Published over 20 papers, see full list on Google Scholar. Notable publications include 'Apple Intelligence Foundation Language Models' (Tech Report 2025), 'Generating Automatic Feedback on UI Mockups with LLMs' (CHI 2024), 'Rambler: Supporting Writing with Speech with LLMs' (CHI 2024). Awards: Google-BAIR Commons Research Grant (2023), UC Berkeley EECS Departmental Fellowship (2022), Outstanding Reviews (2021-24), NSF Graduate Research Fellowship (HM, 2017).
Research Experience
Currently a Research Scientist at Apple's Video Computer-Vision Science team (2023-present), developing and deploying machine learning model optimization and analysis techniques. Previously, an intern at Apple (2020-21) working on 3D scene capture, annotation/segmentation, and navigation, and an intern at Adobe (2019) working on multi-level graph kernel correspondences for vector graphics.
Education
Completed CS PhD in 2023 at UC Berkeley, advised by Björn Hartmann.
Background
Research interests: HCI, computer vision, ML dev tools, model optimization. Worked in Berkeley AI Research (BAIR) Lab and the Berkeley Institute of Design (BiD).
Miscellany
Mentored students: Susan Lin, Sauhard Jain, Matthew Lee, Shuyao Zhou, Angela Zhang, Frederick Kim, Tonya Nguyen. Teaching experience: DI 202 Technology Design Foundations (GSI, 2021), CSC 160 UI Design/Development (Head GSI, 2017, 2020), CSC 169 Software Engineering (Head GSI, 2019), ECE 112 Intro to Logic Design (TA, 2013-2015), ECE 230 Electromagnetic Waves (TA, 2014). Service: Program Committee for ACM CHI (2026), ACM UIST (2024), ICML AI/HCI Workshop (2023), Organizing Committee for ACM UIST (2023, 2024), Reviewer for multiple conferences (2017-2025), Volunteer for ACM SIGCHI Executive Committee (2018), Feature Editor for ACM XRDS Student Magazine (2019), Student Volunteer for ACM IUI and ACM CHI (2017, 2023)