Bruce (Zhi) Wen

Senior applied research scientist at Mila - Quebec AI Institute

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I work in the applied research team at Mila, where we solve real-world problems with deep learning. For examples, I worked with Dialogue on automatic symptoms detection, and with D-BOX on movie events detection.

These days I am most interested in certain topics in NLP, including decoding algorithms, controllable generation, evaluation, retrieval, and interpretability. I also keep an eye on healthcare/bio applications, such as protein design.

I earned my master degree at McGill University, and I did my undergrad at Wuhan University, China. My research focused on machine learning and NLP for healthcare. For instance, I worked on COVID-19 media news surveillance for public health measures, constructing a large medical NLP pre-training dataset, among others.

I have eclectic taste in music, but what I listen to mostly clusters around: Pink Floyd-ish sounds, post-rock, Thai alternative, and ’60s–’80s Japanese music. I used to play a lot of football and I keep procrasticating on picking it back up, meanwhile I’ve recently gotten into climbing.

selected publications

  1. NeurIPS
    Towards Trustworthy Automatic Diagnosis Systems by Emulating Doctors’ Reasoning with Deep Reinforcement Learning
    Arsene Fansi Tchango, Rishab Goel, Julien Martel, and 3 more authors
    Thirty-sixth Conference on Neural Information Processing Systems, 2022
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  2. NeurIPS Dataset
    DDXPlus: A new Dataset for Medical Automatic Diagnosis
    Arsene Fansi Tchango, Rishab Goel, Zhi Wen, and 2 more authors
    Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track, 2022
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  3. Patterns
    Inferring global-scale temporal latent topics from news reports to predict public health interventions for COVID-19
    Zhi Wen, Guido Powell, Imane Chafi, and 2 more authors
    Patterns, 2022
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  4. EMNLP Workshop
    MeDAL: Medical Abbreviation Disambiguation Dataset for Natural Language Understanding Pretraining
    Zhi Wen, Xing Han Lu, and Siva Reddy
    In Proceedings of the 3rd Clinical Natural Language Processing Workshop, 2020
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  5. Nat. Commun.
    Inferring multimodal latent topics from electronic health records
    Yue Li, Pratheeksha Nair, Xing Han Lu, and 8 more authors
    Nature communications, 2020
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