Artificial intelligence — the systems that guide social media feeds, smartphone apps and other aspects of our lives — is getting smarter, and Computer Science & Engineering Professor Feng Yan is playing a role in that scholarship. Yan’s research bridges three key factors of AI: big data, machine learning and computing systems.
That work has garnered Yan a 2022 ÁùºÏ±¦µä Regents’ Rising Researcher Award, one of several Regents’ Awards announced by the ÁùºÏ±¦µä System of Higher Education March 4. In addition to Yan, four other academics received the Rising Researcher honor, which carries a $2,000 prize.
“I am very honored and grateful to receive this prestigious award as it is an important and encouraging reflection of the high-quality research work everyone in my lab has been doing,” Yan said. “We are encouraged by this award and will keep on trying our best to conduct high impact and productive research in the areas of big data, machine learning and computing systems as well as interdisciplinary topics that go beyond computer science and engineering.”
Specific computer science and engineering research Yan and his team have been working on include large-scale distributed deep learning, federated learning (a privacy preserving machine-learning technique), serverless computing (a new cloud computing paradigm), and broad topics in cloud computing and high performance computing. Additionally, Yan’s research into Machine-Learning-as-a-Service (an emerging computing paradigm that provides optimized execution of machine learning tasks) was recognized by the National Science Foundation with a CAREER Award in 2021.
Yan is also interested in interdisciplinary research and has established collaborations with experts in areas such as health, physics, geography, material science, mechanical engineering, civil engineering. He has innovated big data and AI-driven approaches for those fields.
He says convergence research — a means of solving complex problems through deep integration across disciplines — is important for achieving success in today’s AI revolution.
“I see lots of missed opportunities as well as unaddressed challenges in today’s AI revolution that could be solved by seamlessly integrating big data, machine learning, computing systems and application domain knowledge,” Yan said.
Yan adds that his research has the potential to significantly reduce resource and energy consumption as well as the carbon footprint associated with the fast-growing societal demands in big data and machine learning. His work also provides opportunities for undergraduate and graduate students by training them in the art of system optimization combined with the latest big data and machine learning knowledge.
Yan credits his students, colleagues, and many collaborators for his success, and also appreciates the consistent strong supports from Computer Science & Engineering Department, College of Engineering, and the University leadership.
