Bingbin Liu

M.S. Candidate. Stanford University
bingbin [at] stanford [dot] edu
LinkedIn / Github / Google Scholar / CV


I am a second-year CS master's student at Stanford working on the video and healthcare team in the Stanford Vision and Learning Lab under the supervision of Prof. Li Fei-Fei and Dr. Juan Carlos Niebles. I am really interested in video understanding and would like to build video understanding models that are reliable, efficient and versatile enough for real-world applications. I am currently applying to PhD programs, where I can get more in-depth studies on interpretability, data efficiency, and visual reasoning.


Publications

2018

Temporal Modular Networks for Retrieving Complex Compositional Activities in Videos
Bingbin Liu, Serena Yeung, Edward Chou, De-An Huang, Li Fei-Fei, Juan Carlos Niebles
In European Conference on Computer Vision (ECCV), 2018
Paper Project page Poster Video

Learning to Decompose and Disentangle Representations for Video Prediction
Jun-Ting Hsieh, Bingbin Liu, De-An Huang, Li Fei-Fei, Juan Carlos Niebles
In Neural Information Processing Systems (NeurIPS), 2018
Paper Github Poster Video

3D Point Cloud-Based Visual Prediction of ICU Mobility Care Activities
Bingbin Liu*, Michelle Guo*, Edward Chou, Rishab Mehra, Serena Yeung, N. Lance Downing, Francesca Salipur, Jeffrey Jopling, Brandi Campbell, Kayla Deru, William Beninati, Arnold Milstein,
In Machine Learning for Health Care (MLHC), 2018
Paper

Experiences

Teaching: I am currently a teaching assistant for MED277/CS377: AI-Assisted Healthcare leading the ICU project, and was a teaching assistent for CS231n: Convolutional Neural Networks for Visual Recognition in Spring 2018.
I also had a great time working with some talented high school girls who are starting to learn coding. I helped at Girls teach Girls to Code (GTGTC) in April 2018 as the mentor lead of the AI team. I worked with Rob Voigt as research mentors for the NLP team at Stanford AI4ALL in summer 2018, where we worked with an amazing team of 8 girls on a project applying NLP techniques on Tweets to help with identifying resources for disaster relief. If you are interested in learning more about the role identities play in tech industries, please check out the website of Morgan Ames, a postdoc researher who observed the AI4ALL camps and is really nice to talk to. :)

Internship: I joined the Enterprise and Analytics team as a Group IT intern at CLP Power Hong Kong Limited in summer 2016, and was a software engineering intern at Hututa in summer 2015.

Projects

Stacked Attention for Visual Question Answering
CS224N project with Weini Yu. [Report / Poster]

Automatic Melody Transcription
CS229 project with Laetitia Shao and Xiaoyan Wu. [Report / Poster]

Cell Classification & Counting
Summer research project under the supervision of Dr. Dirk Schnieders. [Github]

Object Recognition with Videos
Final year project under the supervision of Dr. Kenneth Wong. [Report / Poster]

Compiler
Undergraduate Research under the supervision of Prof. Ben Hardekopf.

Awards

  • Women in Computer Vision Travel Grant WiCV 2018
  • Powering a Sustainable Generation Scholarship by CLP 2015
  • HKU World Wide Scholarship 2015
  • Dean's Honours List 2013 - 2017
  • Entrance Scholarship for Outstanding Mainland Students 2013 - 2017