Dear Society of Asian Scientist and Engineers,

It's with my great honor to nominate Dr. Kang Jun Bai for the Society of Asian Scientist and Engineer’s (SASE) Achievement Award in the Promising Professional Achievement category.

Growing up from a first-generation and working-class family, it's evident that Kang Jun values his family as it provides a powerful motivation for him to work hard and be successful in his career. It was an honor to him to pursue his Ph.D. in Electrical Engineering at Virginia Tech. Thomas Edison said that “genius is one percent inspiration and ninety-nine percent perspiration.” Following this confidence, over the years of his Ph.D. study, he has made significant contributions to the field of Artificial Intelligence (AI) and Machine Learning (ML), in ways to design innovative neuromorphic chips for mobile edge platforms. His research is truly world-leading and highly productive, including six top-tier journals, eleven conference proceedings, and four open-source articles. Such a strong publication record not only granted Kang Jun the First Prize of Bill and LaRue Blackwell Best Dissertation Award at Virginia Tech, but also paved the way for his career at the Air Force Research Laboratory Information Directorate (AFRL/RI).

As an active researcher at AFRL since 2021, Kang Jun has been pioneering the next-generation neuromorphic systems. Specifically, his research effort involves developing revolutionary hardware and applications for Internet of Military Things (IoMT) and Internet of Battlefield Things (IoBT) that leverage the game-changing AI technology, accelerating cognitive operations to extreme efficiency and robustness as well as accomplishing what conventional approaches cannot. His research is in conjunction with the Office of the Under Secretary of Defense (OUSD), Defense Advanced Research Projects Agency (DARPA), Army Research Laboratory (ARL), and Naval Research Laboratory (NRL). Such opportunities strengthen not only his science and technology strategies but also his critical thinking and leadership skills. More importantly, the significance of Kang Jun's research has been recognized worldwide through published journal articles and conference proceedings with an additional three articles under review. Kang Jun believes where possible, our neuromorphic systems optimized for AI-enabled cognitive operations offer faster and more robust yet more efficient decision-making to enable warfighter success.

To take his research to the next level implementation, he is actively work with other AFRL directorates (including Aerospace Systems – RQ, Materials and Manufacturing – RX, and Sensors – RY) to develop innovative research ideas for pitching new programs based on novel technical approaches. In parallel, he continues to collaborate with academia partners (including the State University of New York's Polytechnic Institute (SUNY Poly), Virginia Tech, University of Massachusetts at Amherst, University of Southern California (USC), San Francisco State University (SFSU), etc.) to implement proof-of-concept demos for supporting on-going in-house projects. Throughout these research collaborations, he has brought resources and opportunities of custom integrated circuit design/tapeout with the high-end 22nm CMOS technology for in-house research, resulting in $150,000+ annual saving per user license for AFRL while encouraging in-house researchers to develop new skillsets.

In addition to his primary duties as a research engineer, Kang Jun also volunteers as an associate editor for the Frontiers Journal in Computational Neuroscience and two international symposiums in the field of AI as well as circuits and systems. Such opportunities allow him and other AFRL experts to guide issue content, develop professional connections at the international level, keep informed of technical approaches and outcomes in broader AI/ML communities, and strengthen AFRL’s standing with leading researchers around the world.

Kang Jun's research and contributions have been world-class and his unique intellectual curiosity in his research efforts make him a top performer at AFRL/RI. I believe Kang Jun's accomplishments have prepared him to be a top candidate for this SASE Achievement Award and he comes with my highest recommendation.

Best Regards,


Peter LaMonica
Chief, High Performance Systems Branch
Air Force Research Laboratory, AFRL/RITB