Associate Professor (with Tenure)
Faculty of Information Science and Electrical Engineering
744 Motooka, Nishi-ku
Fukuoka 819-0395, Japan
Email: malei [at] ait.kyushu-u.ac [dot] jp
I am an Associate professor (with Tenure) and co-leading a research group of about 15 researchers at PANGU Lab at Kyushu University,
My current research mainly focuses on the interdisciplinary research fields of Software Engineering, Security and Artificial Intelligence, and especially on proposing quality assurance and security solutions for machine learning engineering.
I received a B.E. degree from Department of Computer Science and Engineering of Shanghai
Jiaotong Unviersity in 2009, M.E. and Ph.D degrees
from The University of Tokyo in 2011 and 2014, respectively.
During my Ph.D. program, I studied half a year in the Mathematics and Computer Science department of
Technische Universität München(TUM).
After receiving the Ph.D., I worked as a Research Fellow in the joint projects collaborated by The University of Tokyo, Chiba University,
Advanced Industrial Science and Technology (AIST/ITRI) and National Institute of Informatics, and later joined in Harbin Institute of Technology as an Associate Professor in 2016 through Young Talents Plan, during which in 2018 I got the chance to visit Prof. Liu Yang's group at NTU, together, we made a series of work and progress in testing deep learning systems. In 2019, I joined Kyushu University and now is an Associate Professor.
I love theories, but I like even more to transfer theories into practice!
I have several research interests and working directions. My current major research interest mainly focuses on general purpose security and quality assurance for deep learning systems. I believe the robust deep learning system would be the key driving force for novel technology of the future. It does not solely rely on the foundational research from the machine learning community, it also highly requires the contribution from software engineering community, security community, etc; the novel interdisciplinary direction so be called Machine Learning Engineering, an extremely exciting and demanding area of the future! We have conducted consecutive works along the general purpose security and quality assurance of DL systems (i.e., testing, analysis, verification, attacks, defenses), to bridge vast demands from industry application and the academic research. Exciting research results would be continuously updated!
In the past, my research interest mainly lies around software engineering and programming language, in particular automated software testing, verification, analysis, evolution, mining, etc. I also worked on green computation and optimization solutions for cloud and big data centers. In addition, I am also interested in genomic data analsyis to uncover life mystery and to search for health solutions through deep learning techniques.