Research

My current research is in the fields of information theory, federated machine/statistical learning, and causality. I’m also currently being mentored in connections between harmonic analysis and differential geometry.
I also work on RFIC/MMIC design and the automation of its inner tasks. I have worked with research groups at Purdue, Columbia University, and the University of Michigan. For a more in-depth look at this, please reference my CV above.

Publications & Preprints

[2] Ali Hammoud, Anhang Li, Ayushman Tripathi, Wen Tian, Harsh Khandeparkar, Ryan Wans, et al., “Reinforcement Learning-Enhanced Cloud-Based Open Source Analog Circuit Generator for Standard and Cryogenic Temperatures in 130-nm and 180-nm OpenPDKs” in IEEE ICCAD 2024 Proceedings, October, 2024
[1] Ryan Wans, “Open Source 2.4GHz LC-VCO in SKY130,” in ISSCC 2023 Student Notebook Competition, November, 2022

Talks, Presentations, Projects

• Cohomology of Lie Algebras and The Levi Decomposition (2026), Paper here
• 14-16 GHz Sliding-IF Receiver on 45nm CMOS (2025), Paper here, Slides here
• Spectral Theory and Geometry (2025), Slides here
• NIST + UMich LC-VCO Design on SKY130 (2022), Slides here
• NIST + UMich SKY130 Inductor Characterization (2022), Slides here
• High School Research Portfolio (2022), Slides here