Teddy Koker

I am a first-year PhD student at MIT EECS, advised by Professor Tess Smidt.

Previously, I have worked at MIT Lincoln Laboratory, 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 computational sciences. My most recent work focuses on deep learning within the field of computational chemistry and materials science.

Higher-Order Equivariant Neural Networks for Charge Density Prediction in Materials
Teddy Koker, Keegan Quigley, Eric Taw, Kevin Tibbetts, Lin Li.
npj Computational Materials, 2024. Also at NeurIPS AI for Science Workshop, 2023.
Publication / arXiv / Code

UniTS: Building a Unified Time Series Model
Shanghua Gao, Teddy Koker, Owen Queen, Thomas Hartvigsen, Theodoros Tsiligkaridis, Marinka Zitnik.
NeurIPS, 2024.
arXiv / Code / Website

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, Lin Li.
NeurIPS AI for Accelerated Materials Design Workshop, 2022.
arXiv

AAVAE: Augmentation-Augmented Variational Autoencoders.
William Falcon, Ananya Harsh Jha, Teddy Koker, 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, 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, Dimitrios Koutmos.
Journal of Risk and Financial Management, 2020.
Publication