[Ececourtesy-list] CCAM Colloquium on Oct 18: Dr. Wotao Yin, Decision Intelligence Lab, DAMO Academy of Alibaba Group in the U.S.

[Scutari, Gesualdo]

CCAM Colloquium on Oct 18

Time and Location: 11:30-12:30, Oct 18, LILY 3118

Speaker: Dr. Wotao Yin<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwotaoyin.mathopt.com%2F&data=05%7C02%7Cececourtesy-list%40ecn.purdue.edu%7C8e85c216b5f24e21a46408dcea104ae1%7C4130bd397c53419cb1e58758d6d63f21%7C0%7C0%7C638642602892597520%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=1kTWOEDtpF7IpJ3PIuygo351LEIVr9jPuAYavgpt8I8%3D&reserved=0>, Decision Intelligence Lab, DAMO Academy of Alibaba Group in the U.S.

Title: From Academia to Industry: Bridging Mathematical Rigor with Scalable Industrial Solutions

Abstract: After 15 years as a math professor, I transitioned to an industrial lab where R&D integrates with engineering, marketing, and sales. We focus on delivering efficient, scalable algorithmic solutions to real-world challenges. This talk will highlight how we manage uncertainties like load and renewable energy prediction by combining machine learning and optimization techniques, and how we solve large-scale optimization problems to ensure safe and economical grid operations. Finally, I’ll discuss how we blend academic rigor with industry needs for rapid, impactful results.

Bio: Dr. Wotao Yin is a Scientist, Principal Engineer at DAMO Academy of Alibaba Group in the U.S., where he leads the Decision Intelligence Lab. He obtained his Ph.D. in Operations Research in Columbia. Prior to joining DAMO Academy, he was a professor in the Department of Mathematics at UCLA. He received an NSF CAREER Award, an Sloan Research Award, the Morningstar Medal in Applied Mathematics, the DAMO Award, and the Egon Balas Award in 2021. Since 2018, Clarivate Analyese has been listed him as one of the world’s 1% highly cited scholars. His research interests include explainable and controllable decision models, computational optimization algorithms and software, and their applications in signal processing, machine learning, and other data science problems.


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