Gongbo "Tony" Liang, PhD
Assistant Professor of Computer Science
Texas A&M University-San Antonio
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About Me
Hello, I'm Gongbo "Tony" Liang, an IEEE Senior Member and an Assistant Professor of Computer Science at Texas A&M University-San Antonio. Since 2014, I have been dedicated to the field of computer vision and multi-modality learning, with a passion for making our artificial intelligence systems more trustworthy and robust. My research addresses foundational challenges in modern AI, where I develop novel algorithms for uncertainty-aware learning, model calibration, and explainability. This work directly strengthens the cybersecurity of AI systems by making them more robust against adversarial attacks, more transparent, and more reliable.
My journey in this field was formalized with a Ph.D. in Computer Science from the University of Kentucky under the supervision of Dr. Nathan Jacobs (moved to Washington University in St. Louis). Today, my work bridges the gap between theory and practice. The goal is to apply these trustworthy AI solutions to critical real-world problems, from improving diagnostic precision in medical imaging to enhancing roadway safety in rural areas and mitigating bias in generative AI. As a teacher and mentor, I am committed to a hands-on, project-based approach, empowering students from diverse backgrounds to excel in AI and contribute to a more equitable technological future.
My research and educational initiatives have been recognized with the 2024 CASHI-GOOGLE Award and generously supported by funding from organizations like the NSF, NASA, and Google. I am always looking to connect with motivated students who are eager to tackle challenging problems in trustworthy AI. If you're interested in joining my team, please check out the Openings page to learn more.
News
- 08/22/2025: Received the Excellence in Scholarship Award from the College of Arts and Sciences at Texas A&M University–San Antonio.
- 06/24/2025: Our paper about LLM generated Python code evluation is accepted to IEEE Access (IF: 3.4, Q1).
- 05/07/2025: Happy to annouce that I have been elevated to the prestigious rank of Senior Member by IEEE. This distinction is held by only 10% of IEEE's members and recognizes extensive experience, professional maturity, and significant documented achievements. Hooray!
- 04/11/2025: Be invited to give a talk at the IEEE EMBC Lone Star Chapter and IEEE Lone Star Section Life Member Affinity Group.
- "AI and the Future of Healthcare: Ensuring Reliability and Safety"
- 03/24/2025: Congrats to Jaspal Singh Kahlon on his Honor's project be accepted to the 2025 ACM Southeast Annual Conference, ACM's oldest, continuously running, annual conference with over 50 years of history.
- "PortrAid: An AI-Driven Portrait Assistant for Professional-Quality Image Composition"
- 12/19/2024: Congrats to Demetrio, Yuktha, and Ramya on their papes be accepted to AAAI'25 workshop
- "Benchmarking Robustness of Contrastive Learning Models for Medical Image-Report Retrieval"
- "Exploring the Potential of Large Language Models in Public Transportation: San Antonio Case Study"
- 12/06/2024: Great news! Our poster on making neural networks more reliable won the Best Poster at the IEEE EMBS Long Star Section Workshop on AI and Healthcare
- 11/01/2024: One paper about medcial imaging model calibration is accepted to IEEE BigData'25 (CORE Ranking: B, H5-index: 54, Accept Rate: 18.4%)
- 06/18/2024: Exciting news! We've been awarded a one-year pilot research grant from Google to explore Image Generation Bias
- 05/28/2024: A paper about multi-classification of neuropsychiatric disorders is accepted to IEEE Journal of Biomedical and Health Informatics (IF: 7.7, Q1)
- 04/24/2024: Congrats to Cristian Moran for receiving the First Place Poster Award at the 10th Texas A&M University-San Antonio Student Research Symposium.
- Title: Spatial-Temporal Roadway Accident Visualization and Analysis in San Antonio
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