Max Torop
![headshot.png](/assets/img/headshot.png)
I am a PhD candidate in Prof. Jennifer Dy’s Machine Learning (ML) Lab at Northeastern University. I’m broadly interested in interpretable ML, self-supervised learning and out-of-distribution detection. I also collaborate with scientists at MSKCC, developing applications of ML to dermatology. I was a research intern at Apple during the summer of 2024, focusing on data valuation methods for large-language-models.
Before coming to Northeastern I did my Masters in CS at WUSTL, where I was a member of Prof. Ulugbek Kamilov’s Computational Imaging Group (CIG). At CIG I collaborated with Prof. Dmitriy Yablonskiy (Radiology), developing deep learning methods for MRI processing. I recieved a B.S. in Data Science from the University of Rochester in 2018.
Outside of research I love to watch anime and read. Some favorites are One Piece, Fullmetal Alchemist, Dororo, One Hundred Years of Solitude, The Stormlight Archive, Jonathan Strange and Mr. Norrell and East of Eden.
News
Sep 3, 2024 | I will be giving a talk on our work SmoothHess to Prof. Doshi-Velez’s lab at Harvard, on 10/24/24. |
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Apr 22, 2024 | I’ll be joining Apple as an ML Research Intern this Summer! |
Jan 19, 2024 | Our work Boundary-Aware Uncertainty for Feature Attribution Explainers was accepted to AISTATS 2024! |
Sep 22, 2023 | Our work SmoothHess: ReLU Network Feature Interactions via Stein’s Lemma was accepted to NeurIPS 2023! |
May 13, 2022 | Our work using contrastive learning for spirometry accepted to ATS 2022 as an oral presentation. |