
Qiangfei Xia
Energy-efficient hardware systems for machine intelligence, security, sensing and communication; Emerging nanoelectronic devices: design, characterization and understanding; Enabling fabrication and three-dimensional heterogeneous integration technologies
Contact details
Location
Marcus Hall
100 Natural Resources Rd.
Amherst, MA 01003
United States
About
Dr. Qiangfei Xia the Dev and Linda Gupta professor of Electrical & Computer Engineering at UMass Amherst and head of the Nanodevices and Integrated Systems Lab. He received his Ph.D. in Electrical Engineering in 2007 from Princeton University, where he was a recipient of the Guggenheim Fellowship in Engineering (a graduate fellowship from Princeton). He then spent three years as a research associate in the Hewlett Packard Laboratories in Palo Alto, California. During that time he demonstrated the first CMOS/memristor hybrid chip with reconfigurable logic functions. In October 2010, he joined the faculty of UMass Amherst as an assistant professor (tenure clock started in January 2011). He became an associate professor with tenure in January 2016 and then a full professor in September 2018.
Dr. Xia's research interests include electronic materials, beyond-CMOS devices, integrated systems, and enabling technologies, with applications in machine intelligence, reconfigurable RF systems, and hardware security. Recently, with his team, he invented a reliable multilevel resistance-switching device that meets most of the required device properties for analog in-memory computing in artificial neural networks, built the world's smallest memristive devices in a crossbar circuit (2 nm feature size, 6 nm half-pitch), and constructed the tallest 3D crossbar array (8 layers, featured as the cover of Nature Electronics) as a convolutional neural network for video processing. Furthermore, he integrated the largest analog memristive crossbar arrays at the time of publication (chip image featured as the inaugural cover of Nature Electronics) and demonstrated a wide variety of applications in analog computing, machine learning, and hardware security. Finally, he debuted the first nanoscale memristive RF switch with superior performance and a few novel hardware security primitives such as a robust true random number generator and a versatile crossbar array that integrates memory, computing, and hardware security functionalities. He has received a DARPA Young Faculty Award (YFA), an NSF CAREER Award, the Barbara H. and Joseph I. Goldstein Outstanding Junior Faculty Award, and the College of Engineering Outstanding Senior Faculty Award. Dr. Xia is a ‘Highly Cited Researcher’ according to Clarivate, and an IEEE Fellow “for contributions to resistive memory arrays and devices for in-memory computing.”
Dr. Xia teaches freshman to graduate-level courses, including Introduction to Electrical and Computer Engineering (ENGIN 112), Fundamentals of Semiconductor Devices (ECE 344), Microelectronic Fabrication (ECE571), Neuromorphic Engineering (ECE576/676), and Nanostructure Engineering (ECE 597/697NS). He created or developed/co-developed most of these courses. He was nominated for the Distinguished Teaching Award (DTA), a campus-wide highest honor to recognize exemplary teaching at UMass.
Dr. Xia has served as a technical committee member for the IEEE International Electronic Devices Meeting (IEDM), IEEE International Symposium on Circuits and Systems (ISCAS), International Conference on Electron, Ion, and Photon Beam Technology and Nanofabrication (EIPBN, steering committee 2019-25; conference chair 2023), to name a few. He organized the in-memory computing tutorial session at the 2019 IEEE International Memory Workshop (IMW) and served as a guest editor or on the editorial board for several journals. He is also an active panelist for the U.S. and international funding agencies and foundations and a peer reviewer for a few dozen international archival journals and conferences. He co-leads the AI Hardware topical area for the Northeast Microelectronic Coalition (NEMC), one of the eight regional innovation hubs in the nation under the Microelectronics Commons program (funded by the CHIPS and Science Act). Within UMass, his most notable service is building a brand-new cleanroom facility in Marcus Hall. As an entrepreneur, he co-founded TetraMem Inc., a Silicon Valley-based startup specializing in AI accelerators.