PhD student in differential privacy and mobility at the University of Padova. Master's in Theoretical Physics.
Love long hiking and music.
Researcher in ML and Privacy.
PhD @UofT & @VectorInst. previously Research Intern @Google and @ServiceNowRSRCH
https://mhaghifam.github.io/mahdihaghifam/
Machine Learning Researcher @BellLabs
Security and Privacy of Machine Learning at UofT, Vector Institute, and Google 🇨🇦🇫🇷🇪🇺 Co-Director of Canadian AI Safety Institute (CAISI) Research Program at CIFAR. Opinions mine
Responsible AI. Previously, BU, OpenDP, Columbia, Twitter
https://shlomi.hod.xyz
he/they
IEEE Conference on Secure and Trustworthy Machine Learning
March 2026 (Munich) • #SaTML2026
https://satml.org/
Third-year CS Ph.D. student at University of Copenhagen. Very much into differentially private things, and on the postdoc market! jdandersson.net
PhD student in differential privacy & learning at Inria 🇫🇷
TCS+ is the original online seminar in theoretical computer science, committed to the carbon-free dissemination of ideas across the globe since 2013. Talks from the cutting edge of research in TCS, for a wide audience: https://www.tcsplus.org
PhD Student @ UWaterloo, Interested in TCS + Stats/ML and Differential Privacy
https://argymouz.github.io/
Professor and Head of Algorithms, Data Structures and Foundations of Machine Learning at Computer Science, Aarhus University
A little pinch of randomness here and there and poof, your data is now protected. Magic! ✨
(I don't read DMs. Send me an email instead.)
🌉 bridged from ⁂ https://hachyderm.io/@tedted, follow @ap.brid.gy to interact
Assistant Prof of CS at the University of Waterloo, Faculty and Canada CIFAR AI Chair at the Vector Institute. Joining NYU Courant in September 2026. Co-EiC of TMLR. My group is The Salon. Privacy, robustness, machine learning.
http://www.gautamkamath.com
Professor at Penn, Amazon Scholar at AWS. Interested in machine learning, uncertainty quantification, game theory, privacy, fairness, and most of the intersections therein
Computer science, math, machine learning, (differential) privacy
Researcher at Google DeepMind
Kiwi🇳🇿 in California🇺🇸
http://stein.ke/
