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StevenYuan666/README.md

Hi there! 嘿大家好! Salut!

👋 This is Steven.

💬 English, Mandarin(中文), French(français) are all acceptable for me.

🔭 I’m a Third-Year Ph.D. candidate in Computer Science at McGill University and Quebec AI Institute-Mila.

🧑‍🏫 It's fortunate to be supervised by Professor Xue (Steve) Liu.

📅 It's fortunate to have Professor Adriana Romero Soriano and Professor Gintare Karolina Dziugaite as my supervision committee member.

🔭 I obtained my Bachelor of Science Degree in Honorous Computer Science at McGill University.

🧐 What truly captivates me is the potential of intelligent systems and generative modelling to assist humans. How can artificial intelligence accurately and flawlessly complete tasks assigned by humans? How can generative models be applied for specific tasks? How do generative models mitigates the issues suffered by predominately used traditional approaches? More specifically, my research is concentrated on score-based generative algorithms and large language models with their applications in (i) addressing the Offline Black Box Optimization challenges, (ii) alleviating the challenges of knowledge-centric NLP tasks, developing a foundational knowledge model, enabling the automatic knowledge base construction, (iii) improve the efficiency and efficacy of AI systems for real-world applications.

💪 My greatest assets are my eagerness to learn new things, my curiosity to delve into uncharted territories, my drive to stay abreast of the latest developments, and my persistence to work hard.

🏭 Beyond academia, I collaborate closely with Microsoft Research, Samsung Research America, RBC Borealis and Noah’s Ark Lab Canada.

📑 See my publications at Google Scholar.

📧 If you have any questions about my projects or have cooperation intentions with me, feel free to contact me via email: ye.yuan3 AT mail DOT mcgill DOT ca

💰 I'm seeking research opportunities or internships. Feel free to contact me as well.

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  1. mila-iqia/Importance-aware-Co-teaching mila-iqia/Importance-aware-Co-teaching Public

    [NeurIPS 2023] Official Implementation of Importance-aware Co-teaching for Offline Model-based Optimization 🧬 🤖

    Python 6

  2. mila-iqia/Awesome-Offline-Model-Based-Optimization mila-iqia/Awesome-Offline-Model-Based-Optimization Public

    📰 Must-Read Papers on Offline Model-Based Optimization 🔥

    24

  3. mila-iqia/ParetoFlow mila-iqia/ParetoFlow Public

    [ICLR 2025] Official Implementation of ParetoFlow: Guided Flows in Multi-Objective Optimization🧬🧬🧬

    Python 19 1

  4. mila-iqia/Design-Editing-for-Offline-MBO mila-iqia/Design-Editing-for-Offline-MBO Public

    [TMLR 2025 & ICLR 2025 DeLTa] Official Implementation of Design Editing for Offline Model-based Optimization 🧬 🤖

    Python 10

  5. microsoft/Structured-Entity-Extraction microsoft/Structured-Entity-Extraction Public

    Code for the EMNLP'24 paper "Learning to Extract Structured Entities Using Language Models"

    Python 43 6

  6. Awesome-Diffusion-Models-for-NLP Awesome-Diffusion-Models-for-NLP Public

    📰 Must-read papers on Diffusion Models for Text Generation 🔥

    18 1