Jerry Chun-Wei Lin received his Ph.D. from the Department of Computer Science and Information Engineering, National Cheng Kung University in 2010. He is currently a full Professor with the Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway. He has published more than 450 research articles in refereed journals (IEEE TKDE, IEEE TCYB, IEEE TII, IEEE TITS, IEEE TFS, IEEE TNNLS, IEEE TNSE, IEEE TETCI, IEEE SysJ, IEEE SensJ, IEEE IOTJ, ACM TKDD, ACM TDS, ACM TMIS, ACM TOIT, ACM TIST) and international conferences (IEEE ICDE, IEEE ICDM, PKDD, PAKDD), 11 edited books, as well as 33 patents (held and filed, 3 US patents). His research interests include data mining, soft computing, artificial intelligence/machine learning, and privacy preserving and security technologies. He is the Editor-in-Chief of the International Journal of Data Science and Pattern Recognition, the Guest Editor/Associate Editor for several IEEE/ACM journals such as IEEE TFS, IEEE TITS, IEEE TII, ACM TMIS, ACM TOIT, and IEEE Access. He has recognized as the most cited Chinese Researcher respectively in 2018, 2019, and 2020 by Scopus/Elsevier. He is the Fellow of IET (FIET), ACM Distinguished Member and IEEE Senior Member.
Ji Zhang is currently a full
professor in Computer Science
(equivalent to a
distinguished/endowed professor in
North American universities) in
School of Sciences, Faculty of
Health, Engineering and Sciences at
the University of Southern
Queensland (USQ), Australia. He is
an IET Fellow, RSA Fellow, BCS
Fellow, IEEE Senior Member, ACM
Member, Australian Endeavour Fellow,
Queensland International Fellow and
Izaak Walton Killam Scholar
(Canada). He is also an academic
expert of Australian Academy of
Sciences. He was the Principal
Advisor for Research for the
Division of ICT Services at USQ
Prof. Zhang's research interests include big data analytics, data science, data mining, machine learning and computational intelligence. He has published over 240 papers, many appearing in top-tier international journals including IEEE Transactions on Knowledge and Data Engineering (TKDE), IEEE Transactions on Cybernetics, IEEE Transactions on Dependable and Secure Computing (TDSC), ACM Transactions on Knowledge Discovery from Data (TKDD), ACM Transactions on Intelligent Systems and Technology (TIST), ACM Transactions on Management Information Systems (TMIS), ACM Transactions on Spatial Algorithms and Systems, Information Sciences, Knowledge-based Systems, Neurocomputing, WWW Journal, Journal of Intelligent Information Systems (JIIS), Bioinformatics, Knowledge and Information Systems (KAIS), and top international conferences such as AAAI, IJCAI, VLDB, SIGKDD, ICDE, ICDM, WWW, CIKM, CVPR, COLING, PAKDD and DASFAA. He has also authored one monograph and 10 book chapters. He has three(3) papers as the highest cited papers in image mining and one paper as the highly cited paper in pattern mining. He received three(3) best paper awards respectively in WWW workshop 2021, DIKW 2021 and WISE 2019, and the student travel award of ICDM 2006.
Edwin P. Christmann, professor and chair of the secondary education department and graduate coordinator of Slippery Rock University’s mathematics and science teaching program and earned his Ph.D. at Old Dominion University. He served as a contributing editor to the National Science Teachers Association’s middle schools journal, Science Scope, serves on the editorial review boards of several other research journals, and has authored the books Technology-Based Inquiry for Middle School and Beyond the Numbers: Making Sense of Statistics; and he has coauthored Interpreting Assessment Data: Statistical Techniques You Can Use, Designing Elementary Instruction and Assessment: Using the Cognitive Domain, Designing and Assessing IEP Instruction for Students with Mild Disabilities: Using the Cognitive Domain, and Designing Middle and High School Instruction and Assessment: Using the Cognitive Domain. In addition, he has written over 100 articles and is a frequent speaker at international conferences. He currently teaches graduate-level courses in measurement and assessments, science education, and statistics, which are built on the foundation of his math and science experiences.
Zhang is currently a Professor of
Digital Media Department, School of
Information Science, in the Beijing
Language and Culture University. He
worked as an associated professor
from 2002 to 2007 at the
Laboratory, Institute of Software,
Chinese Academy of Sciences. From
2005 to 2006 he was a Postdoctor
advised by Prof. Michael R. Lyu in
the Department of Computer Science
and Engineering, the Chinese
University of Hong Kong. From
February to April in 2001 he was a
Research Assistant by Dr. KeZhang
Chen in the Department of Mechanical
Engineering, the University of Hong
Kong. From 2000 to 2002 he was a
Postdoctor advised by Prof. Shijie
Cai in the Computer Science and
Technology Department, Nanjing
Prof. Zhang 's research interests include pattern recognition, computer vision, and human-computer interaction, as well as their applications in digital image, digital video, and digital ink. Prof. Zhang has published over 60 refereed journal and conference papers in his research areas. His SCI paper are published in Pattern Recognition, IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, Computer-Aided Design. He has published more than twenty EI papers.
Prof. Zhang received his B.E. in Chemical equipment and machinery from Fushun Petroleum Institute (became Liaoning Shihua University since 2002) in 1995, and his Ph.D. advised by Prof. ZongYing Ou in Mechanical manufacturing and automation from Dalian University of Technology in 2000.
Peter pioneered the Big Data Analytics program for K-12 in education in 2014 where neither curriculum nor standards exist. His passion in data analytics is evident in his teachings and research work. He shares his data analytics passion with his students by supervising practical data analytics projects in his Big Data Analytics course. Both his and his students' work have been presented regularly at several international big data analytics conferences. In 2020, Peter and his students developed the Concordia International School online big data online course (www.cissbigdata.org). Peter began his career as an aerospace engineer in the preliminary design of a supersonic Mach 2+ Unmanned Aerial Vehicle (UAV) for the Department of National Defence, Canada. He later found his calling to be a teacher. With a background in Electrical Engr. (B.Sc.), Mechanical Engr. (M.Sc.), Aerospace Engr. (Ph.D.) and Dip. Ed. Peter readily integrates practical real life engineering experience into the classroom. He also developed an Aerospace Engineering course for high school and is the teacher advisor to The Concordia Phoenix Squadron (https://phoenixsquadron.concordiashanghai.org). He is a member of the program committee for International Big Data and Analytics Educational Conference and is on the Advisory Board to True North School Hanoi, Vietnam. He has taught in Australia, Canada, Indonesia, Malaysia, Singapore and is currently teaching in China.