings from the training domain to each unseen test domain guided by language, while preserving task relevant information.

We find that link recommendations have surprising delayed and indirect effects on the structural properties of networks through adapting a simulation-based approach and an explicit dynamic formation model.

Developed and modularized a calculator for the loan product, GS Select, enabling automated daily computation of key financial metrics, including risk-weighted assets.

Optimized TikTok's Android package size and cold startup time by developing custom optimization passes leveraging an open-source Android bytecode optimizer, ReDex.

Website template from Jon Barron. Thanks for stopping by :)
Last updated: May 15, 2026