New life update! 🎆
🎓 This Fall, I will be joining the Department of Computer Science at Johns Hopkins University (@JHUCompSci) as an Assistant Professor, with an affiliation at the new Data Science and AI Institute (@HopkinsDSAI).
Five computer science graduate students have been named 2023 @SiebelScholars. The award recognizes academic achievement and leadership.
Congratulations! 🎉
bit.ly/3xGJyeU
I defended my thesis last week! It was super fun - I made lots of people listen to me talk about my work for a whole hour 😅
Huge thanks to advisor @benjraphael for his mentorship/support over the past decade 😃
Next up: I will join the Broad @Schmidt_Center as a postdoc!
GASTON, our method to learn “topographic maps” of gene expression, is out now @naturemethods!
IMO the coolest part is a new model of *spatial gradients in sparse data*.
As is typical for bio papers, it’s buried in Methods, but see below for a quick outline on the math 👇
Gene expression topography analysis by GASTON portrays domain organization and spatial gradients of gene expression and cell type composition using spatially resolved transcriptomics data. @uthsavc@benjraphael@PrincetonCSnature.com/articles/s4159…
Congratulations to the 2024 Rising Stars in Data Science, including our very own fellow @uthsavc! This week at @HDSIUCSD, Uthsav presented his work on algorithms for understanding the spatial and network organization of biological systems. Learn more: datascience.ucsd.edu/rising-stars-i…
What I’ve been working on for the past year! A new mathematical framework + deep learning algorithm, GASTON, for modeling spatial gradients in ‘omics data
(I’m also open to input for the next climbing-themed algorithm name 🧗 😀)
Our new method GASTON learns a “topographic map” of a tissue slice, enabling simultaneous identification of spatial domains and gene expression gradients in spatial transcriptomics biorxiv.org/content/10.110…
Led by @UthsavC w/ @BrianJohnArnold@hrksrkr@Cong992 Sereno + Kohei (1/7)
I learned last night that I received an NSF Graduate Research Fellowship! @NSFGRFP
While I am extremely excited about receiving the #GRFP, I am also feeling a bit introspective. A few thoughts:
Recently accepted to #ICML2021! Conference version (will update arXiv version soon) includes new result proving our estimator is asymptotically unbiased, thanks to help from new co-author Jasper Lee (who is Twitter-less)
New preprint on finding structured anomalous patterns in Gaussian data. (Also known as the “structured normal means” problem in statistics)
w/ Princeton undergrad (!) Kimberly Ding and advisor @benjraphaelarxiv.org/abs/2007.07878 (1/n)
Presenting at #ISMBECCB2025 tomorrow!
GASTON-Mix, a unified model of spatial gradients and domains in spatial 'omics data.
11:20am UK time at RegSys
Also recruiting students for my new lab at @JHUCompSci, feel free to reach out if you want to chat
The Chitra Lab will build the next generation of machine learning and AI algorithms for addressing fundamental problems in biology.
I am actively recruiting students — please visit our website for more details! chitra-lab.github.io
not to toot my own horn (although i totally am) but i was in the top 10% of all reviewers for #ICML2021 🙂
icml.cc/Conferences/20…
(no idea how this is chosen or what it means but i'll take it?)