About me

I am a Masters Student in Computer Science (Artificial Intelligence) at Mila and University of Montreal under the supervision of Professor Bang Liu and Professor Quoc Nguyen. My current interest centers around the intersection of machine learning and healthcare with a focus on aligning and interpreting LLMs using medical decision concepts. My other research interests revolves around Representation Learning, Mechanistic Interpretability, LLM Representation Engineering and AI4Science.

Outside of academics, I am also a Data Scientist at Intact Insurance working in the DataLab in the Commercial Line Modeling team. I also hold the position of President of the UdeM AI student club where we organize events and workshops for students to learn more about AI and ML. In my freetime, I enjoy sports such as badminton, tennis and recently got into pickleball.

What i'm doing

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    Deep Learning

    Research and development of deep learning algorithms for various applications.

  • LLM

    Research and analysis of LLMs in various contexts and applications.

  • data science icon

    Data Science

    Leverage machine learning for business applications and data analysis.

  • TA icon

    Teaching Assistant

    Assist in teaching the Representation Learning course at Mila.

Daniel lewis
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Daniel lewis

Resume (Download My CV)

Education

  1. Mila - University of Montreal

    2023 — 2025

    Masters in Computer Science (Artificial Intelligence) under the supervision of Prof. Bang Liu and Prof. Quoc Nguyen. Research at the intersection of machine learning and healthcare.

  2. University of Montreal

    2020 - 2023

    Bachelor of Science in Computer Science and Mathematics with a specialization in Data Science. President of the UdeM AI student club.

Publications and Research Works

  1. M. Mitchell et al. “SHADES: Towards a Multilingual Assessment of Stereotypes in Large Language Models”, NAACL 2025

  2. J. Qin, B. Liu and Q. Nguyen “Enhancing Healthcare LLM Trust with Atypical Presentations Recalibration”, EMNLP 2024 Findings https://aclanthology.org/2024.findings-emnlp.142/

  3. L. Cherif, E. Meriaux*, J. Qin*, V. Patel, M. Klissarov, D. Precup, and K. Khetarpal “Leveraging Affordances for Reinforcement Learning in Large Discrete Action Spaces,” In Women in Machine Learning (WiML) Symposium at ICML 2024

  4. Research Collaboration with Samsung on LLM for Material Discovery

Teaching and Work Experience

  1. Teaching Assistant for Representation Learning @ Mila

    2024 Autumn

    Assist in teaching, grading and preparing course materials for the Representation Learning course at Mila with Prof. Aishwarya Agrawal.

  2. Teaching Assistant for Machine Learning @ Polytechnique de Montreal

    2024 Autumn

    Assist in teaching, grading and preparing course materials for the Machine Learning course at Polytechnique with Prof. Sarath Chandar.

  3. Teaching Assistant for Representation Learning @ Mila

    2024 Winter

    Assist in teaching, grading and preparing course materials for the Representation Learning course at Mila with Prof. Aaron Courville.

  4. Data Scientist @ Intact

    2023 — Present

    Extract, analyze and model Commercial Lines insurance data to improve pricing. Leverage machine learning to improve business value of products.

Resume