Qingxue Zhang, assistant professor of electrical and computer engineering in the School of Engineering and Technology, IUPUI, has received a 5-year Faculty Early Career Development (CAREER) Award from the National Science Foundation (NSF) for his work on Artificial Intelligence and Wearable Computing for Big Data Harnessing. The CAREER Award is the NSF’s most prestigious award in support of early-career faculty who have the potential to become leaders in research and education.
By innovatively bridging AI and Wearable Computing, the UbiEi Lab (Ubiquitous Embedded Intelligence Lab), led by Zhang, is researching, developing, and validating next-generation big data paradigms with people in mind.
With footprints in both industry and academia, Zhang has shaped his career with multidisciplinary expertise in big data research. He spent six years in industry to R&D high-performance and energy-efficient products. As a senior system architect and team lead, he was responsible for multi-layer co-design of algorithm/software/hardware for advanced computing architectures, resulting in seven commercialized patents. He afterwards worked at Harvard to research AI & Wearable Computing Innovations for Big Data-driven Precision Health. Dr. Zhang, in the CAREER project, will apply his unique expertise to study how to leverage deep learning, computing, software/hardware design, sensing, and system design to develop a novel and generalizable big data architecture, which is effective and efficient enough for big data harnessing.
“Human Big Data is boosting many emerging applications. But it is very challenging to analyze and understand the big data because of the complexity and the large volume of the data”, said Zhang. “Also, the difficulty in identifying key patterns in big data poses great challenges to realize the pertinence of big data capturing and analysis.”
“Targeting these challenges”, Dr. Zhang said, “we will design new AI algorithms to understand and analyze human-wearable big data, which is not only essential to determine the dominant patterns in the big data, but also crucial to maximize the energy efficiency by boosting the pertinence of big data.” He further added, “by studying the AI learning principles and simplifying the AI models that are usually of millions or more parameters, we will be able to design efficient AI algorithms that can run on edge devices like wearables.”
Through the innovative, systematic, and continued efforts on big data pattern mining, AI algorithm design, computing efficiency boosting, and wearable computing redesign, the UbiEi Lab aims to effectively advance the human-centered big data innovations, developments, and practices.
“Dr. Zhang has an impressive research background which includes a rich industrial experience and a postdoc at Harvard University”, stated Brian King, Chair of the Department of Electrical and Computer Engineering. “He is a tenure-track faculty in the Electrical & Computer Engineering department at IUPUI and is working on cutting-edge research in the big data area, where he researches artificial intelligence/deep learning on smart health and smart world big data. Dr. Zhang’s work is unique as his research incorporates both AI/deep learning and wearable/edge computing, for big data innovations.”