Anirudh Rayas
Goldwater Centre 425
650 E. Tyler Mall
Tempe, AZ, 85281
Ph +1 (925)-922-7942
Welcome to my website!
I’m a Postdoc working with Prof. Pavan Turaga at the GAME School in the Herberger Institute for Design and the Arts at Arizona State University (ASU). I received my PhD in Electrical, Computer, and Energy Engineering from ASU, where I was advised by Prof. Gautam Dasarathy. Before that, I earned my B.Tech degree in Electronics and Communication Engineering from PES University, Bangalore.
My research lies at the intersection of machine learning, statistics, and geometry, with applications in AI for Healthcare and Science. I am particularly interested in statistical and geometric methods, such as graph representation learning and structured inference, that make learning possible when data is scarce. Medical data, in particular, is often high-dimensional, noisy, and expensive to accrue; building good predictive models therefore hinges on understanding the underlying structure of the data and bringing the right statistical and geometric tools to bear. But predictive models are only half the story: because healthcare decisions informed by AI are consequential and carry real risk, I am equally focused on developing uncertainty-aware methods that quantify confidence and guarantee trustworthy, well-calibrated decisions.
In my spare time, I like to read about the history of mathematics and mathematicians. I also enjoy hiking, swimming, playing chess (albeit poorly), and watching animated movies.
news
| Feb 14, 2025 | Best presentation award for Graduation Day at Information Theory and Applications Workshop (ITA), San Diego 🎉 |
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| Dec 04, 2024 | Our paper on Learning Networks from Wide-Sense Stationary Stochastic Processes is out on arXiv. |
| Jul 20, 2024 | Our paper on The Sample Complexity of Differential Analysis for Networks that Obey Conservation Laws has been accepted at ASILOMAR, 2024. |
| May 22, 2024 | Our paper on Orthogonality and graph divergence losses promote disentanglement in generative models has been accepted at Frontiers in Computer Science, 2024. |
| May 21, 2024 | Grateful for a wonderful summer internship at Los Alamos National Laboratory. Huge thanks to Dr. Deepjyoti Deka for hosting me! |
| Apr 19, 2023 | Recieved travel grant to attend North American School on Information Theory (NASIT) at UPenn 🎉 |
| Feb 15, 2023 | Our paper on Differential Analysis for Networks Obeying Conservation Laws has been accepted at ICASSP, 2023. |
| Nov 28, 2022 | Received the Scholar Award to attend NeurIPS, New Orleans 🎉 |
| Sep 20, 2022 | Accepted to Google’s CS Research Mentorship Program. |
| Sep 14, 2022 | Our paper on Learning High Dimensional Networks Obeying Conservation Laws has been accepted at NeurIPS, 2022. |
selected publications
- Orthogonality and graph divergence losses promote disentanglement in generative modelsFrontiers in Computer Science, 2024
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