Anirudh Rayas

Postdoc @ASU, PhD @ASU

prof_pic1.png

Goldwater Centre 425

650 E. Tyler Mall

Tempe, AZ, 85281

Ph +1 (925)-922-7942

:wave: 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 🎉
Dec 04, 2024 Our paper on Learning Networks from Wide-Sense Stationary Stochastic Processes is out on arXiv. :tada:
Jul 20, 2024 Our paper on The Sample Complexity of Differential Analysis for Networks that Obey Conservation Laws has been accepted at ASILOMAR, 2024. :tada:
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. :tada:
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. :tada:
Nov 28, 2022 Received the Scholar Award to attend NeurIPS, New Orleans 🎉
Sep 20, 2022 Accepted to Google’s CS Research Mentorship Program. :tada:
Sep 14, 2022 Our paper on Learning High Dimensional Networks Obeying Conservation Laws has been accepted at NeurIPS, 2022. :tada:

selected publications

  1. [C] WACV
    Improving Shape Bias in Learnable Geometric Moment Representations
    Sangmin Jung, Anirudh Rayas, Reza R. Azghan, Hassan Ghasemzadeh, Yezhou Yang, and 1 more author
    In IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2026
  2. [J] IEEE TSIPN
    Learning Networks from Wide-Sense Stationary Stochastic Processes
    Anirudh Rayas, Jiajun Cheng, Rajasekhar Anguluri, Deepjyoti Deka, and Gautam Dasarathy
    IEEE Transactions on Signal and Information Processing over Networks, 2025
  3. [C] ISIT
    Structure Learning in Gaussian Graphical Models from Glauber Dynamics
    Vignesh Tirukkonda, Anirudh Rayas, and Gautam Dasarathy
    In IEEE International Symposium on Information Theory (ISIT), 2025
  4. Orthogonality and graph divergence losses promote disentanglement in generative models
    Ankita Shukla, Rishi Dadhich, Rajhans Singh, Anirudh Rayas, Pouria Saidi, and 3 more authors
    Frontiers in Computer Science, 2024
  5. Differential Analysis for Networks Obeying Conservation Laws
    Anirudh Rayas, Jiajun Cheng, Rajasekhar Anguluri, and Gautam Dasarathy
    In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023
  6. [C] NeurIPS
    Learning the Structure of Large Networked Systems Obeying Conservation Laws
    Anirudh Rayas, Rajasekhar Anguluri, and Gautam Dasarathy
    In Advances in Neural Information Processing Systems (NeurIPS), 2022