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.
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.
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
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
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
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
CS182/282A Designing, Visualizing and Understanding Deep Neural Networks
CS160 User Interface Design and Development
CS280 Computer Vision
CS294 Talking to Robots
CS294 Special Topics in Deep Learning