Hao Li

Applied Scientist
Amazon Web Services

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I'm an applied scientist at Amazon Web Services, Seattle, working on efficient and automatic machine learning algorithms for AWS computer vision services. I received PhD in computer science from University of Maryland, College Park, where I was fortunate to work with Prof. Tom Goldstein and Prof. Hanan Samet. My PhD research focused on efficient and interpretable deep learning, including model pruning, quantization and loss surface visualization for convolutional neural networks.

Selected Publications

Rethinking the Hyperparameters for Fine-tuning
Hao Li, Pratik Chaudhari, Hao Yang, Michael Lam, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
ICLR 2020 [video]
Visualizing the Loss Landscape of Neural Nets
Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer, Tom Goldstein
NeurIPS 2018 [project / code / poster]
Training Quantized Nets: A Deeper Understanding
Hao Li*, Soham De*, Zheng Xu, Christoph Studer, Hanan Samet, Tom Goldstein
NeurIPS 2017 [poster]
ICML 2017 PADL Workshop [talk] Google Best Student Paper
Pruning Filters for Efficient ConvNets
Hao Li, Asim Kadav, Igor Durdanovic, Hanan Samet, Hans Peter Graf
ICLR 2017 [poster]
NeurIPS 2016 EMDNN Workshop

Dissertation

Towards Fast and Efficient Representation Learning
Hao Li
University of Maryland, College Park, Aug 2018 [slides]

Academic Services

  • Journal Reviewer​
    • Journal of Machine Learning Research (JMLR) (editorial board reviewer)
    • International Journal of Computer Vision (IJCV)
    • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
    • IEEE Transactions on Neural Network and Learning Systems (TNNLS)
    • IEEE Transactions on Multimedia (TMM)
    • Neurocomputing
  • Conference Reviewer
    • NeurIPS, ICML, ICLR, ICCV, CVPR, ECCV, KDD, AAAI