Tian Qiu

Hello! I'm 邱天(qiū tiān), a 2nd year Ph.D. student at UCSB advised by Prof. Haewon Jeong, where I work on responsible AI and AI for science.

Previously:

🎓 B.Eng in EE @ BIT & ANU. Advised by Prof. Xiangyun Zhou.

🎓 M.S. in ECE @ UCSD. Advised by Prof. Pamela Cosman and Prof. Dinesh Bharadia.

My current research is on quantifying and mitigating bias in AI-based data encoding systems. I can be reached at tian_qiuATucsbDOTedu.

LinkedIn  /  Google Scholar  /  Github  /  Blog

News

[Feb 2026] I instructed "Introduction to Machine Learning with Python" workshop at UCSB Library.

[Sep 2025] I taught a introduction to AI class for high schoolers, "REAL AI Bootcamp".

[Jun 2025] I'm attending ISIT '25 and presenting a poster at the workshop "Learn to Compress & Compress to Learn"!

[Jun 2025] I have a paper presenting at FAccT '25. Check out my co-author Arjun Nichani's talk on this paper!

Conference and Journal Papers

Gone With the Bits: Revealing Racial Bias in Low-Rate Neural Compression for Facial Images
Tian Qiu*,  Arjun Nichani*,  Rasta Tadayon,   Haewon Jeong 
2025 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’25)

Tile-Based Wireless Streaming of 360-Degree Video With Rate Adaptation Using Viewport Estimation
Yeohee Im,  Tian Qiu,  Laurence Milstein,   Pamela Cosman 
IEEE Signal Processing Letters 29, 2022.

Delivering 360-degree Video With Viewport-Adaptive Truncation
Tian Qiu,  Ish Kumar Jain,  Raini Wu,  Dinesh Bharadia,  Pamela Cosman 
International Symposium on Wireless Personal Multimedia Communications (WPMC), 2022.

Workshop Papers

CosmoFlow: Scale-Aware Representation Learning for Cosmology with Flow Matching
Sidharth Kannan,  Tian Qiu,  Carolina Cuesta-Lazaro,  Haewon Jeong 
Machine Learning for Astrophysics Workshop @ ICML 25

Gone With the Bits: Revealing Racial Bias in Low-Rate Neural Compression for Facial Images
Tian Qiu*,  Arjun Nichani*,  Rasta Tadayon,   Haewon Jeong 
Learn to Compress & Compress to Learn @ ISIT 25

Gone With the Bits: Benchmarking Bias in Facial Phenotype Degradation Under Low-Rate Neural Compression
Tian Qiu*,  Arjun Nichani*,  Rasta Tadayon,   Haewon Jeong 
ICML 2024 Next Generation AI Safety Workshop, 2024.

*Equal contribution

Academic Services

Conference reviewer: ICLR 25, FAccT {25, 26}

Workshop reviewer: Learn to Compress & Compress to Learn @ ISIT 25, NextGenAISafety @ ICML 24, Machine Learning and Compression @ NeurIPS 2024

Invited Talks

UCSB AI Meetup, 05/02/2025

Work Experiences

Engineering Intern

Qualcomm Video Systems

Summer 2021

Teaching

Introduction to Machine Learning with Python

Winter 2026 · Designer & Instructor

A 2-day workshop at UCSB Carpentry. Covered supervised learning fundamentals, scikit-learn workflows, Keras framework,and hands-on exercises with real datasets.

"this was by far the most useful ML class I have ever taken. I would take this every week if I could..."
"It will be directly relevant for my research" — Workshop participant

REAL AI Bootcamp

Fall 2025 · Course Designer & Instructor

An 3-day introduction to AI program for high school students. Designed curriculum covering neural networks, computer vision, and ethical AI through interactive projects.

"I enjoyed the activities where we were able to learn about the very difficult concepts hands-on" — Student

This website is adapted from the fantastic code by Jon Barron.