Ami Baid

I recently graduated from UT Austin with degrees in computer science and math as a Turing Scholar. During undergrad, I was a researcher in the UT Austin Computer Vision Lab, advised by Prof. Kristen Grauman. I'll be starting my Master's in CS at Stanford this fall🌲

My research focuses on audio-visual multimodal learning. I'm excited about developing intelligent systems that can understand and reason over information from diverse modalities.

Email  /  GitHub

Research

Personal Visual Context Learning in Large Multimodal Models

Zihui Xue, Ami Baid, Sangho Kim, Mi Luo, Kristen Grauman

arXiv 2026   [paper] [project page]

Don't Let the Video Speak: Audio-Contrastive Preference Optimization for Audio-Visual Language Models

Ami Baid, Zihui Xue, Kristen Grauman

ECCV 2026   [paper] [project page]

Action2Sound: Ambient-Aware Generation of Action Sounds from Egocentric Videos

Changan Chen, Puyuan Peng, Ami Baid, Zihui Xue, Wei-Ning Hsu, David Harwath, Kristen Grauman

ECCV 2024, Oral   [paper] [project page]

Self-Supervised Visual-Acoustic Matching

Arjun Somayazulu, Changan Chen, Kristen Grauman

NeurIPS 2023   [paper] [project page]

Internships

• Engineering intern @ Stripe (summer 2025): extended Stripe's LLM-based compliance detection system to support image understanding on merchant websites.
• Software engineering intern @ Salesforce (summer 2024): automated a key workflow in Salesforce's internal Temporal platform and contributed to the open-source Terraform Temporal provider.

Other Projects

• Gaze-centered Egocentric Video Representations: built a gaze-aware preprocessing pipeline that reallocates resolution around gaze, improving efficiency in egocentric video QA. [GitHub]