Xinwei
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Xinwei Shen

I am a postdoctoral fellow at the ETH AI Center and the Seminar for Statistics at ETH Zürich, mentored by Prof. Peter Bühlmann and Prof. Fanny Yang. Previously, I obtained my PhD in the Department of Mathematics at Hong Kong University of Science and Technology advised by Prof. Tong Zhang and Prof. Kani Chen. Prior to that, I obtained a Bachelor of Science degree from the Department of Statistics at Fudan University in 2018.

My research interests lie at the interface of statistics and machine learning with the goal of developing effective machine learning algorithms with theoretical guarantees. Currently, I am working on causal inference, disentanglement, and generative models (e.g., GANs).

Email  /  Google Scholar  /  Github  /  LinkedIn

Publications

Journal Publications:

  • Weakly Supervised Disentangled Generative Causal Representation Learning
    X. Shen, F. Liu, H. Dong, Q. Lian, Z. Chen, T. Zhang
    Journal of Machine Learning Research, vol. 23, pp. 1-55, 2022 | paper | code | slides

  • Surprise Sampling: Improving and Extending the Local Case-Control Sampling
    X. Shen, K. Chen, W. Yu
    Electron. J. Statist., vol. 15, pp. 2454-2482, 2021 | paper

  • In vivo single-cell lineage tracing in zebrafish using high-resolution infrared laser-mediated gene induction microscopy
    S. He, Y. Tian, S. Feng, Y. Wu, X. Shen, K. Chen, Y. He, et al.
    Elife, vol. 9, e52024, 2020 | paper

    Conference Publications:

  • Reframed GES with a Neural Conditional Dependence Measure
    X. Shen, S. Zhu, J. Zhang, S. Hu, Z. Chen
    UAI, 2022 | paper | code

  • TILGAN: Transformer-based Implicit Latent GAN for Diverse and Coherent Text Generation
    S. Diao*, X. Shen*, K. S. Shum, Y. Song, T. Zhang
    Findings of ACL, 2021 (*equal contribution) | paper | code

  • CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models
    M. Yang, F. Liu, Z. Chen, X. Shen, J. Hao, J. Wang
    CVPR, 2021 | paper | code

    Preprints:

  • Bidirectional Generative Modeling Using Adversarial Gradient Estimation
    X. Shen, T. Zhang, K. Chen
    paper | code

  • Asymptotic Statistical Analysis of f-divergence GAN
    X. Shen, K. Chen, T. Zhang
    Available upon request

  • To ArXiv or not to ArXiv: A Study Quantifying Pros and Cons of Posting Preprints
    C. Rastogi, I. Stelmakh, X. Shen, M. Meila, F. Echenique, S. Chawla, N. B Shah
    paper

    • Academic Services

  • Workflow Chair of ICML 2021

  • Reviewer of JMLR, Neural Computation, TNNLS, Machine Learning, UAI, NeurIPS

    • Industry Experience

  • Research Intern, Huawei Noah's Ark Lab, Hong Kong
    Topic: Causal Machine Learning
    Mentor: Jiji Zhang, Zhitang Chen
    July 2020 - Dec 2020

    • Teaching

    Teaching Assistant:

  • MATH 3424: Regression Analysis (Fall 2020, Spring 2021)

  • MATH 3423: Statistical Inference (Spring 2020)

  • MATH 1013: Calculus IB (Fall 2019)

  • MATH 4426: Survival Analysis (Spring 2019)

    • Awards

  • Postgraduate Studentship, 2018 - 2022

  • Best TA Teaching Award, 2019 - 2021

  • Excellent Graduate of Fudan University, 2018

  • China National Scholarship, 2016 - 2017

    • Other Activities

  • Member of HKUST & Fudan Table Tennis Team

  • Member of Fudan Chinese Orchestra

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