Javier
Estudio matemática
Me encanta hablar de matemática
A veces me interesa la política 🫣
@samubortolotti.bsky.social
Ph.D. student in Artificial Intelligence at the University of Trento.
@aoc.bsky.social
Waitress turned Congresswoman for the Bronx and Queens. Grassroots elected, small-dollar supported. A better world is possible. ocasiocortez.com
@theonion.com
America’s Finest News Source. A @globaltetrahedron.bsky.social subsidiary. Get the paper delivered to your door: membership.theonion.com
@ldobartra.bsky.social
Divulgador | Educador | Escribidor. Creador de El Robot de Platón, El Robot de Linneo y Robotitus. He escrito 3 libros y no me gusta el café.
@gautamkamath.com
Assistant Prof of CS at the University of Waterloo, Faculty and Canada CIFAR AI Chair at the Vector Institute. Joining NYU Courant in September 2025. Co-EiC of TMLR. My group is The Salon. Privacy, robustness, machine learning. http://www.gautamkamath.com
@aaroth.bsky.social
Professor at Penn, Amazon Scholar at AWS. Interested in machine learning, uncertainty quantification, game theory, privacy, fairness, and most of the intersections therein
@stein.ke
Computer science, math, machine learning, (differential) privacy Researcher at Google DeepMind Kiwi🇳🇿 in California🇺🇸 http://stein.ke/
@thejonullman.bsky.social
Associate Professor of Computer Science at Northeastern University in Boston. Dad. Imposter.
@ccanonne.github.io
Senior Lecturer #USydCompSci at the University of Sydney. Postdocs IBM Research and Stanford; PhD at Columbia. Converts ☕ into puns: sometimes theorems. He/him.
@thesasho.bsky.social
Associate professor at U of Toronto. Computer science and math research: (differentially) private data analysis, geometry, discrepancy, optimization.
@zstevenwu.bsky.social
Computer science professor at Carnegie Mellon. Researcher in machine learning. Algorithmic foundations of responsible AI (e.g., privacy, uncertainty quantification), interactive learning (e.g., RLHF). https://zstevenwu.com/
@nandofioretto.bsky.social
Assistant Professor of Computer Science at the University of Virginia. I work on Responsible AI (differential privacy & fairness) and machine learning for science and engineering (differentiable optimization) | http://nandofioretto.github.io
@adamsmith.xyz
Professor of computer science at Boston University. Not related to any economists, living or dead, as far as I know.
@bipr.bsky.social
ML & Privacy Prof at the University of Melbourne, Australia. Deputy Dean Research. Prev Microsoft Research, Berkeley EECS PhD. @bipr on the X bird site. He/him.
@ahonkela.bsky.social
Prof of machine learning at University of Helsinki. Interested in (differential) privacy and open source software.
@jubaz.bsky.social
Assistant professor at Georgia Tech in ISyE. I do mechanism design, differential privacy, fairness, and learning theory, mostly. Postdoc @Penn; Ph.D. @Caltech; MSc @Columbia and @Supélec. He/him.
@differentialprivacy.org
🤖 new arXiv preprints mentioning "differential privacy" or "differentially private" in the title/abstract/metadata + updates from https://differentialprivacy.org [Under construction.]
@vsergei.bsky.social
Algorithms, predictions, privacy. https://theory.stanford.edu/~sergei/
@amartyasanyal.bsky.social
Assistant Professor @Dept. Of Computer Science, University of Copenhagen, Ex Postdoc @MPI-IS, ETHZ, PhD @University of Oxford, B.Tech @CSE,IITK.
@gavin-brown.bsky.social
Postdoc at UW CSE. Differential privacy, memorization in ML, and learning theory.
@rasmuspagh.net
Professor of computer science at University of Copenhagen. Interested in random things & their application (especially to algorithms and privacy). rasmuspagh.net
@jelaninelson.bsky.social
Professor and Chair of Computer Science Division, UC Berkeley EECS. Research Scientist (part-time) at Google. Founder, AddisCoder. 🇻🇮🇺🇸🇪🇹
@mdinitz.bsky.social
Associate Professor, Department of Computer Science, Johns Hopkins University. https://www.cs.jhu.edu/~mdinitz/
@svpino.com
I help companies build Machine Learning • I run http://ml.school. • Posts about what I learn along the way.
@timrudner.bsky.social
Assistant Professor & Faculty Fellow, NYU. AI Fellow, Georgetown University. Probabilistic methods for robust and transparent ML & AI Governance. Prev: Oxford, Yale, UC Berkeley. https://timrudner.com
@alexlew.bsky.social
Theory & practice of probabilistic programming. Current: MIT Probabilistic Computing Project; Fall '25: Incoming Asst. Prof. at Yale CS
@cmaddis.bsky.social
Asst. Prof. in Machine Learning at UofT. #LongCOVID patient. https://www.cs.toronto.edu/~cmaddis/
@canaesseth.bsky.social
Assistant Professor of Machine Learning Generative AI, Uncertainty Quantification, AI4Science Amsterdam Machine Learning Lab, University of Amsterdam https://naesseth.github.io
@sejdino.bsky.social
Professor of Statistical Machine Learning at the University of Adelaide. https://sejdino.github.io/
@desirivanova.bsky.social
Research fellow @OxfordStats @OxCSML, spent time at FAIR and MSR Former quant 📈 (@GoldmanSachs), former former gymnast 🤸♀️ My opinions are my own 🇧🇬-🇬🇧 sh/ssh
@eringrant.bsky.social
Senior Research Fellow @ ucl.ac.uk/gatsby & sainsburywellcome.org {learning, representations, structure} in 🧠💭🤖 my work 🤓: eringrant.github.io not active: sigmoid.social/@eringrant @[email protected], twitter.com/ermgrant @ermgrant
@jwvdm.bsky.social
Associate Professor (UHD) at the University of Amsterdam. Probabilistic methods, deep learning, and their applications in science in engineering.
@mvdw.bsky.social
Associate Professor in Machine Learning at the University of Oxford. Interested in automatic inductive bias selection using Bayesian tools.
@mgorinova.bsky.social
ex-@TwitterCortex @Birdwatch 💙 | Now LLMs for innovation & IP 🚀 | PhD in probabilistic machine learning, loyal servant to a cat, collector of random variables, lover of well-placed puns https://mgorinova.github.io/
@maosbot.bsky.social
Parent, spouse, Australian, Professor of Machine Learning in Oxford. Bayesian ML, Long Covid, trans rights, photos of dog, AI must be good for humans, https://www.robots.ox.ac.uk/~mosb
@tychovdo.bsky.social
Postgraduate researcher (PhD) at Imperial College London and visiting researcher at the University of Oxford. Working on probabilistic machine learning.
@vincefort.bsky.social
PI at Helmholtz AI, Faculty at TU Munich, Fellow at Zuse School for reliable AI, Branco Weiss Fellow, ELLIS Scholar. Prev: Cambridge CBL, St John's College, ETH Zürich, Google Brain, Microsoft Research, Disney Research. https://fortuin.github.io/
@yaringal.bsky.social
Associate Professor of Machine Learning, University of Oxford; OATML Group Leader; Director of Research at the UK government's AI Safety Institute (formerly UK Taskforce on Frontier AI)
@willieneis.bsky.social
Assistant Professor in CS + AI at USC. Previously at Stanford, CMU. Machine Learning, Decision Making, AI-for-Science, Generative AI, ML Systems, LLMs. https://willieneis.github.io
@karen-ullrich.bsky.social
Research scientist at FAIR NY ❤️ Machine Learning + Information Theory. Previously, PhD at UoAmsterdam, intern at DeepMind + MSRC.
@nolovedeeplearning.bsky.social
human being | assoc prof in #ML #AI #Edinburgh | PI of #APRIL | #reliable #probabilistic #models #tractable #generative #neuro #symbolic | heretical empiricist | he/him 👉 https://april-tools.github.io
@emilevankrieken.com
Post-doc @ University of Edinburgh. Neurosymbolic Machine Learning, Generative Models, NLP https://www.emilevankrieken.com/
@mgollub.bsky.social
🧬💻 | Director of Machine Learning @jura.bsky.social | Probabilistic models, ML, Molecular biology, Immune receptors.