Uthsav Chitra

I am a postdoctoral fellow at the Eric and Wendy Schmidt Center at the Broad Institute of MIT and Harvard.

I completed my PhD in Computer Science at Princeton University. I was very fortunate to be advised by Ben Raphael and supported by an NSF Graduate Research Fellowship and a Siebel Scholar award.

I am broadly interested in developing statistical and machine learning methods to address fundamental problems in biology, with a particular focus on problems involving graphs or spatial structure.

Here is my CV, Google Scholar, and my research statement (minus the “future work” section).

In Fall 2025, I will be starting as an Assistant Professor in the Department of Computer Science at Johns Hopkins University. I am hiring motivated students and postdocs; please contact me if you are interested in working with me!

Recent Updates

(March 2025) Two papers (GASTON-Mix, and SARDINE by Gary Hu) accepted to ISMB 2025.
(March 2025) GLACIER, a method for spatial Granger causality (with Prannav Shankar, Huan Liang, Rohit Singh) was accepted to RECOMB-seq 2025. Pre-print coming soon!
(February 2025) Our paper on measuring higher-order epistasis was published in Nature Communications.
(January 2025) GASTON, an interpretable deep learning model for learning spatial gradients from sparse spatial gene expression data, was published in Nature Methods.
(November 2024) Selected as a Rising Star in Data Science and attended the workshop at UC San Diego.
(May 2024) DIALECT, our method to identify mutually exclusive driver mutations that accounts for passenger mutations, was accepted to and won the Best Paper Award at RECOMB-CCB 2024.

Papers

^{* denotes joint first authorship

† denotes joint last (senior) authorship}

Spatial metabolic gradients in the liver and small intestine.
Laith Samarah, Clover Zheng, …, Uthsav Chitra, …, Benjamin J. Raphael, Joshua Rabinowitz.
In review.

Decoding the causal drivers of spatial cellular topology.
Prannav Shankar, Huan Liang, Uthsav Chitra†, Rohit Singh†.
RECOMB Satellite Conference on Biological Sequence Analysis (RECOMB-seq 2025).

Anomaly Detection in Spatial Transcriptomics via Spatially Localized Density Comparison.
Gary Hu, Julian Gold, Uthsav Chitra, Sunay Joshi, Benjamin J. Raphael.
Accepted to ISMB 2025.

GASTON-Mix: a unified model of spatial gradients and domains using spatial mixture-of-experts.
Uthsav Chitra, Shu Dan, Fenna Krienen, Benjamin J. Raphael
Accepted to ISMB 2025.

A latent variable model for evaluating mutual exclusivity between driver mutations in cancer.
Ahmed Shuaibi*, Uthsav Chitra*, Benjamin J. Raphael
In preparation.
Best Paper Award at RECOMB Satellite Workshop on Computational Cancer Biology (RECOMB-CCB 2024).

Mapping the topography of spatial gene expression with interpretable deep learning.
Uthsav Chitra, Brian J. Arnold, Hirak Sarkar, Kohei Sanno, Cong Ma, Sereno Lopez-Darwin, Benjamin J. Raphael
Nature Methods (2025). Accepted to RECOMB 2024 [RECOMB slides, MIA lightning talk].

Resolving discrepancies between chimeric and multiplicative measures of higher-order epistasis.
Uthsav Chitra*, Brian J. Arnold*, Benjamin J. Raphael
Nature Communications (2025).

A count-based model for delineating cell-cell interactions in spatial transcriptomics data.
Hirak Sarkar*, Uthsav Chitra*, Julian Gold, Benjamin J. Raphael
Bioinformatics (2024). Accepted to ISMB 2024.

Belayer: Modeling discrete and continuous spatial variation in gene expression from spatially resolved transcriptomics.
Cong Ma*, Uthsav Chitra*, Shirley Zhang, Benjamin J. Raphael
Cell Systems (2022). Accepted to RECOMB 2022.

NetMix2: Unifying network propagation and altered subnetworks.
Uthsav Chitra*, Tae Yoon Park*, Benjamin J. Raphael
Journal of Computational Biology (2022). Accepted to RECOMB 2022 [RECOMB slides].

Quantifying and Reducing Bias in Maximum Likelihood Estimation of Structured Anomalies
Uthsav Chitra, Kimberly Ding, Jasper C. H. Lee, Benjamin J. Raphael
International Conference on Machine Learning (ICML 2021) [ICML slides, ICML talk].

NetMix: A network-structured mixture model for reducing bias in the identification of altered subnetworks.
Matthew A. Reyna*, Uthsav Chitra*, Rebecca Elyanow, Benjamin J. Raphael
Journal of Computational Biology (2021). Accepted to RECOMB 2020 [RECOMB slides].

Analyzing the Impact of Filter Bubbles on Social Network Polarization.
Uthsav Chitra, Christopher Musco
ACM Conference on Web Search and Data Mining (WSDM 2020).
Preliminary version presented at KDD WISDOM 2019 workshop [KDD slides].

Random Walks on Hypergraphs with Edge-Dependent Vertex Weights.
Uthsav Chitra, Benjamin J. Raphael
International Conference on Machine Learning (ICML 2019) [ICML slides, ICML talk @ 55:27].

Committee Selection is More Similar Than You Think: Evidence from Avalanche and Stellar.
Tarun Chitra, Uthsav Chitra
Manuscript, 2019.

Personal

I like to go bouldering in my free time.