I am a postdoctoral fellow at the Eric and Wendy Schmidt Center at the Broad Institute. I completed my PhD in Computer Science at Princeton University, where I was very fortunate to be advised by Ben Raphael and generously 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 problems in biology, with a particular interest in problems involving spatial or network structure.
Here is my CV and Google Scholar.
Recent Updates
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(September 2024) Selected as a Rising Star in Data Science and will attend the workshop at UC San Diego in November.
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(July 2024) New pre-print on measuring higher-order epistasis.
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(June 2024) GASTON, our deep learning model for learning spatial gradients from sparse spatial transcriptomics data, was accepted to Nature Methods.
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(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.
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(March 2024) Copulacci, our method for learning cell-cell interactions from sparse spatial transcriptomics data, was accepted to ISMB 2024.
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(March 2024) I defended my PhD thesis! Slides available here. Next up: I will join the Eric and Wendy Schmidt Center at the Broad Institute as a postdoctoral fellow.
Papers
* denotes joint first authorship.
GASTON-Mix: a unified model of spatial gradients and domains using spatial mixture-of-experts.
Uthsav Chitra, Shu Dan, Fenna Krienen, Benjamin J. Raphael
In submission.
Mapping the topography of spatial gene expression with interpretable deep learning.
Uthsav Chitra, Brian J. Arnold, Hirak Sarkar, Cong Ma, Sereno Lopez-Darwin, Kohei Sanno, Benjamin J. Raphael
Nature Methods, in press. Previously appeared at RECOMB 2024 [slides].
Quantifying higher-order epistasis: beware the chimera.
Uthsav Chitra*, Brian J. Arnold*, Benjamin J. Raphael
In review.
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.
A latent variable model for evaluating mutual exclusivity between driver mutations in cancer.
Ahmed Shuaibi*, Uthsav Chitra*, Benjamin J. Raphael
RECOMB Satellite Workshop on Computational Cancer Biology (RECOMB-CCB 2024).
Best Paper Award.
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 [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) [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 [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 [slides].
Random Walks on Hypergraphs with Edge-Dependent Vertex Weights.
Uthsav Chitra, Benjamin J. Raphael
International Conference on Machine Learning (ICML 2019) [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, attempt to do crosswords, and make bad puns.