Jan-Christian Hütter
About
I develop methods for the analysis of omics data, in particular in the context of large-scale high-content perturbation screens. These screens enable mapping out functional properties of genes and gene-regulatory networks at unprecedented scale. To draw conclusions from the associated data, I harness mathematical, statistical, and machine learning methods methods such as statistical optimal transport and differentiable causal discovery.
Currently, I am a Principal ML Scientist II in the Biology Research | AI Development (BRAID) department at Genentech. Before, I was a Postdoctoral Researcher in the Regev group at the Broad Institute (co-advised by Caroline Uhler in 2021) and obtained my PhD at MIT in 2019 under the supervision of Philippe Rigollet.
Publications
In articles without equal joint authorship, an asterisk (*) next to the name indicates that the author is co-first.Preprints
Muralikrishnna G Sethuraman, Romain Lopez, Rahul Mohan, Faramarz Fekri, Tommaso Biancalani, and Jan-Christian Hütter (corresponding)
arXiv Preprint arXiv:2301.01849, 2023
[Arxiv]
Michael Truell, Jan-Christian Hütter, Chandler Squires, Piotr Zwiernik, and Caroline Uhler
arXiv Preprint arXiv:2112.00816, 2021
[Arxiv]
Journal articles
Eran Hodis, Elena Torlai Triglia, John Y. H. Kwon, Tommaso Biancalani, Labib R. Zakka, Saurabh Parkar, Jan-Christian Hütter, Lorenzo Buffoni, Toni M. Delorey, Devan Phillips, Danielle Dionne, Lan T. Nguyen, Denis Schapiro, Zoltan Maliga, Connor A. Jacobson, Ayal Hendel, Orit Rozenblatt-Rosen, Martin C. Mihm, Levi A. Garraway, and Aviv Regev
Science 376, no. 6592 (April 2022): eabi8175
Yaara Oren, Michael Tsabar, Michael S Cuoco, Liat Amir-Zilberstein, Heidie F Cabanos, Jan-Christian Hütter, Bomiao Hu, Pratiksha I Thakore, Marcin Tabaka, Charles P Fulco, William Colgan, Brandon M Cuevas, Sara A Hurvitz, Dennis J Slamon, Amy Deik, Kerry A Pierce, Clary Clish, Aaron N Hata, Elma Zaganjor, Galit Lahav, Katerina Politi, Joan S Brugge, and Aviv Regev
Nature 596, no. 7873 (2021): 576–82
Jan-Christian Hütter and Philippe Rigollet
The Annals of Statistics 49, no. 2 (2021): 1166–94
[Arxiv]
Piotr Bielecki (co-first), Samantha J. Riesenfeld (co-first), Jan-Christian Hütter (co-first), Elena Torlai Triglia (co-first), Monika S. Kowalczyk, Roberto R. Ricardo-Gonzalez, Mi Lian, Maria C. Amezcua Vesely, Lina Kroehling, Hao Xu, Michal Slyper, Christoph Muus, Leif S. Ludwig, Elena Christian, Liming Tao, Amanda J. Kedaigle, Holly R. Steach, Autumn G. York, Mathias H. Skadow, Parastou Yaghoubi, Danielle Dionne, Abigail Jarret, Heather M. McGee, Caroline B. M. Porter, Paula Licona-Limón, Will Bailis, Ruaidhrí Jackson, Nicola Gagliani, Georg Gasteiger, Richard M. Locksley, Aviv Regev, and Richard A. Flavell
Nature 592, no. 7852 (April 2021): 128–32
Jan-Christian Hütter, Cheng Mao, Philippe Rigollet, and Elina Robeva
Electronic Journal of Statistics 14, no. 2 (2020): 2600–2652
[Arxiv]
Jan-Christian Hütter, Cheng Mao, Philippe Rigollet, and Elina Robeva
Bernoulli 26, no. 4 (2020): 3051–80
[Arxiv]
Massimo Fornasier and Jan-Christian Hütter
Journal of Fourier Analysis and Applications 22, no. 3 (2016): 694–749
[Arxiv]
Marco Di Francesco, Massimo Fornasier, Jan-Christian Hütter, and Daniel Matthes
SIAM Journal on Mathematical Analysis 46, no. 6 (2014): 3814–37
[Arxiv]
Conference articles
Ethan Weinberger, Romain Lopez, Jan-Christian Hütter, and Aviv Regev
In Machine Learning in Computational Biology, 16–32. PMLR, 2022
Romain Lopez, Jan-Christian Hütter, Jonathan Pritchard, and Aviv Regev
In NeurIPS, 2022
[Arxiv]
Safiye Celik, Jan-Christian Hütter, Sandra Melo, Nathan Lazar, Rahul Mohan, Conor Tillinghast, Tommaso Biancalani, Marta Fay, Berton Earnshaw, and Imran S Haque
In NeurIPS 2022 Workshop on Learning Meaningful Representations of Life, 2022
Jan-Christian Hütter and Philippe Rigollet
In Conference on Uncertainty in Artificial Intelligence (UAI), 1169–78. PMLR, 2020
[Arxiv]
Aden Forrow, Jan-Christian Hütter, Mor Nitzan, Philippe Rigollet, Geoffrey Schiebinger, and Jonathan Weed
In The 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 2454–65. Proceedings of Machine Learning Research, 2019
[Arxiv]
Jan-Christian Hütter and Philippe Rigollet
In Conference on Learning Theory (COLT), 1115–46, 2016
[Arxiv]
Teaching
Past teaching
- Spring 2018: Teaching Assistant for Fundamentals of Statistics online class on edx (recitation videos and quizes)
- Notes on adaptive estimation with Lepski's method, co-written with Cheng Mao
- Lecture notes on high-dimensional statistics, co-written with Philippe Rigollet