Yanjie Fu

Yanjie Fu says that he is intrigued by a passion to explore the unknown. This mindset has driven him to make impacts in the engineering field.

“I was originally drawn to engineering because it allows us to solve foundational problems that benefit a variety of applications and develop intelligent technologies to make our lives better,” he says.

Fu is preparing for a new role as an associate professor of computer science and engineering in the School of Computing and Augmented Intelligence, part of the Ira A. Fulton Schools of Engineering at Arizona State University.

Throughout his career, Fu has received more than $2.5 million in research grants to support eleven projects, secured five core research awards through the National Science Foundation, including its prestigious Faculty Early Career Development Program, or CAREER, Award. 

His research interests span data mining, machine learning and interdisciplinary applications, with recent focuses including deep spatial, time series and stream learning; graph learning; reinforcement learning; data-centric AI; causal learning and anomaly detection; and distribution drift. Fu has also published more than 90 papers in top research journals and conference proceedings in his field, garnering more than 4,000 citations. 

Prior to joining ASU, Fu worked as an assistant professor at the University of Central Florida. He also brings experience from his time at the Missouri University of Science and Technology and Rutgers University, where he developed and offered a total of six courses on machine learning, data mining, big data and information systems.

Fu says he is attracted to ASU because of the quality of its students, the school’s academic ranking and alumni achievements. 

“I am excited to work with colleagues and PhD students at ASU to conduct cutting-edge research on AI for transformative interdisciplinary applications,” Fu says, noting that applications include urban and social computing, operations management and AI for science.

Fu says that his students should be prepared to learn about data mining, algorithms, data structures, programming and databases in his courses.

Outside of the classroom, he enjoys playing table tennis and musical instruments.

Meet the newest faculty members of the Fulton Schools of Engineering here.

Written by Annelise Krafft