Teddy Koker

I am currently a machine learning researcher at MIT Lincoln Laboratory, where I am a member of the Artificial Intelligence Technology group.

Previously, I have worked at Lightning AI and Harvard Medical School.

Email / CV / Github / Google Scholar / Twitter

Research

I am broadly interested in machine learning and its applications to the sciences and medicine. My most recent work focuses on machine learning within the field of material science, as well as methods for domain adaptation and interpretability of time-series models.

Higher Order Equivariant Graph Neural Networks for Charge Density Prediction
Teddy Koker, Keegan Quigley, and Lin Li.
NeurIPS AI for Science Workshop, 2023.
PDF

Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency
Owen Queen, Thomas Hartvigsen, Teddy Koker, Huan He, Theodoros Tsiligkaridis, Marinka Zitnik
NeurIPS, 2023 (spotlight).
arXiv / Code / Website

Domain Adaptation for Time Series Under Feature and Label Shifts
Huan He, Owen Queen, Teddy Koker, Consuelo Cuevas, Theodoros Tsiligkaridis, Marinka Zitnik.
International Conference on Machine Learning (ICML), 2023.
arXiv / Code / Website

Graph Contrastive Learning for Materials
Teddy Koker, Keegan Quigley, Will Spaeth, Nathan C. Frey, and Lin Li.
NeurIPS AI for Accelerated Materials Design Workshop, 2022.
arXiv

AAVAE: Augmentation-Augmented Variational Autoencoders.
William Falcon, Ananya Harsh Jha, Teddy Koker, and Kyunghyun Cho.
Preprint.
arXiv / Code

TorchMetrics: Measuring Reproducibility in PyTorch
N. Detlefsen, J. Borovec, J. Schock, A. Jha, T. Koker, L. Liello, D. Stancl, C. Quan, M. Grechkin, W. Falcon.
The Journal of Open Source Software, 2022.
Publication / Code

U-Noise: Learnable Noise Masks for Interpretable Image Segmentation.
T. Koker, F. Mireshghallah, T. Titcombe, and G. Kaissis.
International Conference on Image Processing (ICIP), 2021.
Publication / arXiv / Code

On Identification and Retrieval of Near-Duplicate Biological Images: A New Dataset and Protocol.
T. Koker*, S.S. Chintapalli*, S. Wang, B.A. Talbot, D. Wainstock, M. Cicconet, M.C. Walsh.
International Conference on Pattern Recognition (ICPR), 2020.
Publication / PDF / Code

Cryptocurrency Trading Using Machine Learning.
Teddy Koker and Dimitrios Koutmos.
Journal of Risk and Financial Management, 2020.
Publication