Li, Ang

Senior Research Scientist
Google DeepMind

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Biography

I am a Senior Research Scientist at Google DeepMind, Mountain View, CA. My research aims at developing deep and reinforced AI systems that are scalable and feasible for learning from the real world. I also work closely with many engineering teams to land cutting-edge AI technologies into Alphabet products. I led the development of Population Based Training into Google's infrastructure. Our infrastructure became the basis for multiple collaborations such as Hyper-parameter Tuning for Google's Self-driving Cars and Automatic Data Augmentation in Waymo. I further landed the application of meta learning in optimizing Graph Neural Networks for Google Maps traffic prediction. I was an AI coach at Google Launchpad Accelerator and consulted a non-profit organization WattTime on applying artificial intelligence with satellite imaging to estimate carbon emission from power plants across the globe.

I received my Ph.D. in Computer Science in 2017 from the University of Maryland College Park,, and B.Sc. from Nanjing University. I have also pursued research studies in artificial intelligence at Carnegie Mellon University, Google, Facebook AI Research, and Comcast Labs DC.

Publication

2020

  • The Effectiveness of Memory Replay in Large Scale Continual LearningPDF ] [ bibtex ]
    Yogesh Balaji, Mehrdad Farajtabar, Dong Yin, Alex Mott, Ang Li
    ArXiv 2020.
  • Learning to Incentivize Other Learning AgentsPDF ] [ bibtex ] [ code ]
    Jiachen Yang, Ang Li, Mehrdad Farajtabar, Peter Sunehag, Edward Hughes and Hongyuan Zha
    NeurIPS 2020.
    - AAMAS 2020 Adaptive and Learning Agents (ALA) Workshop.
  • SOLA: Continual Learning with Second-Order Loss Approximation PDF ] [ bibtex ]
    Dong Yin, Mehrdad Farajtabar, Ang Li
    ArXiv 2020.
    - ICML 2020 Workshop on Continual Learning.
  • The AVA-Kinetics Localized Human Actions Video DatasetPDF ] [ bibtex ]
    Ang Li, Meghana Thotakuri, David A. Ross, Joao Carreira, Alexander Vostrikov, Andrew Zisserman
    ArXiv 2020.
  • Hybrid Models for Open Set RecognitionPDF ] [ Bibtex ]
    Hongjie Zhang, Ang Li, Jie Guo, Yanwen Guo
    ECCV 2020 (Oral).
  • PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous DrivingPDF ] [ bibtex ]
    Zelun Kong, Junfeng Guo, Ang Li, Cong Liu
    CVPR 2020.
  • Orthogonal Gradient Descent for Continual LearningPDF ] [ Bibtex ]
    Mehrdad Farajtabar, Navid Azizan, Alex Mott, Ang Li
    AISTATS 2020
  • Prediction, Consistency, Curvature: Representation Learning for Locally-Linear ControlPDF ] [ Bibtex ]
    Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui
    ICLR 2020
    - Poster at BayLearn 2019.
  • Improved Knowledge Distillation via Teacher AssistantPDF ] [ Bibtex ]
    Seyed-Iman Mirzadeh, Mehrdad Farajtabar, Ang Li, Nir Levine, Akihiro Matsukawa, Hassan Ghasemzadeh
    AAAI 2020.
    - Poster at BayLearn 2019

2019

  • Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing
    Ge Liu, Heng-Tze Cheng, Rui Wu, Jing Wang, Jayiden Ooi, Lihong Li, Ang Li, Sibon Li, Craig Boutilier.
    - NeurIPS 2019 Deep Reinforcement Learning Workshop, Vancouver, BC.
    - NeurIPS 2019 Optimization Foundations for Reinforcement Learning Workshop, Vancouver, BC.
  • Cross-View Policy Learning for Street NavigationPDF ] [ Bibtex ]
    Ang Li*, Huiyi Hu*, Piotr Mirowski, Mehrdad Farajtabar
    ICCV 2019.
    - Short paper at ICML 2019 Multitask and Lifelong RL workshop, Long Beach, CA.
    - Poster at BayLearn 2019.
  • Layout-induced Video Representation for Recognizing Agent-in-Place ActionsPDF ] [ Bibtex ]
    Ruichi Yu, Hongcheng Wang, Ang Li, Jingxiao Zheng, Vlad I. Morariu, Larry S. Davis
    ICCV 2019.
    - Poster at BayLearn 2019.
  • A Generalized Framework for Population Based TrainingPDF ] [  Youtube  ] [ Bibtex ]
    Ang Li, Ola Spyra, Sagi Perel, Valentin Dalibard, Max Jaderberg, Chenjie Gu, David Budden, Tim Harley, Pramod Gupta
    KDD 2019.
    - Short paper at NeurIPS 2018 Workshop on Systems for ML, Montréal, Canada.
  • Improving Open Set Domain Adaptation Using Image-to-Image Translation
    Hongjie Zhang, Ang Li, Xu Han, Zhaoming Chen, Yang Zhang, Yanwen Guo
    ICME 2019.
  • SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-task LearningPDF ]
    Jiaqi Ma, Zhe Zhao, Jilin Chen, Ang Li, Lichan Hong, Ed H. Chi
    AAAI 2019, Honolulu, Hawaii.

2018

  • C-WSL: Count-guided Weakly Supervised LocalizationPDF ] [ Bibtex ]
    Mingfei Gao, Ang Li, Ruichi Yu, Vlad I. Morariu, Larry S. Davis
    ECCV 2018, Munich, Germany.
  • NISP: Pruning Networks using Neuron Importance Score PropagationPDF ] [ Bibtex ]
    Ruichi Yu, Ang Li, Chun-Fu Chen, Jui-Hsin Lai, Vlad I. Morariu, Xintong Han, Mingfei Gao, Ching-Yung Lin, Larry S. Davis
    CVPR 2018, Salt Lake City, Utah.
  • Dynamic Zoom-in Network for Fast Object Detection in Large ImagesPDF ] [ Bibtex ]
    Mingfei Gao, Ruichi Yu, Ang Li, Vlad I. Morariu, Larry S. Davis
    CVPR 2018, Salt Lake City, Utah.

2017

2015

2014

2013

2012

2010

Professional Service

  • Journal Reviewer:
    • IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI) 2019, 2020
    • IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 2020
    • IEEE Transaction on Image Processing (TIP) 2017
    • The Visual Computer Journal (TVCJ) 2016
    • SPIE Journal of Electronic Imaging (JEI) 2014, 2016, 2018, 2019
    • IEEE Transaction on Cybernetics 2014
    • Robotics and Autonomous Systems 2018
    • Machine Learning 2019
  • Senior Program Committee:
    • AAAI Conference on Artificial Intelligence (AAAI) 2021
    • International Joint Conference on Artificial Intelligence (IJCAI) 2020, 2021
    • International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS) 2020
  • Program Committee or Reviewer:
    • International Conference on Learning Representations (ICLR) 2018, 2019, 2020
    • Annual Conference on Neural Information Processing Systems (NeurIPS) 2017, 2018, 2019
    • IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, 2018, 2019
    • International Conference on Machine Learning (ICML) 2017, 2018, 2019
    • IEEE International Conference on Computer Vision (ICCV) 2015, 2017, 2019
    • European Conference on Computer Vision (ECCV) 2018
    • International Joint Conference on Artificial Intelligence (IJCAI) 2019
    • International Conference on Artificial Intelligence and Statistics (AISTATS) 2018, 2020
    • Asian Conference on Computer Vision (ACCV) 2018
    • Asian Conference on Machine Learning (ACML) 2019
    • Winter Conference on Computer Vision (WACV) 2020
    • IEEE International Conference on Biometrics (BTAS) 2012, 2015
    • ACM International Conference on Multimedia (MM) 2014