Nhi Le

Nhi Le

Machine Learning Engineer & Researcher

Hi, I’m Nhi 👋

I am a passionate Machine Learning Engineer & Researcher with nearly 2 years of experience deploying various large-scale AI/ML applications, mainly in the areas of RecSys & NLP, for millions of users.

My research interests include graph machine learning, agentic AI, multimodal learning (and potentially more as I explore).

I completed my M.S. in Computer Science at Brandeis University (Massachusetts, US), where I was part of the MINDS Lab (Machine Intelligence and Data Science Lab), under the supervision of Professor Chuxu Zhang. Before joining Brandeis, I received my B.S. from Monash University (Melbourne, Australia), where I worked as an undergraduate research assistant under Professor Buser Say.

Experience At A Glance

  • May 2025 - Present: Machine Learning Engineer - Adobe - San Jose, CA

  • Jun 2024 - Feb 2025: Graduate Research Assistant - MINDS Lab, supervised by Professor Chuxu Zhang

  • May 2024 - Aug 2024: Machine Learning Engineer Intern - Adobe - San Jose, CA

  • Feb 2022 - Jul 2023: Data Scientist - Telstra - Melbourne, Australia

  • Jul 2021 - Feb 2022: Undergraduate Research Assistant - Monash University, supervised by Professor Buser Say

  • Nov 2020 - Feb 2021: Data Science Intern - Telstra - Melbourne, Australia

Education

  • Aug 2023 - May 2025: M.S. Computer Science - Brandeis University

    • Recipient of a $40,000 Merit Scholarship from the Michtom School of Computer Science.

  • Feb 2019 - Dec 2021: B.S. Actuarial Science - Monash University

    • Department of Econometrics & Statistics 2020 Student Prize.

    • Top 5% of 15,000 graduates in 2021.

Publications

  • [ACL’25] NGQA: A Nutritional Graph Question Answering Benchmark for Personalized Health-aware Nutritional Reasoning. [paper] [code]

    Zheyuan Zhang*, Yiyang Li*, Nhi Ha Lan Le*, Zehong Wang, Tianyi Ma, Vincent Galassi, Keerthiram Murugesan, Nuno Moniz, Werner Geyer, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye.

  • [KDD’25] MOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation. [paper] [code]

    Zheyuan Zhang, Zehong Wang, Tianyi Ma, Varun Sameer Taneja, Sofia Nelson, Nhi Ha Lan Le, Keerthiram Murugesan, Mingxuan Ju, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye.

  • [IEEE SSCI’22] Training Experimentally Robust and Interpretable Binarized Regression Models Using Mixed-Integer Programming. [paper] [code]

    Sanjana Tule, Nhi Ha Lan Le, Buser Say.

(* indicates equal contribution)

Teaching

  • COSI 104A: Introduction to Machine Learning (Brandeis University)
  • COSI 10A: Introduction to Problem Solving in Python (Brandeis University)