The Ken Kennedy Institute's January Member of the Month: Shiqian Ma

Associate Professor of Computational Applied Mathematics and Operations Research

Shiqian Ma

The Ken Kennedy Institute's January Member of the Month: Shiqian Ma, Associate Professor of Computational Applied Mathematics and Operations Research (CMOR).

Associate Professor Shiqian Ma received his Ph.D. in Industrial Engineering and Operations Research from Columbia University. His research interests include theory and algorithms for large-scale optimization, and its various applications in operations, statistics, machine learning, and signal processing. His research is currently supported by NSF Grants from the DMS, CCF, and ECCS programs. He was a plenary speaker of the 2023 Texas Colloquium on Distributed Learning and a semi-plenary speaker of the XVI International Conference on Stochastic Programming in 2023. Shiqian currently serves as the elected Secretary/Treasurer of the INFORMS Optimization Society and the General Chair of the INFORMS Optimization Society Conference 2024.

How would you explain your research in 1-2 sentences?

My group aims to design optimization algorithms that are efficient, accurate, and scalable for applications from science and engineering.

How does your work impact the community at large?

How to minimize the cost, maximize the revenue, minimize the training loss, find the shortest path? These are some representative questions that optimization cares about. My research is a fundamental part of many real problems that the community concerns in our daily life.

What kind of collaborations are you looking for at Rice and within the community?

I am open to any collaborations where there is an optimization component. I have many collaborators from other fields such as machine learning, signal processing, communication, statistics, bioinformatics and so on. I am very interested in developing new collaborations in these fields at Rice and within the community.

How do you see computation and data advancing in the future?

Optimization becomes one of the main workhorses of machine learning and data science, since the emergence of big data and deep learning. These fields bring new challenges for optimization, such as how to design algorithms to deal with noisy data, huge-scale data, and partial data. These questions were not widely considered in optimization back to twenty years ago. With more and more data generated, the demand for computational infrastructures, tools, and methods increases rapidly. Therefore, this is a very exciting era for optimization and data science, and they will benefit from each other’s development in the future.

How do you see the Ken Kennedy Institute supporting you and/or your research?

The Ken Kennedy Institute has provided a very good research environment such as supporting workshops, providing seed funding, organizing seminars and the members’ luncheon etc. I have benefited a lot from these activities to exchange research ideas and foster my research.

What is your favorite book or movie?

I enjoy reading history books. I like a lot of movies such as “The Shawshank Redemption”, “The Lord of the Rings”, and Hong Kong Kung Fu movies. But now I watch “Peppa Pig” the most because of my daughters.

Do you have any words of inspiration you would like to share?

“Success is not final, failure is not fatal: It is the courage to continue that counts.”


See Shiqian's Rice Profile here.


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