Twitter CV

Aston Zhang is a scientist at Amazon Web Services AI Research. He studies language models and multimodality for AI. He received the ICLR Outstanding Paper Award (2021), the ACM Ubicomp Distinguished Paper Award (2018), and the ACM SenSys Best Paper Award Nomination (2017). His open-source textbook, Dive into Deep Learning, has been adopted worldwide. He obtained his Ph.D. in Computer Science from University of Illinois at Urbana-Champaign.

Hi! I’m happy to connect and discuss. Our office is at Santa Clara in the San Francisco Bay Area. Just email me.

Books

• A. Zhang, Z. C. Lipton, M. Li, and A. J. Smola
  Dive into Deep Learning
  Cambridge University Press, 2023
  
  • Adopted at 400 universities from 60 countries
  • Featured in the AWS re:Invent keynote by Swami, Head of AWS AI, Database, and Analytics
    
• A. Zhang, M. Li, Z. C. Lipton, and A. J. Smola
  动手学深度学习
  人民邮电出版社, 2nd ed., 2023, 1st ed., 2019
  
  • Best seller in China
    

Papers (All)

• Z. Zhang, A. Zhang, M. Li, H. Zhao, G. Karypis, and A. J. Smola
  Multimodal Chain-of-Thought Reasoning in Language Models
  “Imagine reading a book without figures: Multimodal-CoT surpasses humans on ScienceQA.” In arXiv, 2023
  [Idea Inspiration by Homeschooling]

• J. Chen, A. Zhang, X. Shi, M. Li, A. J. Smola, and D. Yang
  Parameter-Efficient Fine-Tuning Design Spaces
  In Proceedings of the International Conference on Learning Representations (ICLR), 2023
  

• Z. Zhang, A. Zhang, M. Li, and A. J. Smola
  Automatic Chain of Thought Prompting in Large Language Models
  In Proceedings of the International Conference on Learning Representations (ICLR), 2023
  

• Z. Liu, Z. Tang, X. Shi, A. Zhang, M. Li, A. Shrivastava, and A. Wilson
  Learning Multimodal Data Augmentation in Feature Space
  In Proceedings of the International Conference on Learning Representations (ICLR), 2023
  

• T. Yang, Y. Zhu, Y. Xie, A. Zhang, C. Chen, and M. Li
  AIM: Adapting Image Models for Efficient Video Understanding
  In Proceedings of the International Conference on Learning Representations (ICLR), 2023
  

• H. Wang, A. Zhang, Y. Zhu, S. Zheng, M. Li, A. J. Smola, and Z. Wang
  Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition
  In Proceedings of International Conference on Machine Learning (ICML, Long Presentation), 2022
  

• H. Wang, A. Zhang, S. Zheng, X. Shi, M. Li, and Z. Wang
  Removing Batch Normalization Boosts Adversarial Training
  In Proceedings of International Conference on Machine Learning (ICML), 2022
  

• E. Grassucci, A. Zhang, and D. Comminiello
  PHNNs: Lightweight Neural Networks via Parameterized Hypercomplex Convolutions
  In IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
  

• A. Zhang, Y. Tay, S. Zhang, A. Chan, A. T. Luu, S. C. Hui, and J. Fu
  Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with 1/n Parameters
  In Proceedings of the International Conference on Learning Representations (ICLR, Outstanding Paper Award), 2021
  

Tutorials

• with A. J. Smola
  Attention in Deep Learning [Keynote] [PDF] [Video]
  In The 36th International Conference on Machine Learning (ICML), 2019

• with H. Lin, X. Shi, L. Lausen, H. He, S. Zha, and A. J. Smola
  Dive into Deep Learning for Natural Language Processing
  In Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019

• with H. Lin, L. Lausen, S. Zha, A. J. Smola, C. Wang, and M. Li
  From Shallow to Deep Language Representations: Pre-training, Fine-tuning, and Beyond [Website]
  In The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019

• with H. Zhang, T. He, Z. Zhang, Z. Zhang, H. Lin, and M. Li
  Everything You Need to Know to Reproduce SOTA Deep Learning Models from Hands-on Tutorial
  In International Conference on Computer Vision (ICCV), 2019

Services

• Area Chair
  • Annual Meeting of the Association for Computational Linguistics (ACL)
  • Conference on Empirical Methods in Natural Language Processing (EMNLP)
• Senior Program Committee
  • AAAI Conference on Artificial Intelligence (AAAI)
• Journal Editorial Board
  • Frontiers in Big Data

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