I am a fourth-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.

I worked with Prof. Ranjitha Kumar in her Data-driven Design Group in the HCI Group during my undergraduate studies at UIUC. I was also the president of the Promoting Undergraduate Research in Engineering Committee at UIUC.

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.

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  • 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)

Peer-reviewed Conference Publications
  • Multi-modal Search for Inspirational Examples in Design
    Elisa Kwon, Forrest Huang, and Kosa Goucher-Lambert
    To Appear in 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