publications
Publications in reverse chronological order. * indicates equal contribution or co-first authorship.
2026
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Data-Hugging Shields Proprietary AI Models from Research That Could Disprove Themnpj Artificial Intelligence, 2026 -
ProtoCDisco: Unsupervised Concept Discovery Using Foundation Model RepresentationsManuscript in submission, 2026 -
Cosine Similarity Is Almost All You Need (for Prototypical-Part Models)In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, Mar 2026
2025
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It’s LIT! LLMs with Interpretable ToolsIn Multi-Turn Interactions in Large Language Models Workshop (MTI-LLM Workshop, NeurIPS), Mar 2025 -
"What is Different Between These Datasets?" A Framework for Explaining Data Distribution ShiftsJournal of Machine Learning Research, Mar 2025 -
Rashomon sets for prototypical-part networks: Editing interpretable models in real-timeIn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Jun 2025 -
Improving Atrial Fibrillation Detection Using a Shared Latent Space for ECG and PPG SignalsHarvard Data Science Review, Jun 2025
2024
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Improving Clinician Performance in Classifying EEG Patterns on the Ictal–Interictal Injury Continuum Using Interpretable Machine LearningNEJM AI, Jun 2024 -
Learning From Alarms: A Robust Learning Approach for Accurate Photoplethysmography-Based Atrial Fibrillation Detection using Eight Million Samples Labeled with Imprecise Arrhythmia AlarmsIEEE Journal of Biomedical and Health Informatics, Jun 2024 -
Sparse learned kernels for interpretable and efficient medical time series processingNature Machine Intelligence, Jun 2024 -
SiamQuality: a ConvNet-based foundation model for photoplethysmography signalsPhysiological Measurement, Jun 2024 -
Integrated Single-cell Multiomic Analysis of HIV Latency Reversal Reveals Novel Regulators of Viral ReactivationGenomics, Proteomics & Bioinformatics, Jun 2024 -
This Looks Better than That: Better Interpretable Models with ProtoPNeXtarXiv preprint arXiv:2406.14675, Jun 2024
2023
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Reconsideration on Evaluation of Machine Learning Models in Continuous Monitoring Using WearablesarXiv preprint arXiv:2312.02300, Jun 2023
2021
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A supervised machine learning semantic segmentation approach for detecting artifacts in plethysmography signals from wearablesPhysiological Measurement, Jun 2021
