Nine new tenure-track faculty join Johns Hopkins Computer Science
Their research spans social computing and human-computer interaction to the theoretical foundations and real-world applications of machine learning models.
The Department of Computer Science is pleased to welcome nine new tenure-track faculty to its ranks this academic year! Featuring @anandbhattad.bsky.social, @uthsav.bsky.social, @gligoric.bsky.social, @murat-kocaoglu.bsky.social, @tiziano.bsky.social, and more:
29.10.2025 13:43 β π 10 π 4 π¬ 0 π 1
10 new CS professors! π₯³
@anandbhattad.bsky.social @uthsav.bsky.social @gligoric.bsky.social @murat-kocaoglu.bsky.social @tiziano.bsky.social
08.10.2025 17:43 β π 9 π 6 π¬ 0 π 0
NSF just cancelled ALL grants to Harvard researchers. Thatβs right - physics, astronomy, bio, CAREER - ALL. Professors wonβt get paid. Postdocs wonβt get paid. PhD students wonβt get paid. This is insane!
If they can do this to Harvard, they can do this to your school.
16.05.2025 03:04 β π 562 π 231 π¬ 18 π 21
Wow. "NIH" canceled my co-mentored (with Dave Sulzer) PhD student's F31 funding. His work is on understanding the genetics and neuroscience of language learning disorders. F31 provides no indirect $ to Columbia, just pays his salary. Not that it should matter, but he's an American citizen. W.T.F.
11.03.2025 12:41 β π 521 π 221 π¬ 21 π 17
Computer Science Seminar Series. Tuning Our Algorithmic Amplifiers: Embedding Pro-Social Values Into Online Platforms. March 13, 2025, 228 Malone Hall. Refreshments available 10:30 a.m. Seminar begins 10:45 a.m. Tiziano Piccardi, Stanford University.
CS & BME Seminar Series: Machine Learning for Spatial and Network Biology. March 13, 2025, 12 p.m. 228 Malone Hall. Refreshments available at noon. Seminar begins 12:15 p.m. Uthsav Chitra, Eric and Wendy Schmidt Center at Broad Institute.
2β£ seminars coming up on Thursday with @tiziano.bsky.social and @uthsav.bsky.social! Check them out at bit.ly/3Fv5n7C and bit.ly/3FssGPr
10.03.2025 19:05 β π 2 π 2 π¬ 0 π 0
Check out the paper for more details and neat biological applications! For example, modeling spatial gradients β much more accurate SVG identification
Thanks to great collaborators: Brian @hrksrkr.bsky.social Kohei @congma.bsky.social Sereno @braphael.bsky.social
24.01.2025 21:27 β π 0 π 0 π¬ 1 π 0
GASTON algorithm: parametrize functions h,d with neural nets and learn from data!
Fun back-story: @braphael.bsky.social and I derived most of this model at the bar near an NCI workshop π₯π
24.01.2025 21:27 β π 0 π 0 π¬ 1 π 0
Model implicitly accounts for sparsity by βpoolingβ 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 βtopographic mapβ analogy.
24.01.2025 21:27 β π 0 π 0 π¬ 1 π 0
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! π
We call d(x,y) the "isodepth" - it characterizes spatial gradients β½f_g
24.01.2025 21:27 β π 1 π 0 π¬ 1 π 0
We handle sparsity w/ two assumptions:
(1) genes have *shared* gradient directions, i.e. each gradient β½f_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 βcurlβ, so v=β½d is gradient of "spatial potential" d
24.01.2025 21:27 β π 0 π 0 π¬ 1 π 0
You can view ST data as samples of function f: R^2 β R^G, where f(x,y) is (high-dim) gene expression vector at location (x,y).
Spatial gradients are gradients β½f_g of each component (gene)
Unfortunately, large data sparsity means naive estimation of gradient β½f_g is very noisy π±
24.01.2025 21:27 β π 1 π 0 π¬ 1 π 0
GASTON, our method to learn βtopographic mapsβ of gene expression, is out now @naturemethods.bsky.social!
IMO the coolest part is a new model of *spatial gradients in sparse data*.
As is typical for bio papers, itβs buried in Methods, but see below for a quick outline on the math π
24.01.2025 21:27 β π 2 π 0 π¬ 1 π 0
Distinguishing real from invented problems with the NIH
How does the NIH work and where does it work well?
A must-read article by @sashagusevposts.bsky.social (hopefully by those whose voice will have an impact). Personally, I'd advocate for a fruit-based distribution system of funds.
theinfinitesimal.substack.com/p/distinguis...
07.12.2024 21:44 β π 16 π 3 π¬ 1 π 0
Assistant Professor of Computer Science @JohnsHopkins,
CS Postdoc @Stanford,
PHD @EPFL,
Computational Social Science, NLP, AI & Society
https://kristinagligoric.com/
Schmidt Center Postdoctoral Fellow @ Broad Institute of MIT and Harvard
AI/ML for computational biology π» π§¬π§ͺ
PhD Student @ JHU Langmead Lab
The Irving Institute for Cancer Dynamics (IICD) focuses on the interplay between mathematical sciences and cancer research at Columbia University.
https://linktr.ee/cancerdynamics
Postdoctoral Fellow & BroadIgnite PI - Chen Lab - Broad Institute of MIT and Harvard (@broadinstitute.org) & HSCRB
Ex: @sangerinstitute.bsky.social, University of Cambridge, @ox.ac.uk
Professor of EECS and Statistics at UC Berkeley. Mathematical and computational biologist.
Husband, Father and grandfather, Datahound, Dog lover, Fan of Celtic music, Former NIGMS director, Former EiC of Science magazine, Stand Up for Science advisor, Pittsburgh, PA
NIH Dashboard: https://jeremymberg.github.io/jeremyberg.github.io/index.html
Asst Prof at Carnegie Mellon Stats Dept interested in infectious disease, genomics, time series, and discrete stable distributions.
Genomics, Bioinformatics.
github.com/tobiasrausch
Founder & CEO @jura.bsky.social | Full-stack probabilistic machine learning for the development of genetic medicines | NYC & Basel & Boston
Professor of Computer Science @ JHU. https://www.langmead-lab.org/ https://www.youtube.com/BenLangmead
A diverse and collaborative community on the cutting edge of computing and technology within hopkinsengineer.bsky.social at the Johns Hopkins University.
cs.jhu.edu β’ Baltimore, MD
πΉπ·. Postdoc @Yale, formerly @MIT @Broad. Skeets(?) in TR/EN, views my own.
Postdoc at @genomescience.bsky.socialβ¬. Scientist working in computer science and genomics. More info: arundas.org .
PhD from Schatz Lab @ JHU. Previously: CS @ Brown. He/His/Him. #YNWA π
Researcher in bioinformatics working on single-cell data visualization
Associate Professor of CS @ University of Maryland. Proud Rust advocate! I β₯ science & compiled, statically-typed programming languages! Views are my own. Tech stack: https://github.com/rob-p/tech-stack.
Assistant Professor of Computer Science at UMD | PhD from ETH Zurich