Vera Liao

Vera Liao is a Principal Researcher at Microsoft Research, where she is part of the FATE (Fairness, Accountability, Transparency, and Ethics of AI) group. She will join the University of Michigan Computer Science and Engineering department as an Associate Professor in fall 2025. Her work focuses on human-AI interaction, explainable AI, and responsible computing. Liao has made significant contributions to IBM products such as AI Explainability 360 and Uncertainty Quantification 360 during her time at IBM T.J. Watson Research Center.

Dr. Liao received her education from the University of Illinois at Urbana-Champaign and Tsinghua University. Her academic journey has positioned her at the intersection of human-computer interaction and artificial intelligence, with a strong emphasis on creating AI systems that are transparent, accountable, and user-centered.

Vera Liao's research primarily centers around human-centered AI explainability and transparency. She investigates how to design AI systems that effectively communicate their capabilities, limitations, and decision-making processes to users. Her work examines the intersection of AI transparency with trust, control, and user experience. Liao has pioneered approaches to bridging the socio-technical gap in AI evaluation and has developed frameworks for contextualized evaluation of explainable AI systems. Her research spans multiple domains including conversational interfaces, data storytelling, and creative work with generative AI.

Liao's publications reveal a clear trend toward addressing the challenges of large language models and their impact on human-AI interaction. Her recent work focuses on understanding how uncertainty communication affects user trust, how to design for appropriate reliance on AI systems, and how to create authentic co-creation experiences with generative models. She has been examining the risks in AI-infused information ecosystems and developing methods for human-centered evaluation of language technologies.

Her scientific contributions have been recognized with multiple honors:

• Best Paper Award, Honorable Mention at CHI 2025 (two papers)
• Best Paper Award at CHI 2024
• Best Paper Award, Honorable Mention at FAccT 2023
• Best Paper Award, Honorable Mention at HCOMP 2022
• Best Paper Award, Honorable Mention at CHI 2021
• Best Paper Award, Honorable Mention at CHI 2014
• Outstanding Paper Award at IUI 2019

Dr. Liao is an active mentor, having guided numerous research interns from top universities including Cornell, Princeton, CMU, Stanford, and MIT. She serves in editorial roles as Co-Editor-in-Chief of the Springer Human-Computer Interaction Book Series and as an Editor for ACM CSCW. Liao has secured research funding through her work at Microsoft Research and previously at IBM, focusing on projects related to AI explainability, transparency, and responsible AI development.

As part of Microsoft Research's FATE group, Liao collaborates with a multidisciplinary team of researchers focused on the ethical implications of AI technologies. Her work bridges the gap between technical AI development and human-centered design principles, ensuring that AI systems are developed with user needs and societal impacts in mind.