Aston Zhang

I am a senior scientist at Amazon Web Services. My research interests are in deep learning. I earned my Ph.D. in Computer Science from University of Illinois at Urbana-Champaign.

My past internships were with Google Research, Microsoft Research, Yahoo Labs, UBS, and trading. I also obtained an M.S. in Statistics, an M.S. in Computer Science, and a B.Eng in Computer Science with a Business Minor (Rank 1).

[GitHub] [LinkedIn] [Twitter]

Books

• A. Zhang, Z. C. Lipton, M. Li, and A. J. Smola
  Dive into Deep Learning
  • Textbook for STAT 157 Introduction to Deep Learning at UC Berkeley, Spring 2019


• A. Zhang, M. Li, Z. C. Lipton, and A. J. Smola
  动手学深度学习 (in Chinese)
• Best seller of new books in "Computers and Internet" at the largest Chinese online bookstore (week of 7/15/19)

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, 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 [Website]
  In International Conference on Computer Vision (ICCV), 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

 

Papers

• H. Shao, S. Yao, D. Sun, A. Zhang, S. Liu, D. Liu, J. Wang, and T. Abdelzaher
  ControlVAE: Controllable Variational Autoencoder
  In Proceedings of International Conference on Machine Learning (ICML), 2020

• J. Guo, H. He, T. He, L. Lausen, M. Li, H. Lin, X. Shi, C. Wang, J. Xie, S. Zha, A. Zhang, H. Zhang, Z. Zhang, Z. Zhang, S. Zheng, and Y. Zhu
  GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing
  In Journal of Machine Learning Research (JMLR), Vol. 21, No. 23, 2020

• H. Shao, D. Sun, J. Wu, Z. Zhang, A. Zhang, S. Yao, S. Liu, T. Wang, C. Zhang, and T. Abdelzaher
  GitHub Repository Recommendation for Academic Papers
  In Proceedings of the Web Conference (WWW), 2020

• Y. Tay, A. T. Luu, A. Zhang, S. Wang, and S. C. Hui
  Compositional De-Attention Networks
  In Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2019

• S. Zhang, L. Yao, L. V. Tran, A. Zhang, and Y. Tay
  Quaternion Collaborative Filtering for Recommendation
  In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019

• Y. Tay, A. Zhang, A. T. Luu, J. Rao, S. Zhang, S. Wang, J. Fu, and S. C. Hui
  Lightweight and Efficient Neural Natural Language Processing with Quaternion Networks
  In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL), 2019

• Y. Tay, S. Wang, A. T. Luu, J. Fu, M. C. Phan, X. Yuan, J. Rao, S. C. Hui, and A. Zhang
  Simple and Effective Curriculum Pointer-Generator Networks for Reading Comprehension over Long Narratives
  In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL), 2019

• A. El-Kishky, F. Xu, A. Zhang, and J. Han
  Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings
  In Proceedings of the IEEE International Conference on Big Data (IEEE BigData), 2019

• S. Yao, Y. Zhao, A. Zhang, S. Hu, H. Shao, C. Zhang, L. Su, and T. Abdelzaher
  Deep Learning for the Internet of Things
  In Computer, 2018 (selected as May 2018 cover feature of the flagship magazine of the IEEE Computer Society)

• A. Zhang, X. Lu, C. A. Gunter, S. Yao, F. Tao, R. Zhu, H. Gui, D. Fabbri, D. Liebovitz, and B. Malin
  De Facto Diagnosis Specialties: Recognition and Discovery
  In Learning Health Systems (LHS), 2018

• S. Yao, Y. Zhao, H. Shao, C. Zhang, A. Zhang, S. Hu, D. Liu, S. Liu, L. Su, and T. F. Abdelzaher
  SenseGAN: Enabling Deep Learning for Internet of Things with a Semi-Supervised Framework
  In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (ACM Ubicomp, Distinguished Paper Award), 2018

• A. El-Kishky, F. Xu, A. Zhang, S. Macke, and J. Han
  Entropy-Based Subword with an Application to Word Embeddings
  In Proceedings of the 2nd Workshop on Subword and Character Level Models in NLP at the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL SCLeM), 2018

• S. Yao, Y. Zhao, H. Shao, C. Zhang, A. Zhang, D. Liu, S. Liu, L. Su, and T. Abdelzaher
  ApDeepSense: Deep Learning Uncertainty Estimation Without the Pain for IoT
  In Proceedings of the 38th IEEE International Conference on Distributed Computing Systems (ICDCS), 2018

• A. Zhang, L. Garcia-Pueyo, J. B. Wendt, M. Najork, and A. Broder
  Email Category Prediction
  In Proceedings of the 26th International World Wide Web Conference (WWW), 2017

• S. Yao, S. Hu, Y. Zhao, A. Zhang, and T. Abdelzaher
  DeepSense: A Unified Deep Learning Framework for Time-Series Mobile Sensing Data Processing
  In Proceedings of the 26th International World Wide Web Conference (WWW), 2017

• S. Yao, Y. Zhao, A. Zhang, S. Lu, and T. Abdelzaher
  DeepIoT: Compressing Deep Neural Network Structures for Sensing Systems without Loss of Performance
  In Proceedings of the 15th ACM Conference on Embedded Networked Sensor Systems (ACM Sensys, Best Paper Award Nomination), 2017

• S. Yao, Y. Zhao, H. Shao, A. Zhang, C. Zhang, S. Li, and T. Abdelzaher
  RDeepSense: Reliable Deep Mobile Computing Models with Uncertainty Estimations
  In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (ACM Ubicomp), 2017

• A. Zhang, A. Goyal, R. Baeza-Yates, Y. Chang, J. Han, C. A. Gunter, and H. Deng
  Towards Mobile Query Auto-Completion: An Efficient Mobile Application-Aware Approach
  In Proceedings of the 25th International World Wide Web Conference (WWW), 2016

• A. Zhang and Q. Gu
  Accelerated Stochastic Block Coordinate Descent with Optimal Sampling [Proof of Lemmas]
  In Proceedings of the 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2016

• S. Demetriou, W. Merrill, W. Yang, A. Zhang, and C. A. Gunter
  Free for All! Assessing User Data Exposure to Advertising Libraries on Android
  In Proceedings of the Network and Distributed System Security Symposium (NDSS), 2016

• R. Zhu, A. Zhang, J. Peng, and C. Zhai
  Exploiting Temporal Divergence of Topic Distributions for Event Detection
  In Proceedings of the IEEE International Conference on Big Data (IEEE BigData), 2016

• A. Zhang, A. Goyal, W. Kong, H. Deng, A. Dong, Y. Chang, C. A. Gunter, and J. Han
  adaQAC: Adaptive Query Auto-Completion via Implicit Negative Feedback
  In Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2015

• W. Kong, R. Li, J. Luo, A. Zhang, Y. Chang, and J. Allan
  Predicting Search Intent Based on Pre-Search Context
  In Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2015

• H. Fu, A. Zhang, and X. Xie
  Effective Social Graph De-anonymization based on Graph Structure and Descriptive Information
  In ACM Transactions on Intelligent Systems and Technology (ACM TIST), Vol. 6, No. 4, 2015

• A. Zhang*, X. Lu*, C. A. Gunter, D. Fabbri, D. Liebovitz, and B. Malin (*equal contribution)
  Discovering De Facto Diagnosis Specialties
  In Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), 2015 (selected to receive the NSF travel fellowship)

• A. Zhang, X. Xie, K. C.-C. Chang, C. A. Gunter, J. Han, and X. Wang
  Privacy Risk in Anonymized Heterogeneous Information Networks
  In Proceedings of the 17th International Conference on Extending Database Technology (EDBT), 2014

• H. Fu, A. Zhang, and X. Xie
  De-anonymizing Social Graphs via Node Similarity
  In Proceedings of the 23rd International World Wide Web Conference (WWW), 2014

 

Services

• Journal Editorial Board Member
  • Frontiers in Big Data
• Senior Program Committee Member
  • AAAI Conference on Artificial Intelligence (AAAI)
• Program Committee Member/Reviewer
  • AAAI Conference on Artificial Intelligence (AAAI)
  • ACM International Conference on Web Search and Data Mining (WSDM) (Outstanding PC Award)
  • ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
  • Annual Meeting of the Association for Computational Linguistics (ACL)
  • Conference on Neural Information Processing Systems (NeurIPS)
  • International Conference on Machine Learning (ICML)
  • International Conference on Learning Representations (ICLR)
  • The International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
  • The Web Conference (WWW)