Jongha Jon Ryu

I am a Wormley Family Early Career Assistant Professor in the Department of Computer Science and Engineering and a faculty co-hire in the Institute for Computational and Data Sciences at Penn State.

I develop the mathematical and statistical foundations of scientific machine learning. My work connects spectral learning, generative modeling, and uncertainty quantification to make scientific inference more scalable and reliable.

My first name is pronounced Jong-ha (Korean: 종하), but I usually go by Jon.

CV (September 2026)

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research interests

My recent research centers on by three questions:

• Operator learning: How can we learn structured operator representations that preserve the essential dynamics and physics of complex systems?

• Probabilistic and generative modeling: How can we learn and generate from complex distributions when their densities are unknown or intractable?

• Uncertainty quantification: How can we equip predictive models with statistically meaningful uncertainty estimates that support reliable decisions in adaptive settings?

For more details, check out my research program and publication list.

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bio

Before joining Penn State, I was a postdoc at MIT EECS and RLE, hosted by Gregory W. Wornell. I received my Ph.D. in Electrical Engineering from UC San Diego, advised by Young-Han Kim and Sanjoy Dasgupta, with support from the Kwanjeong Educational Foundation. I earned dual B.S. degrees in Electrical and Computer Engineering and Mathematical Sciences, with a minor in Physics, from Seoul National University, where I graduated with the highest distinction.