I am a final-year PhD Candidate at University of California, Berkeley working with Prof. John Canny. My current research focuses on developing machine-learning powered interactive systems supporting sketch-based human-computer interactions. I am based in Hong Kong | Berkeley, CA. I am familiar with Tensorflow/Machine Learning research, and Java/Android | Python/Flask Development.

My research is kindly supported by Berkeley Institute of Design, Berkeley AI Research, and Google. I also graciously received an Honourable Mention for the Adobe Research Fellowship 2020.

I am currently on the job market looking for industry research positions starting Fall 2022.

descriptionCV (Feb 2022)

rss_feed news

  • 06/23/2021 Our Paper Multi-modal Search for Inspirational Examples in Design is accepted to IDETC 2021!

  • 02/10/2020 Our Late-breaking Work JAM: Just-in-time Analysis of Model Training for Non-Expert ML Programmers is accepted to CHI 2020!

  • 12/12/2019 Our paper Scones: Towards Conversational Authoring of Sketches is accepted as a long paper to IUI 2020!

  • 11/20/2019 I am excited to receive an Honourable Mention for the Adobe Research Fellowship 2020.

  • 10/20/2019 We presented our paper Sketchforme: Composing Sketched Scenes from Text Descriptions for Interactive Applications at UIST 2019 in New Orleans, USA.

library_books publications

(note: publications prior to 2018 published as Zifeng Huang)

Book Chapters

  • Sketch-based Creativity Support Tools using Deep Learning
    Forrest Huang, Eldon Schoop, David Ha, Jeffrey Nichols, and John Canny
    In Artificial Intelligence for Human Copmuter Interaction: A Modern Approach (Springer 2021) | Preprint | Book

  • An Early Rico Retrospective: Three Years of Uses for a Mobile App Dataset
    Biplab Deka, Bardia Doosti, Forrest Huang, Chad Franzen, Joshua Hibschman, Daniel Afergan, Yang Li, Ranjitha Kumar, Tao Dong, and Jeffrey Nichols
    In Artificial Intelligence for Human Copmuter Interaction: A Modern Approach (Springer 2021) | Book


Peer-reviewed Conference Publications

  • Multi-modal Search for Inspirational Examples in Design
    Elisa Kwon, Forrest Huang, and Kosa Goucher-Lambert
    Proceedings of IDETC '21 | Paper

  • UMLAUT: Debugging Deep Learning Programs using Program Structure and Model Behavior
    Eldon Schoop, Forrest Huang, and Björn Hartmann
    Proceedings of CHI '21 | Paper

  • Scones: Towards Conversational Authoring of Sketches
    Forrest Huang, Eldon Schoop, David Ha, and John F. Canny
    Proceedings of IUI '20 (Long Paper) | Paper

  • Sketchforme: Composing Sketched Scenes from Text Descriptions for Interactive Applications
    Forrest Huang, and John F. Canny
    Proceedings of UIST '19 | Paper

  • Swire: Sketch-based User Interface Retrieval
    Forrest Huang, John F. Canny, and Jeffrey Nichols
    Proceedings of CHI '19 | Paper

  • MakerLens: What Sign-In, Reservation and Training Data Can (and Cannot) Tell You About Your Makerspace
    Eldon Schoop, Forrest Huang, Nathan Khuu, and Björn Hartmann
    Proceedings of ISAM '18 | Paper

  • ZIPT: Zero-Integration Performance Testing of Mobile App Designs
    Biplab Deka, Zifeng Huang, Chad Franzen, Jeffrey Nichols, Yang Li, and Ranjitha Kumar
    Proceedings of UIST '17 | Paper

  • Rico: A Mobile App Dataset for Building Data-Driven Design Applications
    Biplab Deka, Zifeng Huang, Chad Franzen, Joshua Hibschman, Daniel Afergan, Yang Li, Jeffrey Nichols, and Ranjitha Kumar
    Proceedings of UIST '17 | Paper

  • ERICA: Interaction Mining for Mobile Apps
    Biplab Deka, Zifeng Huang, and Ranjitha Kumar
    Proceedings of UIST '16 | Paper


Journal Articles

  • GPU-Accelerated t-Distributed Stochastic Neighbor Embedding
    David M. Chan*, Roshan Rao*, Forrest Huang*, and John F. Canny
    Journal of Parallel and Distributed Computing | Paper


Workshop Papers | Posters | Extended Abstracts

  • SCRAM: Simple Checks for RealtimeAnalysis of Model Training forNon-Expert ML Programmers
    Eldon Schoop, Forrest Huang, and Björn Hartmann
    Late-Breaking Works of CHI '20 and ICML 2020 Workshop on Human in the Loop Learning | LBW

  • t-SNE-CUDA: GPU-Accelerated t-SNE and its Applications to Modern Data
    David M. Chan*, Roshan Rao*, Forrest Huang*, and John F. Canny
    HPML Workshop '18 Outstanding Paper Award | Paper

  • Ranking Designs and Users in Online Social Networks
    Biplab Deka, Haizi Yu, Devin Ho, Zifeng Huang, Jerry O. Talton, and Ranjitha Kumar
    Extended Abstracts of CHI '15 | Poster | Extended Abstract

navigation coursework

  • Teaching

    CS182/282A Designing, Visualizing and Understanding Deep Neural Networks

    CS160 User Interface Design and Development

  • Selected Coursework

    CS280 Computer Vision

    CS294 Talking to Robots

    CS294 Special Topics in Deep Learning