It was my pleasure to host @Masdar CEO Mohamed Jameel Al Ramahi and his team at @Caltech We talked about physical AI and its role for next-generation energy systems
@animaanandkumar
-
AI Researcher Receives Kiyo Tomiyasu Award for Neural Operators
By
–
Thank you @CVPR for hosting my @IEEEorg Kiyo Tomiyasu award. I am thrilled to represent the work of my team and collaborators in bringing AI to scientific domains with Neural Operators and physics-informed learning. The future of science is AI+Science!
I was not aware that Kiyo -
Neural Operators for Medical Imaging Advance at CVPR
By
–
Check out our poster on neural operators for medical imaging today @CVPR
-
Caltech Fellowship Support Advances AI Research Education
By
–
Thank you @WKortschak for your generous support to @Caltech like countless others @ZongyiLiCaltech benefited from your fellowship and mentorship immensely!
-
Caltech Awards Neural Operators Research at 2026 Commencement
By
–
The best undergraduate and graduate research awards at @Caltech commencement this year were presented to research on Neural Operators by my students @ZongyiLiCaltech and Miguel Liu-Schiaffini.
— Prof. Anima Anandkumar (@AnimaAnandkumar) 14 juin 2025
This recognition is a testament to their passion and dedication, and the impact… pic.twitter.com/I9JtAjqCyYThe best undergraduate and graduate research awards at
@Caltech commencement this year were presented to research on Neural Operators by my students @ZongyiLiCaltech and Miguel Liu-Schiaffini. This recognition is a testament to their passion and dedication, and the impact -
Celebrating Student Success and Professional Growth
By
–
Thank you @furongh You were my first student and it fills me with joy to see you fly so high and do amazing impactful work!
-
IEEE Kiyo Tomiyasu Award Winner Attending CVPR2025
By
–
I will be at #CVPR2025 tomorrow and thrilled to receive the IEEE Kiyo Tomiyasu award. See you all there !
-
Gradient Descent Learning on Two-Layer Neural Networks
By
–
Given the new result, I see an extension to proving conditions under which gradient descent can learn general functions on two layer neural network based on score function tensor formulation we developed, which is generalization of Hermite polynomials for Gaussians.
-
Overparametrized Gradient Descent Learns Gaussian Mixtures
By
–
A very cool result showing overparametrized gradient descent (EM) learns Gaussian mixtures. It uses tools from tensor decomposition we developed and connects it to gradient descent.
-
Caltech’s Pivotal Role in AI History and NeurIPS Origins
By
–
Thank you @Caltech for including me in the history of AI. It starts with Carver Mead, John Hopfield and Richard Feynman coming together to teach a course on physics of computation. Not many are aware that the main AI conference, NeurIPS, started at @Caltech