professor of EECS at MIT, currently visiting IAS. working in theoretical computer science namely algorithm design, complexity theory, circuit complexity, etc.
i'll let you know when P != NP is proved (and when it's not)
Associate Professor, Yale Statistics & Data Science. Social networks, social and behavioral data, causal inference, mountains. https://jugander.github.io/
Editor-in-chief, Jewish Currents
Southmayd Prof @YaleLawSch + Philosophy @Yale. Ed, @LegalTheory + Stanford Encyclopedia of Phil. “Legality”, “The Internationalists” (with @oonahathaway), “Fancy Bear Goes Phishing.” Overuses “neurosymbolic”
I study Mathematical Optimization @UCLouvain
Math Assoc. Prof. (on leave, Aix-Marseille, France)
Interest: Prob / Stat / ANT. See: https://sites.google.com/view/sebastien-darses/research?authuser=0
Teaching Project (non-profit): https://highcolle.com/
Assistant Professor @JohnsHopkinsAMS, Works in Mathematical Optimization,
Mostly here to share pretty maths/3D prints, sometimes sharing my research
CNRS researcher in linear programming
Assistant Professor at the university of Warwick.
I compute integrals for a living.
https://adriencorenflos.github.io/
Lecturer in Maths & Stats at Bristol. Interested in probabilistic + numerical computation, statistical modelling + inference. (he / him).
Homepage: https://sites.google.com/view/sp-monte-carlo
Seminar: https://sites.google.com/view/monte-carlo-semina
Senior Staff Research Scientist @Google DeepMind, former Chair Prof @Oxford Uni
Computer science, math, machine learning, (differential) privacy
Researcher at Google DeepMind
Kiwi🇳🇿 in California🇺🇸
http://stein.ke/
Mathematician at UCLA. My primary social media account is https://mathstodon.xyz/@tao . I also have a blog at https://terrytao.wordpress.com/ and a home page at https://www.math.ucla.edu/~tao/
https://sites.google.com/view/kriznakumar/ Associate professor at @ucdavis
#machinelearning #deeplearning #probability #statistics #optimization #sampling
Georgia Tech Prof; Tsinghua (Math+Phys), Caltech (Control & Dynamical Systems), NYU Courant (Applied & Computational Math)
* deep learning theory
* (diffusion) generative model, probabilistic machine learning
* AI4Science
We advance science and technology to benefit humanity.
http://microsoft.com/research
Researcher in computational mathematics
Theory of deep learning, optimal transport, optimization
EPFL
