YuXiang CHEN

IBM Distinguished Engineer, IBM

Practices of Machine Learning and Optimization with Quantum Computing

In many cases, real problems need to involve both Machine Learning and Optimization, we usually start from building predictive models based on “data” when lack of insight, but after that, sometimes we intend to rebuild models based on “rules” to find an optimal solution. This talk will introduce few practical ways to leverage Quantum Computing to accelerate problem solving on both AI (Artificial Intelligence) and OR (Operational Research), including full space searching, dot-production of functions, etc. Powered by the next generation computer in future, we could improve both speed and accuracy in real world problems solving.


YuXiang CHEN is a Distinguished Engineer from IBM, most working on designing software solutions with the new technologies and solving real problems for clients, His research interests most focus on AI and Quantum, As a leader of IBM CTO office and IBM Open Innovation Community, he is leading many innovations and run IBM internal academy education in Great China as well, covering Machine Learning, Deep Learning, Quantum Computing and Optimization. In recent years, he published 5 books and many patents on these areas.

YuXiang has rich experience on architecture design and Banking industry solutions, he is both IBM certified IT specialist and architect for many years. In most recently, he is working on put all these technologies together in practical industry solutions.

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(Note: IEEE FITYR2024 is part of the IEEE International Congress on Intelligent and Service-Oriented Systems Engineering (CISOSE 2024), which groups six conferences that cover the whole range of Service-Oriented System Engineering and its Applications, from Artificial Intelligence and Big Data to Distributed, Cloud and Mobile systems.)