Starting Fall 2019, I will be an Assistant Professor of Biomedical Data Science and Electrical Engineering (by courtesy) at Stanford University. For the 2018-19 academic year, I will be visiting Harvard University as a TEAM postdoctoral fellow, focusing on the intersection of AI and healthcare and hosted by Susan Murphy, Todd Zickler and John Halamka.

I received my Ph.D. from Stanford University, where I was advised by Fei-Fei Li and Arnold Milstein. My research was broadly in the areas of computer vision, machine learning, and deep learning, with particular focus on video understanding and applications to healthcare.

I spent internships at Facebook AI Research in 2016 and Google Cloud AI in 2017. I also co-taught Stanford's CS231N Convolutional Neural Networks course in 2017 and 2018, with Justin Johnson and Fei-Fei Li.

Before starting my Ph.D., I received a B.S. in Electrical Engineering in 2010, and an M.S. in Electrical Engineering in 2013, both from Stanford. I also worked as a software engineer at Rockmelt (acquired by Yahoo) from 2009-2011.


Publications

Temporal Modular Networks for Retrieving Complex Compositional Activities in Video
Bingbin Liu, Serena Yeung, Edward Chou, De-An Huang, Li Fei-Fei, Juan Carlos Niebles
ECCV 2018
[Coming soon]
Neural Graph Matching Networks for Fewshot 3D Action Recognition
Michelle Guo, Edward Chou, Shuran Song, De-An Huang, Serena Yeung, Li Fei-Fei
ECCV 2018
[Coming soon]
Focus on the Hard Things: Dynamic Task Prioritization for Multitask Learning
Michelle Guo, Albert Haque, De-An Huang, Serena Yeung, Li Fei-Fei
ECCV 2018
[Coming soon]
Computer Vision-based Descriptive Analytics of Seniors’ Daily Activities for Long-term Health Monitoring
Jun-Ting Hsieh*, Zelun Luo*, Niranjan Balachandar, Serena Yeung, Guido Pusiol, Jay Luxenberg, Grace Li, Li-Jia Li, N. Lance Downing, Arnold Milstein, Li Fei-Fei
MLHC 2018
[Coming soon]
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, Li Fei-Fei
MLHC 2018
[Coming soon]
Bedside Computer Vision -- Moving Artificial Intelligence from Driver Assistance to Patient Safety
Serena Yeung, N. Lance Downing, Li Fei-Fei, Arnold Milstein
New England Journal of Medicine 2018
[pdf]
Scaling Human-Object Interaction Recognition through Zero-Shot Learning
Liyue Shen, Serena Yeung, Judy Hoffman, Greg Mori, Li Fei-Fei
WACV 2018
[pdf]
Tool Detection and Operative Skill Assessment in Surgical Videos Using Region-Based Convolutional Neural Networks
Amy Jin, Serena Yeung, Jeffrey Jopling, Jonathan Krause, Dan Azagury, Arnold Milstein, Li Fei-Fei
NIPS 2017 Machine Learning for Health Workshop (Best Paper Award)
WACV 2018
[pdf] [project page] [data]
Tackling Over-pruning in Variational Autoencoders
Serena Yeung, Anitha Kannan, Yann Dauphin, Li Fei-Fei
ICML 2017 Workshop on Principled Approaches to Deep Learning
[pdf]
Towards Vision-Based Smart Hospitals: A System for Tracking and Monitoring Hand Hygiene Compliance
Albert Haque, Michelle Guo, Alexandre Alahi, Serena Yeung, Zelun Luo, Alisha Rege, Jeffrey Jopling, Lance Downing, William Beninati, Amit Singh, Terry Platchek, Arnold Milstein, Li Fei-Fei
MLHC 2017
[pdf]
Learning to Learn from Noisy Web Videos
Serena Yeung, Vignesh Ramanathan, Olga Russakovsky, Liyue Shen, Greg Mori, Li Fei-Fei
CVPR 2017
[pdf]
Jointly Learning Energy Expenditures and Activities using Egocentric Multimodal Signals
Katsuyuki Nakamura, Serena Yeung, Alexandre Alahi, Li Fei-Fei
CVPR 2017
[pdf] [project page]
Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos
Serena Yeung, Olga Russakovsky, Ning Jin, Mykhaylo Andriluka, Greg Mori, Li Fei-Fei
IJCV 2017
[pdf] [project page] [data]
End-to-end Learning of Action Detection from Frame Glimpses in Videos
Serena Yeung, Olga Russakovsky, Greg Mori, Li Fei-Fei
CVPR 2016
[pdf] [project page] [code]
Towards Viewpoint Invariant 3D Human Pose Estimation
Albert Haque, Boya Peng, Zelun Luo, Alexandre Alahi, Serena Yeung, Li Fei-Fei
ECCV 2016
[pdf] [project page]
Vision-Based Hand Hygiene Monitoring in Hospitals
Serena Yeung, Alexandre Alahi, Zelun Luo, Boya Peng, Albert Haque, Amit Singh, Terry Platchek, Arnold Milstein, Li Fei-Fei
NIPS 2015 Machine Learning for Health Care Workshop
[pdf]
VideoSET: Video Summary Evaluation through Text
Serena Yeung, Alireza Fathi, Li Fei-Fei
CVPR 2014 Egocentric Vision Workshop
[pdf] [project page] [data]
Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis
Quoc Le, Will Zou, Serena Yeung, Andrew Ng
CVPR 2011
[pdf]

AI-Assisted Healthcare

I am a member of the Stanford Program in AI-Assisted Care (PAC), which is a collaboration between the Stanford AI Lab and Stanford Clinical Excellence Research Center that aims to use computer vision and machine learning to create AI-assisted smart healthcare spaces. My particular focus is on applying my research in video understanding and human action recognition towards hand hygiene-based infection control, recognition of clinical care activities, and continuous patient assessment in hospitals and assisted living facilities.

Our collaborators include Lucile Packard Children's Hospital at Stanford, Stanford Health Care, and Intermountain Healthcare.


Outreach

I enjoy helping future generations of researchers and engineers discover the exciting field of AI. I was a Research Instructor for SAILORS 2015, a 2-week summer program run by the AI Lab for 10th grade girls. In the past I've also co-organized Stanford's JETS Engineering Outreach Day for high school students, and been involved with programs including Exploring New Worlds, for elementary school students from underprivileged areas, and TechGyrls.