This year’s ACM Dissertation Award goes to Chuchu Fan for her awesome work just down the street at the ECE Department [1].
I’ve never met Dr. Fan in person, but I will join with all Illinois alums saluting her great work. She makes us proud, and makes us all look good.
The work in question is very impressive [2]. Not that I understand the details. But I understand why it is important and why it is hard.
From what I do understand of the work, it is an interesting case of putting together pieces to make a useful whole. Basically, she is able to combine formal mathematical descriptions of the parts of a system, including different types of models, with incomplete and missing pieces. The “data driven” part includes machine learning, naturally, as well as other data sources.
The hard part is to formally prove properties of this complicated and messy thing.
It’s hard. So hard no one could do it before, at least not in reasonable ways.
But yes, yes she can. And did.
Naturally, this being Illinois, she also built software and actually did it on real life examples. We expected nothing less. : – )
And these methods are widely applicable and far more efficient. In short, they are revolutionizing the development of autonomous robots and many other devices.
No this is what I call, “a result”! : – )
Well done, Dr. Fan.
- Association for Computing Machinery, University of Illinois at Urbana-Champaign Graduate Receives ACM Doctoral Dissertation Award. 2021. https://awards.acm.org/about/2020-doctoral-dissertation
- Chuchu Fan, “Formal methods for safe autonomy: Data-driven verification, synthesis, and applications.” Ph.D. Dissertation, Electrical & Computer Engineering, University of Illinois at Urbana-Champaign, 2019. http://hdl.handle.net/2142/106202
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