Daniel Petrini
PhD in computer vision/AI - medical imagens. Electronics projects, astronomy, and the history of science. Father, husband, electrical engineer and engineering manager.
@neuripsconf.bsky.social
The Thirty-Eighth Annual Conference on Neural Information Processing Systems will be held in Vancouver Convention Center, on Tuesday, Dec 10 through Sunday, Dec 15. https://neurips.cc/
@erictopol.bsky.social
physician-scientist, author, editor https://www.scripps.edu/faculty/topol/ Ground Truths https://erictopol.substack.com SUPER AGERS https://www.simonandschuster.com/books/Super-Agers/Eric-Topol/9781668067666
@alirezamh.bsky.social
PhD Student at the University of Toronto. Interested in deep learning theory. https://www.cs.toronto.edu/~mousavi/
@froskekongen.bsky.social
AI researcher. CTO at HANCE, Associate Professor at NTNU. Compression, generative, audio, time series
@mohaas.bsky.social
IMPRS-IS PhD student @ University of Tübingen with Ulrike von Luxburg and Bedartha Goswami. Mostly thinking about deep learning theory. Also interested in ML for climate science. mohawastaken.github.io
@mufan-li.bsky.social
Postdoc at Princeton | Incoming Assistant Prof at Waterloo Statistics | Prev: PhD at UofT and Vector https://mufan-li.github.io/
@adamian.bsky.social
@pontilgroup.bsky.social
Computational Statistics and Machine Learning (CSML) Lab | PI: Massimiliano Pontil | Webpage: csml.iit.it | Active research lines: Learning theory, ML for dynamical systems, ML for science, and optimization.
@erfunmirzaei.bsky.social
Researcher @PontilGroup.bsky.social| Ph.D. Student @ellis.eu, @Polytechnique, and @UniGenova. Interested in (deep) learning theory and others.
@laurenceai.bsky.social
Lecturer at the University of Bristol. probabilistic ML, optimisation, interpretability, LLM evals.
@anirbit.bsky.social
Assistant Professor/Lecturer in ML @ The University of Manchester | https://anirbit-ai.github.io/ | working on the theory of neural nets and how they solve differential equations. #AI4SCIENCE
@shamkakade.bsky.social
Harvard Professor. ML and AI. Co-director of the Kempner Institute. https://shamulent.github.io
@eadeli.bsky.social
Assistant Prof at Stanford, Director of Stanford Translational AI (STAI) Lab Computer Vision, Computational Neuroscience
@aleximas.bsky.social
Economics + Applied AI, Prof at University of Chicago Booth School of Business. Formerly: Carnegie Mellon, UCSD, Northwestern. Website: www.aleximas.com
@danielrock.bsky.social
Assistant Professor at UPenn/Wharton OID researching economics of AI and productivity. Fan of dogs.
@carl-allen.bsky.social
Laplace Junior Chair, Machine Learning ENS Paris. (prev ETH Zurich, Edinburgh, Oxford..) Working on mathematical foundations/probabilistic interpretability of ML (what NNs learn🤷♂️, disentanglement🤔, king-man+woman=queen?👌…)
@leenacvankadara.bsky.social
Lecturer @GatsbyUCL; Previously Applied Scientist @AmazonResearch; PhD @MPI-IS @UniTuebingen
@alucchi.bsky.social
Researcher in optimization and theoretical machine learning. Assistant professor at the University of Basel. Past: EPFL, ETH Zurich (Switzerland) 🇨🇭
@ernestryu.bsky.social
Professor of Applied Mathematics at UCLA. Interested in deep learning and optimization.
@evanatyourservice.bsky.social
ML/RL enthusiast, second-order optimization, plasticity, environmentalist
@krizna.bsky.social
https://sites.google.com/view/kriznakumar/ Associate professor at @ucdavis #machinelearning #deeplearning #probability #statistics #optimization #sampling
@benedikt.phd
Imperial PhD Deep learning | computer vision | autonomous drones | diffusion models | LLMs + RAG benedikt.phd
@hessianfree.bsky.social
Optimization Generative Modeling @Caltech, PhD @UCLA. ex Research Scientist Intern @AIatMeta (opinions are my own) why is jax so difficult
@atlaswang.bsky.social
https://vita-group.github.io/ 👨🏫 UT Austin ML Professor (on leave) https://www.xtxmarkets.com/ 🏦 XTX Markets Research Director (NYC AI Lab) Superpower is trying everything 🪅 Newest focus: training next-generation super intelligence - Preview above 👶
@henrygo.uk
Assistant Professor (Lecturer) and RAEng Research Fellow at University of Edinburgh 🏴. Working on Verifiable AI. henrygouk.com
@saxelab.bsky.social
Professor at the Gatsby Unit and Sainsbury Wellcome Centre, UCL, trying to figure out how we learn
@rarefin.bsky.social
PhD Candidate Mila/University of Montreal | Intern at Amazon | Ex. ServiceNow, Recursion, UpStride | Researching to understand how Deep Learning works https://rarefin.github.io
@thserra.bsky.social
Assistant professor at University of Iowa, formerly at Bucknell University, mathematical optimizer with an #orms PhD from Carnegie Mellon University, curious about scaling up constraint learning, proud father of two
@richtarik.bsky.social
Professor of CS and Math @ KAUST. Interested in Optimization for Machine Learning. Federated learning guru. Likes 🏓🏋️♂️🎾🏐⛷️⛸️🧘♂️🤿🎹🎸✈️🏔️📷☀️🐈🍅🥚☕️
@dccsillag.xyz
Applied mathematician working on machine learning, statistics and compilers. Currently doing research at FGV EMAp. dccsillag.xyz
@pierremarion.bsky.social
Postdoc @ EPFL, working on the theory of deep learning. Previously Polytechnique and Sorbonne Université.
@gkdziugaite.bsky.social
Sr Research Scientist at Google DeepMind, Toronto. Member, Mila. Adjunct, McGill CS. PhD Machine Learning & MASt Applied Math (Cambridge), BSc Math (Warwick). gkdz.org
@emalach.bsky.social
Research Fellow @ Kempner Institute, Harvard University Theory of Deep Learning / Learning of Deep Theory
@ananyak.bsky.social
Research scientist at OpenAI working on reasoning and RL. Previously PhD student at Stanford University working with Percy Liang and Tengyu Ma.
@vaishnavh.bsky.social
Foundations of AI. I like simple and minimal examples and creative ideas. I also like thinking about the next token 🧮🧸 Google Research | PhD, CMU | https://arxiv.org/abs/2504.15266 | https://arxiv.org/abs/2403.06963 vaishnavh.github.io
@oymak.bsky.social
EECS Prof @UMich, Research on the Foundations of ML+RL+LLM https://sota.engin.umich.edu/
@erdog.bsky.social
Professor at University of Toronto. Research on machine learning, optimization, and statistics.
@lenaicchizat.bsky.social
Researcher in computational mathematics Theory of deep learning, optimal transport, optimization EPFL
@cevherlions.bsky.social
Associate Professor of Electrical Engineering, EPFL. Amazon Scholar (AGI Foundations). IEEE Fellow. ELLIS Fellow.
@yasamanbb.bsky.social
Research Scientist @ Google DeepMind. Physics of learning, ML / AI, condensed matter. Prev Ph.D. Physics @ UC Berkeley.