I am currently working at ByteDance as head of the applied machine learning (AML) research team. Previously, I worked as a research scientist at Google. Even earlier, I received my PhD from Computer Science Department, Princeton University, working with Prof. David Blei. Our team works on fundamental machine learning research and its applications for many of our products, such as TikTok and Douyin, among others. We are actively hiring research engineers, scientists and interns. Please apply here: research scientist and research engineer. If you are seeking an internship, you can apply here: internship. Feel free to use my referral code: UN7TKMA. email: chong.wang@[companyname].com

Some Awards:

• SIGKDD 2021 Test of Time Award
• Google PhD fellow and Siebel Scholar
• Paper awards or honorable mentions at NIPS, AISTATS, KDD

Highlights:

• A more accurate approximation to softmax attention with linear complexity,
  • Linear Complexity Randomized Self-attention Mechanism, ICML 2022
• A more efficient nonuniform negative sampling algorithm,
  • Nonuniform Negative Sampling and Log Odds Correction with Rare Events Data, NeurIPS 2021
• Learning large-scale end-to-end retrieval models without resorting to approximate nearest neighbor search,
  • Deep Retrieval: An End-to-End Learnable Structure Model for Large-Scale Recommendations, CIKM 2021.
• Neural networks meet structured Bayesian methods,
  • Fully Supervised Speaker Diarization provides better accuracy and efficiency in speaker diarization, ICASSP 2019.
    • Official Google AI blog.
    • Media reports: VentureBeat, SiliconANGLE, InfoQ, futurism, cnBeta, Sina Tech, iThome, ChinaEmail, eepw, QbitAI, oschina.
    • Open source on github with 1400+ stars!
• A generic approach for sequence modeling through segmentations,
  • Sequence Modeling via Segmentations, ICML 2017;
  • Towards Neural Phrase-based Machine Translation (code), ICLR 2018;
  • Subgoal Discovery for Hierarchical Dialogue Policy Learning, EMNLP 2018.
  • Neural Phrase-to-Phrase Machine Translation on Arxiv.
• Lookahead convolution architecture (ICLR 2016 workshop) enabled the deployment of an end-to-end speech recognition system (ICML 2016) to benefit hundreds of millions of users (http://maps.baidu.com) by significantly reducing the latency. See a torch implementation.
• Collaborative topic models (KDD 2011) are used by New York Times for their recommendation engine.

Publications:

• Find me at Google scholar and LinkedIn.

Recent News:

• 05/2022: Differentially Private Multi-Party Data Release for Linear Regression accepted to UAI 2022.
• 05/2022: PathFlow: A Normalizing Flow Generator that Finds Transition Paths accepted to UAI 2022.
• 05/2022: Fourier Learning with Cyclical Data accepted to ICML 2022.
• 05/2022: Linear Complexity Randomized Self-attention Mechanism accepted to ICML 2022.
• 03/2022: Differentially Private Label Protection in Split Learning on arxiv, 2022.
• 01/2022: Label Leakage and Protection in Two-party Split Learning accepted to ICLR, 2022.
• 11/2021: Learning Large-Time-Step Molecular Dynamics with Graph Neural Networks presented at AI for Science workshop in NeurIPS 2021.
• 09/2021: Nonuniform Negative Sampling and Log Odds Correction with Rare Events Data accepted to NeurIPS 2021.
• 08/2021: Deep Retrieval: An End-to-End Learnable Structure Model for Large-Scale Recommendations accepted to CIKM 2021.
• 05/2019: Rate Distortion For Model Compression: From Theory To Practice accepted to ICML 2019.
• 02/2019: Fully Supervised Speaker Diarization accepted to ICASSP 2019.
• 12/2018: Neural Logic Machines accepted to ICLR 2019.
• 11/2018: Invited talk at University of Washington, Seattle.
• 10/2018: Fully Supervised Speaker Diarization submitted to Arxiv, perhaps the first supervised method doing so!
• 08/2018: Subgoal Discovery for Hierarchical Dialogue Policy Learning to appear at EMNLP (oral presentation), 2018.
• 06/2018: Invited talk at machine learning thoery workshop, Peking University, Beijing, China.
• 03/2018: Invited talk at Caltech, Pasadena, CA.
• 02/2018: Thoracic Disease Identification and Localization with Limited Supervision to appear at CVPR, 2018.
• 01/2018: Towards Neural Phrase-based Machine Translation to appear at ICLR, 2018. (code)
• 01/2018: A General Method for Robust Bayesian Modeling to appear at Journal of Bayesian Analysis.
• 09/2017: Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes to appear at NIPS, 2017.

Fun stuff:

• Stories written by my daughter Amy on Wattpad.