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Uthsav Chitra Profile
Uthsav Chitra

@uthsavc

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Incoming Assistant Professor @JHUCompSci | Postdoc @Schmidt_Center @broadinstitute | PhD @PrincetonCS | computational biology + ML

Cambridge, MA
Joined September 2018
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@uthsavc
Uthsav Chitra
1 month
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).
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@uthsavc
Uthsav Chitra
6 days
Congrats to @gillianychu et al!!.
@gillianychu
Gillian
7 days
The culmination of several PhD years — today LAML is published! LAML infers max likelihood time-resolved cell lineage trees from dynamic lineage tracing data accurately and efficiently. Thanks to @benjraphael for his guidance!
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@uthsavc
Uthsav Chitra
1 month
I am so deeply grateful for the support of many mentors and role models throughout the application process — there are too many to tag here, but thank you all 🙏 . (Also grateful for the @HDSIUCSD Rising Stars in Data Science workshop which pushed me to apply this cycle!).
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@uthsavc
Uthsav Chitra
1 month
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!
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@uthsavc
Uthsav Chitra
1 month
RT @joshuasweitz: The White House Vision for Dismantling Science in One Simple Plot .
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@uthsavc
Uthsav Chitra
2 months
RT @Schmidt_Center: 🎉Congrats!.🥇@uthsavc: Mapping the topography of spatial gene expression with interpretable deep learning.🥈Anurendra Kum….
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@uthsavc
Uthsav Chitra
2 months
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@uthsavc
Uthsav Chitra
2 months
RT @sebacultrera: Excited to share our latest preprint, introducing the hierarchical cross-entropy (HCE) loss — a simple change that consis….
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@uthsavc
Uthsav Chitra
3 months
RT @rohitsingh8080: I met @uthsavc at RECOMB '22. We got lunch and talked science. His GASTON work (RECOMB '24), with its isodepth, was th….
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@uthsavc
Uthsav Chitra
3 months
RT @rohitsingh8080: At RECOMB-Seq, I will be presenting GLACIER, with @uthsavc and my trainees Prannav and @hliang74 , where we introduce S….
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@uthsavc
Uthsav Chitra
4 months
RT @fabian_theis: 2/ Here, wanted to highlight interesting approach from Bonnie Berger’s lab @MIT, velorama @CellSystemsCP. It goes the oth….
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@uthsavc
Uthsav Chitra
5 months
RT @Schmidt_Center: Congratulations to @Schmidt_Center postdoc @uthsavc and team on their preprint, which introduces GASTON-Mix, an unsuper….
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@uthsavc
Uthsav Chitra
5 months
RT @henrismitch: 🚀 introducing fastppm: turbocharging tumor phylogeny reconstruction from bulk DNA-seq! we develop a new technique, tree-st….
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@uthsavc
Uthsav Chitra
6 months
@benjraphael @henrismitch informed me that the NCI workshop where we developed these ideas is now canceled thanks to the @realDonaldTrump @elonmusk NIH freeze 🙁.
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@uthsavc
Uthsav Chitra
6 months
Finally, if you've gotten this far: this work builds on our earlier work with @Cong992 using *complex analysis* (conformal mapping) to model spatial gradients. Check it out!.
@benjraphael
Ben Raphael
3 years
Spatial transcriptomics meets complex analysis – our new method Belayer models spatial gene expression in layered tissues, now published in @CellSystemsCP. Work led by @Cong992 and @uthsavc with Shirley Zhang. 1/6
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@uthsavc
Uthsav Chitra
6 months
Check out the paper for more details and neat biological applications! For example, modeling spatial gradients → much more accurate SVG identification. Thanks to great collaborators @BrianJohnArnold @koheisanno @hrksrkr @Cong992 Sereno @benjraphael 🙂
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@uthsavc
Uthsav Chitra
6 months
GASTON algorithm is quite natural: parametrize functions h,d with neural nets and learn from data. Fun back-story: @benjraphael and I derived most of this model at the bar near an NCI workshop 🥂😅
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@uthsavc
Uthsav Chitra
6 months
Model implicitly accounts for sparsity by “pooling” measurements across locations (x,y) with equal isodepth d(x,y). These locations look like contours of equal height on an elevation map, hence the “topographic map” analogy.
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@uthsavc
Uthsav Chitra
6 months
We prove that f(x,y) = h(d(x,y)), i.e. gene expression f(x,y) is function of a *single* spatial coordinate d(x,y) rather than 2 spatial coordinates x,y. Spatial dimensionality reduction! 🚀.We call d(x,y) the "isodepth"; it characterizes spatial gradients ▽f_g.
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@uthsavc
Uthsav Chitra
6 months
We make two assumptions:.(1) genes have *shared* gradient directions, i.e. each gradient ▽f_g(x,y) is proportional to shared vector field v(x,y).(Equivalent to Jacobian of f being rank-1 everywhere). (2) vector field v has no “curl”, so v=▽d is gradient of "spatial potential" d
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