Multiple research assistantships (full financial support) are available immediately at Dr. Yongchao Yang’s group in the Mechanical Engineering Department at Michigan Tech. Dr. Yang is actively seeking motivated Ph.D. students, who will conduct thesis research in developing physics-aware machine/deep learning methodology to advance the broad artificial intelligence (AI) technology and applications.
The Ph.D. students’ specific directions are flexible and can exploit one or a couple among a wide class of structural/system dynamic models (e.g., vibrational, thermal, elastic waves, multi-scale dynamics, etc). They will explore exciting state-of-the-art techniques such as machine/deep learning, signal/image processing, optimization, networks, etc for topics in broad areas of cyber-physical systems and infrastructure resiliency such as structural dynamics sensing and identification, multi-scale material characterization and detection, and structural health monitoring and non-destructive evaluations in Mechanical/ Aerospace/Civil/Electrical fields.
The students will join a multi-disciplinary research team of structural/mechanical/computer faculty and researchers and will also collaborate with Argonne National Laboratory (https:www.anl.gov) and Los Alamos National Laboratory (https://www.lanl.gov/).
The positions are available immediately (Spring or Fall 2020). Interested students are welcome to directly contact Prof. Yongchao Yang (email@example.com) with CV and research interests.
About the PI – Dr. Yongchao Yang is an Assistant Professor in the Department of Mechanical Engineering – Engineering Mechanics at Michigan Tech. He was a Staff Scientist at Argonne National Laboratory (2018-2019), after a Director’s Funded Postdoctoral Fellowship at Los Alamos National Laboratory (2015-2017). He obtained his Ph.D. from Rice University in 2014 and bachelor’s from Harbin Institute of Technology in 2010, both in structural engineering. His expertise is in structural dynamics, experimental mechanics, system identification and health monitoring. His recent research, funded by DARPA and DOE, has focused on developing new high-resolution structural sensing/imaging and identification methods, combining approaches from computer vision and machine learning. He is the author of more than 30 international journal publications, 3 book chapters, and 2 US patents.
Dr. Yang has received a number of awards and recognitions. He was a recipient of the Best Paper Award of the United Nations International Conference on Sustainable Development (New York, 2015), a winner of the TechCrunch Disrupt NY (New York, 2016), mentored a student winning a 2nd place in the student competition of the IEEE Resilience Week (Chicago, 2016), and received the Mary & Richard Mah Publication Prize for Engineering Science (2018), the 2017 Raymond C. Reese Research Prize of American Society of Civil Engineers (ASCE), and the latest R & D 100 Award (2018). Find out more about Dr. Yang’s recent publications and sponsored projects on his webpage (https://www.mtu.edu/mechanical/people/faculty/yang-y/).