Dr. Kai Ni received his B.S. degree in Electrical Engineering from University of Science and Technology of China, Hefei, China in 2011, M.S. degree of Electrical Engineering from Vanderbilt University, Nashville, TN, USA in 2013, and Ph.D. degree of Electrical Engineering from Vanderbilt University, Nashville, TN, USA in 2016. Since 2016, he was a postdoctoral associate at University of Notre Dame. He is currently an assistant professor in Microsystems Engineering at Rochester Institute of Technology.
His research interests lie in nanoelectronic devices enabling novel computing paradigms and storage technologies. In particular, he is interested in design of nanoelectronic devices for Artificial Intelligence accelerator, targeting at not only deep learnings but life-long learning and learning to learn general Artificial Intelligence. He is also interested in exploring unconventional computing by harnessing the novel functionalities of emerging devices, for example, Ising Machine for optimization problems, dynamical systems for computational hard problems, and hardware security etc. Additionally, he is interested in exploring unconventional electronics. For example, he is actively investigating the Cryogenic CMOS for high-performance computation and control for Quantum Computing. Another area is reliable and radiation hard electronics for Space Electronics. All these research efforts manifest a new exciting hyperscaling era to come, enabled by all these functional augmentation of today’s technology!
There are currently positions available in our group. Interested and highly motivated students are encouraged to send his/her CV to Dr. Kai Ni
In the News
November 21, 2022
Dozens of RIT researchers included on Stanford University’s list of the world’s top 2% of scientists
Numerous Rochester Institute of Technology faculty, professors emeriti, and postdoctoral researchers were recognized as top-cited scientists in their fields, according to a Stanford University study published by Elsevier.
July 6, 2022
Microelectronic engineering professor developing options for improving memory technologies for storage and computing
Research at RIT into new energy-efficient materials for computing could improve the bottleneck that often occurs when retrieving large amounts of data, hindering processing throughput and energy efficiency.