Michael Xieyang Liu
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People + AI Research (PAIR)
Google DeepMind
moc.liamg@lgg.gnayeixl
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Github
Google Scholar
Research Focus
My research is at the intersection of Human-computer Interaction (HCI), programming tools, sensemaking, intelligent user interfaces, and human-AI interaction, where I design and build systems that accelerate online sensemaking for developers and facilitate human-AI interactions for end-users.
Professional Experience
Aug. 2023 - present
Google DeepMind, Research Scientist
May - Aug. 2022
Microsoft Research, Research Intern
with Advait Sarkar, Carina Negreanu, Jack Williams, Andy Gordon & Ben Zorn
Natural language interactions for end-user programmers using code-generating LLMs.
May - Aug. 2020
Google, Research Intern
with Dustin Smith, Todd Kulesza, & Sarah D'Angelo
Go developers' refactoring practices and engagement with refactoring tools
May - Aug. 2019
Bosch Research, Research Intern
with Lisa Yu, Wan-Yi Lin & Alessandro Oltramari
AI & Crowdsourcing for improving the safety and performance of autonomous vehicles.
Education
2017 - 2023
Ph.D. in Human-Computer Interaction
Carnegie Mellon University, Pittsburgh, PA, USA
Thesis: Tool Support for Knowledge Foraging, Structuring, and Transfer during Online Sensemaking
Advisors: Brad A. Myers & Aniket Kittur
Committee: Kenneth Holstein, Daniel M. Russell
2017 - 2021
M.S. in Human-Computer Interaction
Carnegie Mellon University, Pittsburgh, PA, USA
2013 - 2017
B.S. in Computer Science
University of Michigan, Ann Arbor, MI, USA
Publications
Conference Papers, Journal Articles & Pre-prints
C18.
Minsuk Kahng, Ian Tenney, Mahima Pushkarna, Michael Xieyang Liu, James Wexler, Emily Reif, Krystal Kallarackal, Minsuk Chang, Michael Terry, Lucas Dixon. LLM Comparator: Interactive Analysis of Side-by-Side Evaluation of Large Language Models. IEEE Transactions on Visualization and Computer Graphics, 2024
IEEE VIS 2024
C17.
Michael Xieyang Liu*, Savvas Petridis*, Alexander J. Fiannaca, Vivian Tsai, Michael Terry, Carrie J. Cai. In Situ AI Prototyping: Infusing Multimodal Prompts into Mobile Settings with MobileMaker. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2024
VL/HCC 2024
C16.
Michael Xieyang Liu, Sherry Tongshuang Wu, Tianying Chen, Franklin Mingzhe Li, Aniket Kittur, Brad A. Myers. Selenite: Scaffolding Online Sensemaking with Comprehensive Overviews Elicited from Large Language Models. ACM CHI Conference on Human Factors in Computing Systems (CHI), 2024
CHI 2024
C15.
Franklin Mingzhe Li, Michael Xieyang Liu, Shaun K. Kane, Patrick Carrington. A Contextual Inquiry of People with Vision Impairments in Cooking. ACM CHI Conference on Human Factors in Computing Systems (CHI), 2024
CHI 2024
C14.
Michael Xieyang Liu, Frederick Liu, Alexander J. Fiannaca, Terry Koo, Lucas Dixon, Michael Terry, Carrie J. Cai. "We Need Structured Output": Towards User-centered Constraints on Large Language Model Output. Extended Abstract in ACM CHI Conference on Human Factors in Computing Systems (CHI), 2024
CHI 2024
C13.
Minsuk Kahng, Ian Tenney, Mahima Pushkarna, Michael Xieyang Liu, James Wexler, Emily Reif, Krystal Kallarackal, Minsuk Chang, Michael Terry, Lucas Dixon. LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models. Extended Abstract in ACM CHI Conference on Human Factors in Computing Systems (CHI), 2024
CHI 2024
C12.
Michael Xieyang Liu, Advait Sarkar, Carina Negreanu, Ben Zorn, Jack Williams, Neil Toronto, Andrew D. Gordon. "What It Wants Me To Say": Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language Models. ACM CHI Conference on Human Factors in Computing Systems (CHI), 2023
CHI 2023
🏅 Best Paper Honorable Mention Award
C11.
Tianying Chen, Michael Xieyang Liu, Emily Ding, Emma O’Neil, Mansi Agarwal, Robert E. Kraut, Laura Dabbish. Facilitating Counselor Reflective Learning With a Real-time Annotation Tool. ACM CHI Conference on Human Factors in Computing Systems (CHI), 2023
CHI 2023
C10.
Michael Xieyang Liu, Andrew Kuznetsov, Yongsung Kim, Joseph Chee Chang, Aniket Kittur, Brad A. Myers. Wigglite: Low-cost Information Collection and Triage. ACM Symposium on User Interface Software and Technology (UIST), 2022
UIST 2022
C9.
Franklin Mingzhe Li, Michael Xieyang Liu, Yang Zhang, Patrick Carrington. Freedom to Choose: Understanding Input Modality Preferences of People with Upper-body Motor Impairments for Activities of Daily Living. ACM SIGACCESS Conference on Computers and Accessibility, 2022
ASSETS 2022
C8.
Michael Xieyang Liu, Aniket Kittur, Brad A. Myers. Crystalline: Lowering the Cost for Developers to Collect and Organize Information for Decision Making. ACM CHI Conference on Human Factors in Computing Systems (CHI), 2022
CHI 2022
C7.
Amber Horvath, Michael Xieyang Liu, River Hendriksen, Connor Shannon, Emma Paterson, Kazi Jawad, Andrew Macvean, Brad A. Myers. Understanding How Programmers Can Use Annotations on Documentation. ACM CHI Conference on Human Factors in Computing Systems (CHI), 2022
CHI 2022
C6.
Michael Xieyang Liu, Aniket Kittur, Brad A. Myers. To Reuse or Not To Reuse? A Framework and System for Evaluating Summarized Knowledge. ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW), 2021
CSCW 2021
🏆 Best Paper Award
C5.
Joseph Chee Chang, Yongsung Kim, Victor Miller, Michael Xieyang Liu, Brad A. Myers, Aniket Kittur. Tabs.do: Task-Centric Browser Tab Management. ACM Symposium on User Interface Software and Technology (UIST), 2021
UIST 2021
C4.
Alex Reinhart, Logan Brooks, Maria Jahja, Aaron Rumack, Jingjing Tang, [et al., including Michael Xieyang Liu]. An open repository of real-time COVID-19 indicators. Proceedings of the National Academy of Sciences (PNAS), 2021
PNAS 2021
C3.
Michael Xieyang Liu, Jane Hsieh, Nathan Hahn, Angelina Zhou, Emily Deng, Shaun Burley, Cynthia Taylor, Aniket Kittur, Brad A. Myers. Unakite: Scaffolding Developers’ Decision-Making Using the Web. ACM Symposium on User Interface Software and Technology (UIST), 2019
UIST 2019
🏅 Best Paper Honorable Mention Award
C2.
Jean Y. Song, Stephan J. Lemmer, Michael Xieyang Liu, Shiyan Yan, Juho Kim, Jason J. Corso, Walter S. Lasecki. Popup: Reconstructing 3D Video Using Particle Filtering to Aggregate Crowd Responses. ACM International Conference on Intelligent User Interfaces (IUI), 2019
IUI 2019
C1.
Yu-Wei Chao, Yunfan Liu, Xieyang Liu, Huayi Zeng, Jia Deng. Learning to Detect Human-Object Interactions. IEEE Winter Conference on Applications of Computer Vision (WACV), 2018
WACV 2018
Workshop Papers & Posters
W3.
Jane Hsieh, Michael Xieyang Liu, Brad A. Myers, Aniket Kittur. An Exploratory Study of Web Foraging to Understand and Support Programming Decisions. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2018
VL/HCC 2018
W2.
Michael Xieyang Liu, Nathan Hahn, Angelina Zhou, Shaun Burley, Emily Deng, Aniket Kittur, Brad A. Myers. UNAKITE: Support Developers for Capturing and Persisting Design Rationales When Solving Problems Using Web Resources. DTSHPS'18 Workshop on Designing Technologies to Support Human Problem Solving, 2018
VL/HCC 2018
W1.
Michael Xieyang Liu, Shaun Burley, Emily Deng, Angelina Zhou, Aniket Kittur, Brad A. Myers. Supporting Knowledge Acceleration for Programming from a Sensemaking Perspective. Sensemaking Workshop @ The ACM Conference on Human Factors in Computing Systems (CHI), 2018
CHI 2018
Patent
P2.
Ben Zorn, Carina Negreanu, Advait Sarkar, Andrew Gordon, Jack Williams, Michael Xieyang Liu, Neil Toronto, Sruti Srinivasa Ragavan. Generation of Interactive Utterances of Code Tasks. US Patent (submitted), 2022
P1.
Aniket Kittur, Brad A. Myers, Michael Xieyang Liu. Multidirectional Gesturing for OnDisplay Item Identification and/or Further Action Control. US Patent PCT/US2022/043604 (submitted), 2022
Invited Talks & Guest Lectures
April 2024
Dec. 2023
Building AI Sensemaking Systems, University of ZĂĽrich
Sept. 2023
Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language Models, Viginia Tech
Mar. 2023
Accelerating Programming Sensemaking with Human-Centered Interactive Systems, Microsoft Research
Mar. 2023
Accelerating Programming Sensemaking with Human-Centered Interactive Systems, Apple AI/ML
Feb. 2023
Accelerating Sensemaking with Human-Centered Interactive Systems, Google Research
Feb. 2023
Accelerating Sensemaking with Human-Centered Interactive Systems, Allen Institute for Artificial Intelligence (AI2)
Aug. 2022
Bridging the Abstration Gap Between End-User Programmers and LLM-backed Code-Generating Models, Microsoft Research
Aug. 2020
Understanding Refactoring with Golang, Google Cloud DevEx Presentation
April 2018
Supporting Knowledge Acceleration for Programming from a Sensemaking Perspective, Sensemaking Workshop at CHI Conference on Human Factors in Computing Systems
Open-source Experience
2019 - present
Chrome extension boilerplate (w/ React & Webpack)
3.6k stars, 1.1k forks on GitHub (as of Oct. 2024)
2019 - present
Vertical Tabs Chrome Extension
36.9k users on Chrome Web Store; 460+ stars on GitHub (as of Oct. 2024)
Service
Academic Service
Associate Chair
Paper Reviewing
Conferences: CHI (2019 - 2025), CSCW (2019 - 2023), UIST (2019 - 2024), IUI (2020), VAST (2020)
Journal: TOCHI (2022)
Special Recognitions for Outstanding Reviews: UIST (2021), CHI (2023)
Departmental & Community Service
Committee Member
Ph.D. Admission Committee (2022-2023)
Committee Member
REU (Research Experience for Undergraduate) Admissions Committee (2021-2022)
Committee Member
CMU HCII Faculty Lunch Organization Committee (2019-2020)
Committee Member
CMU HCII Ph.D. Student Lounge Committee (2019-2020)
Research Experience
2023 - present
Research Scientist
People + AI Research, Google
2017 - 2023
Graduate Research Assistant (advised by Brad A. Myers & Aniket Kittur)
Human-Computer Interaction Institute, Carnegie Mellon University
Working on prototype systems that scaffold developers in making decisions using information from various web sources and enable subsequent developers to learn, understand, and reuse those decisions and rationales.
2020 - 2021
Research Assistant (with Jodi Forlizzi, Roni Rosenfeld & Ryan Tibshirani)
Delphi Research Group, Carnegie Mellon University
Working on the visualization team of the COVIDcast system, which displays indicators related to COVID-19 activity level across the U.S. These indicators are derived from a variety of anonymized, aggregated data sources made available by multiple partners, including Facebook, Google, and Quidel. [Press coverage]
2016 - 2017
Undergraduate Researcher
Crowds and Machines Lab, University of Michigan, Ann Arbor
Worked on crowd & AI-powered interdisciplinary projects that address novel and promising research questions.
2015 - 2016
Research Assistant (advised by Jia Deng)
Vision & Learning Lab, University of Michigan, Ann Arbor
Worked on a computer vision based toolkit that boosts performance on human-object interaction detection by exploiting human-object spatial relations.
Mentoring
2018 - 2019
Jane Hsieh
Oberlin College Student (Currently a CMU S3D Ph.D. Candidate)
Studied programmers' web-foraging behaviors. Contributed to the development of the Unakite system.
2017 - 2018
Emily Deng
CMU Master's Student
Designed and carried out interview studies with programmers that probe their programming behaviors and needs.
2017 - 2018
Shaun Burley
CMU Master's Student
Designed and carried out interview studies with programmers that probe their programming behaviors and needs.
Selected Honors, Grants, Awards & Coverage
April 2023
🏅 Best Paper Honorable Mention Award, ACM CHI Conference on Human Factors in Computing Systems (CHI 2023)
Nov. 2022
Special Recognitions for Outstanding Reviews, ACM CHI Conference on Human Factors in Computing Systems (CHI 2023)
Nov. 2021
CMU SCS News Coverage on our CSCW 2021 Best Paper: "CMU Researchers Develop Tool To Help Determine When To Reuse Content"
Oct. 2021
🏆 Best Paper Award, 24th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2021)
June 2021
Special Recognitions for Outstanding Reviews, 34th Annual ACM Symposium on User Interface Software and Technology (UIST 2021)
April 2020
Oct. 2019
🏅 Best Paper Honorable Mention Award, 32nd Annual ACM Symposium on User Interface Software and Technology (UIST 2019)
March 2017
James B. Angell Scholar, 94th Annual Honors Convocation, University of Michigan
March 2017
EECS Scholar Award, 2017 EECS Honors & Awards Reception, University of Michigan
May 2016
Summer Undergraduate Research Experience (SURE) program, University of Michigan
July 2015, July 2016
Tang-Junyuan Fellowship (Top 2/250, $50,000), UM-SJTU Joint Institute
Dec. 2015, April 2016
Dean's List, University of Michigan
Aug. 2015
Basic Teaching Assistant Certificate, Center for Learning and Teaching, UM-SJTU Joint Institute
Dec. 2013, Aug. 2014, Dec. 2014
Dean's List, UM-SJTU Joint Institute
June 2015
Fellowship for Outstanding Academic Performance, Shanghai Jiao Tong University
April 2015
Meritorious Winner (Acceptance: 9%), COMAP Mathematical Contest in Modeling
Teaching Experience
Fall 2020
Teaching Assistant – 05-410/05-610 User-Centered Research & Evaluation
Human-Computer Interaction Institute, Carnegie Mellon University
Fall 2020
Teaching Assistant – 05-431/05-631 Software Structures for User Interfaces
Human-Computer Interaction Institute, Carnegie Mellon University
Fall 2019
Teaching Assistant – 05-430/05-630 Programming Usable Interfaces
Human-Computer Interaction Institute, Carnegie Mellon University
Winter 2017
Instructional Aide – EECS484 Database Management Systems
University of Michigan, Ann Arbor
Fall 2016
Instructional Aide – EECS484 Database Management Systems
University of Michigan, Ann Arbor
Summer 2015
Teaching Assistant – Vv255 Multivariate Calculus
University of Michigan – Shanghai Jiao Tong University Joint Institute
Languages, Technical Skills & Courses
Languages
English, Chinese (Mandarin) - Native or bilingual proficiency, German - Limited working proficiency
Programming
HTML/Javascript/CSS, Python, SQL, C/C++, Swift, Java, LaTeX, etc.
Web & App Development
React.js, Angular, Redux, Bootstrap, Node.js, PHP, Ionic Framework, etc.
Deep Learning & AI
PyTorch, Tensorflow, ml5.js
Courses
Machine Learning, Deep Learning, Advanced User Interfaces, Database Management Systems, Information Security, Web Development