Enterprise ML grounded in fundamental research
I am a Sr. Machine Learning Scientist with Layer 6 AI at TD. On the applied side, I lead the development of credit risk ML models for TD, while in research I focus on Trustworthy AI and generative modelling.
Designing trustworthy machine learning models is crucial in highly regulated industries like banking and healthcare. My research group at Layer 6 AI is advancing TD’s capabilities in privacy, fairness, robustness, and explainability, both for predictive and generative AI.
My current interest in generative modeling is how to properly account for the implications of the manifold hypothesis - that high-dimensional natural data belong to low-dimensional manifolds. To accurately represent natural data, generative models should learn both manifold structure and the distribution of data on the manifold. My work with our group at Layer 6 AI is aimed at developing rigorous techniques that solve foundational problems in generative modeling.
News:
- Oct. 2024 - With NeurIPS workshop decisions out, I had four papers accepted to the TRL, FITML, ATTRIB, and SSL workshops.
- Sept. 2024 - We had our paper on estimating local intrinsic dimension selected for a Spotlight at NeurIPS 2024
- Aug. 2024 - I’ll be an Area Chair for next year’s ICLR 2025 in Singapore
- July 2024 - This month two papers were accepted to TMLR, first my collaborative work with Vector Institute researchers, and second a comprehensive survey of deep generative modelling through the lens of the manifold hypothesis.
- June 2024 - I had eight workshop papers accepted at ICML with a couple of them as Oral (*) presentations. SPIGM*, DAE*, GRaM x2, HAS, NGAIS, AI4Science, FMWild.
- May 2024 - Two papers accepted to ICML 2024, one on conformal prediction and another that solves the longstanding paradox around OOD detection with deep generative models.
- Apr. 2024 - I’ll be serving as an Area Chair for NeurIPS 2024
- Mar. 2024 - We had a paper selected for a Highlight at CVPR 2024, and two posters accepted to the ICLR workshops BGPT and GenAI4DM
- Feb. 2024 - At TD Bank’s annual patent awards I was nominated for both Inventor of the Year, and Invention of the year, while crossing the half-century mark for patents filed
- Jan. 2024 - Another Poster accepted to ICLR 2024, which also had an Oral at the NeurIPS Table Representation Workshop
- Dec. 2023 - I’m happy to say that our paper on topology-aware learning is published in TMLR
- Dec. 2023 - I was named a Top Reviewer at NeurIPS 2023. I’ll also be reviewing for ICML 2024
- Sept. 2023 - One Poster accepted at NeurIPS, a massive project with 10 authors from Layer 6 AI
- May 2023 - Nature Communications has published my paper on decentralized federated learning with differential privacy guarantees
- Jan. 2023 - We had two papers accepted at ICLR 2023 including one Spotlight (notable top 25%) and a Poster
- Oct. 2022 - Five papers submitted to various NeurIPS workshops were all accepted this year, one with an oral and another spotlight. AFCP, ICBINB, FL, ML4PS, NeurReps
- Sept. 2022 - I’ll be serving as a Program Chair for the federated learning workshop at this year’s NeurIPS
- June 2022 - Two papers accepted to the ICML workshops TAG-ML and TPDP, headed to an in-person conference for the first time in years
- Feb. 2022 - Some joint work on privacy enhancing technologies with Graham Taylor’s lab was accepted in Nature Scientific Reports
- Aug. 2021 - We had a paper accepted at this year’s NeurIPS conference
- Jan. 2021 - Our paper on reinforcement learning was accepted to ICLR
- Sept. 2019 - Jumping full-time into ML, I joined Layer 6 AI, part of TD Bank, as a Machine Learning Scientist
- Aug. 2019 - I defended my thesis to complete my PhD in physics at UofT
- Nov. 2017 - I was very pleased to win a Vanier Canada Graduate Scholarship, Canada’s most competitive PhD level scholarship!