Jordan T. Ash
ash.jordan -at- microsoft.com
I'm a senior researcher at Microsoft Research in New York City, where I mostly think about problems related to deep learning and sequential decision making. I earned my PhD from the computer science department at Princeton University and was advised by Ryan P. Adams.
An experimental design framework for label-efficient supervised finetuning of large language models
Gantavya Bhatt, Yifang Chen, Arnav M. Das, Jifan Zhang, Sang T. Truong, Stephen Mussmann, Yinglun Zhu, Jeffrey Bilmes, Simon S. Du, Kevin Jamieson, Jordan T. Ash and Robert D. Nowak. 2024.
Exposing attention glitches with flip-flop language modeling
Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy and Cyril Zhang. NeurIPS 2023 (short talk).
Transformers learn shortcuts to automata
Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy and Cyril Zhang. ICLR 2023 (talk).
Eigen memory trees
Mark Rucker, Jordan T. Ash, John Langford, Paul Mineiro and Ida Momennejad. 2022.
Understanding contrastive learning requires incorporating inductive biases
Nikunj Saunshi, Jordan T. Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham Kakade and Akshay Krishnamurthy. ICML 2022 (short talk).
Investigating the role of negatives in contrastive representation learning
Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy and Dipendra Misra. AISTATS 2022.
Joint analysis of gene expression levels and histological images identifies genes associated with tissue morphology
Jordan T. Ash, Gregory Darnell, Daniel Munro and Barbara E. Engelhardt. Nature Communications 2021.
paper / code
A data-driven computational scheme for the nonlinear mechanical properties of cellular mechanical metamaterials under large deformation
Tianju Xue, Alex Beatson, Maurizio Chiaramonte, Geoffrey Roeder, Jordan T. Ash, Yigit Menguc, Sigrid Adriaenssens, Ryan P. Adams and Sheng Mao. Soft Matter 2020.
End-to-end training of deep probabilistic CCA for joint modeling of paired biomedical observations
Gregory Gundersen, Bianca Dumitrascu, Jordan T. Ash and Barbara E. Engelhardt. UAI 2019.
paper / code
Unsupervised domain adaptation using approximate label matching
Jordan T. Ash, Rob Schapire and Barbara E. Engelhardt. ICML workshop on implicit generative models 2017.
Automated particle picking for low-contrast macromolecules in cryo-electron microscopy
Robert Langlois, Jesper Pallesen, Jordan T. Ash, Danny Nam Ho, John L. Rubinstein and Joachim Frank. Journal of structural biology 2014.
paper / code
Fully automated particle selection and verification in single-particle cryo-EM
Robert Langlois, Jordan T. Ash, Jesper Pallesen and Joachim Frank. Computational Methods for Three-Dimensional Microscopy Reconstruction, Springer 2014.