Alan Zelun Luo

Stanford Vision and Learning Lab
Advisor: Prof. Fei-Fei Li
Stanford University
alanzluo at stanford dot edu
[Google Scholar] [Github] [CV (updated on July 2018)]

About

I am a first-year PhD student in the Computer Science department at Stanford University. I am working in the Stanford Vision and Learning Lab, advised by Prof. Fei-Fei Li.

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.

Before that, I received my master's degree from Stanford University and my bachelor's degree from the University of Illinois Urbana-Champaign. During my master's study, I spent three years researching in the Stanford Vision and Learning Lab with Prof. Fei-Fei Li, and the Clinical Excellence Research Center with Prof. Arnold Milstein. During my undergraduate study, I spent three years reseaching in the Quantitative Light Imaging Laboratory with Prof. Gabriel Popescu, and the Computer Vision and Robotics Laboratory with Prof. Jia-Bin Huang and Prof. Narendra Ahuja.

News

Education

Doctor of Philosophy
Computer Science
Stanford University
2018 - Present

Master of Science
Computer Science
Stanford University
2015 - 2018

Bachelor of Science
Electrical and Computer Engineering
University of Illinois Urbana-Champaign
2012 - 2015

Industry

Google
Research Intern
Summer 2017

Amazon A9
Research Intern
Summer 2016

Yahoo
Software Engineering Intern
Summer 2015

Teaching

  • Head Teaching Assistant, MED 277 / CS 337 (AI-Assisted Health Care), Fall 2018

  • Teaching Assistant, CS 231N (Convolutional Neural Networks for Visual Recognition), Spring 2017

  • Teaching Assistant, CS 224N (Natural Language Processing with Deep Learning), Winter 2017

  • Head Teaching Assistant, CS 131 (Computer Vision: Foundations and Applications), Fall 2016

  • Teaching Assistant, CS 109 (Probability for Computer Scientists), Spring 2016

  • Teaching Assistant, CS 109 (Probability for Computer Scientists), Winter 2016

  • Teaching Assistant, CS 131 (Computer Vision: Foundations and Applications), Fall 2015

Professional Activities

  • Reviewer, International Conference on Machine Learning (ICML) 2019

  • Reviewer, Conference on Computer Vision and Pattern Recognition (CVPR) 2019

  • Reviewer, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Nov. 2018

  • Reviewer, Machine Learning for Healthcare (MLHC) 2018

  • Reviewer, Conference on Computer Vision and Pattern Recognition (CVPR) 2018

Selected Publications

Computer Vision and Deep Learning

Graph Distillation for Action Detection with Privileged Information

Action Recognition Multi-modal Learning Knowledge Distillation Learning Using Priviledged Information

Zelun Luo, Jun-Ting Hsieh, Lu Jiang, Juan Carlos Niebles, Li Fei-Fei

European Conference on Computer Vision (ECCV) 2018

DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Network Consistency

Unsupervised Learning Domain Adaptation Depth Estimation Flow Estimation

Yuliang Zou, Zelun Luo, Jia-Bin Huang

European Conference on Computer Vision (ECCV) 2018

Label Efficient Learning of Transferable Representations across Domains and Tasks

Domain Adaptation Semi-Supervised Learning Transfer Learning

Zelun Luo, Yuliang Zou, Judy Hoffman, Li Fei-Fei

Conference on Neural Information Processing Systems (NIPS) 2017

Unsupervised Learning of Long-Term Motion Dynamics for Videos

Action Recognition Unsupervised Learning 3D Computer Vision

Zelun Luo, Boya Peng, De-An Huang, Alexandre Alahi, Li Fei-Fei

Conference on Computer Vision and Pattern Recognition (CVPR) 2017

Towards Viewpoint Invariant 3D Human Pose Estimation

Human Pose Estimation 3D Computer Vision

Albert Haque, Zelun Luo*, Boya Peng*, Alexandre Alahi, Serena Yeung, Li Fei-Fei

European Conference on Computer Vision (ECCV) 2016

AI-Assisted Healthcare

Computer Vision-based Descriptive Analytics of Seniors' Daily Activities for Long-term Health Monitoring

Action Detection Multi-modal Learning

Zelun Luo*, Jun-Ting Hsieh*, Niranjan Balachandar, Serena Yeung, Guido Pusiol, Jay Luxenberg, Grace Li, Li-Jia Li, N. Lance Downing, Arnold Milstein, Li Fei-Fei

Machine Learning for Healthcare (MLHC) 2018, Stanford, CA, August 17-18, 2018

Towards Vision-Based Smart Hospitals: A System for Tracking and Monitoring Hand Hygiene Compliance

Action Recognition 3D Computer Vision

Albert Haque, Michelle Guo, Alexandre Alahi, Serena Yeung, Zelun Luo, Alisha Rege, Amit Singh, Jeffrey Jopling, N. Lance Downing, William Beninati, Terry Platchek, Arnold Milstein, Li Fei-Fei

Machine Learning for Healthcare (MLHC) 2017, Boston, MA, August 18-19, 2017

Computer Vision-based Approach to Maintain Independent Living for Seniors

Action Recognition Multi-modal Learning

Zelun Luo, Alisha Rege, Guido Pusiol, Arnold Milstein, Li Fei-Fei, N. Lance Downing

American Medical Informatics Association (AMIA), Washington, DC, November 4-8, 2017

Vision-Based Hand Hygiene Monitoring in Hospitals

Action Recognition 3D Computer Vision

Serena Yeung, Alexandre Alahi, Zelun Luo, Boya Peng, Albert Haque, Amit Singh, Terry Platchek, Arnold Milstein, Li Fei-Fei

American Medical Informatics Association (AMIA), Chicago, November 12-16, 2016

NIPS Workshop on Machine Learning for Healthcare, 2015

Biomedical Imaging and Diagnosis

Label-Free Tissue Scanner for Colorectal Cancer Screening

Bioimaging Medical Image Analysis

Mikhail E. Kandel, Shamira Sridharan, Jon Liang, Zelun Luo, Kevin Han, Virgilia Macias, Anish Shah, Roshan Patel, Krishnarao Tangella, Andre Kajdacsy-Balla, Grace Guzman, Gabriel Popescu

Journal of Biomedical Optics, Opt. 22(6), 2017

Towards Quantitative Automated Histopathology of Breast Cancer using Spatial Light Interference Microscopy (SLIM)

Bioimaging Medical Image Analysis

Hassaan Majeed, Tan H Nguyen, Mikhail E Kandel, Kevin Han, Zelun Luo, Virgilia Macias, Krishnarao Tangella, Andre Balla, Minh N Do, Gabriel Popescu

United States and Canadian Academy of Pathology (USCAP), Seattle, WA, March 12-18, 2016

Breast Cancer Diagnosis using Spatial Light Interference Microscopy

Bioimaging Medical Image Analysis

Hassaan Majeed, Mikhail E Kandel, Kevin Han, Zelun Luo, Virgilia Macias, Krishnarao Tangella, Andre Balla, Gabriel Popescu

Journal of Biomedical Optics, Opt. 20(11), 2015

High Throughput Imaging of Blood Smears using White Light Diffraction Phase Microscopy

Bioimaging Medical Image Analysis

Hassaan Majeed, Mikhail E Kandel, Basanta Bhaduri, Kevin Han, Zelun Luo, Krishnarao Tangella, Gabriel Popescu

SPIE Photonics West: BiOS, San Francisco, CA, February 7-12, 2015

Diagnosis of Breast Cancer Biopsies using Quantitative Phase Imaging

Bioimaging Medical Image Analysis

Hassaan Majeed, Mikhail E Kandel, Kevin Han, Zelun Luo, Virgilia Macias, Krishnarao Tangella, Andre Balla, Gabriel Popescu

SPIE Photonics West: BiOS, San Francisco, CA, February 7-12, 2015

C++ Software Integration for a High-throughput Phase Imaging Platform

Bioimaging Medical Image Analysis

Mikhail E Kandel, Zelun Luo, Kevin Han, Gabriel Popescu

SPIE Photonics West: BiOS, San Francisco, CA, February 7-12, 2015

Projects

End-to-End Deep Neural Network
for Scene Text Recognition

Internship Project
Visual Search, Amazon A9
Advisors: Dr. Son Tran, Dr. R. Manmatha

Superstitchous:
Image Stitching and Core Segmentation Software for Large Scale Digital Holography

Senior Design
Advisor: Prof. Gabriel Popescu

Navi:
Your In-Store Navigator

Deep Annotator:
A General Purpose Web Annotation Interface

Show, Discriminate, and Tell:
A Discriminative Image Captioning Model
with Deep Neural Networks