Invited Speakers
Prof. Ting Zhang
University of Baltimore, USA
Ting Zhang is Professor of Economics and Harry Y.
Wright Chair at the Merrick School of Business,
University of Baltimore. She has secured over $10
million in grants from U.S. Departments of Labor,
Agriculture, Education, Gates, and Kauffman
Foundations. Past Chair of the North American
Regional Science Council (2024), past NERSA
President, and APPAM Entrepreneurship Fellow, Dr.
Zhang's scholarship spans aging, entrepreneurship,
and workforce policy with books (Elderly
Entrepreneurship, World Scientific 2008;
Entrepreneurship and Economic Growth in China,
World Scientific 2013, Chinese Entrepreneurship,
De Gruyter 2026) and widely cited articles in top
journals (Small Business Economics,
Entrepreneurship & Regional Development, Applied
Economics, Transportation Research Part A [ABDC
A*]), etc.
She has held editorial roles including Small
Business Economics, Entrepreneurship and
Regional Development, Journal of Urban Management, Letters
in Spatial and Resource Sciences. Her recent
honors include the University System of Maryland
Board of Regents Faculty Award in Research (2023),
President's Faculty Award (2024), Black & Decker
Research Award (2025), and five T. Rowe Price
Excellence in Teaching Awards. A frequent keynote
speaker (Uddevalla Symposium, Harvard, Tsinghua) and
featured in Forbes, Bloomberg, and Time, her work
informs congressional testimony and Maryland Equal
Pay Commission policy.
Prof. Jianping Gou
Southwest University, China
Jianping Gou received the Ph.D. degree in computer
science from University of Electronic Science and
Technology of China, Chengdu, China, in 2012. He was
a Post-Doctoral Research Fellow with The University
of Sydney. Now, he is currently a professor and
doctoral Supervisor in College of Computer and
Information Science, College of Software, Southwest
University, Chongqing, China. His current research
interests are artificial intelligence and machine
learning. His research has resulted in more than 160
publications on top-tier journals and conferences.
He served as a Section Editor of Recent Advances in
Electrical & Electronic Engineering, a Guest Editor
of Mathematics, a Guest Editor of Frontiers in
Physics, Editorial Board of Mathematics, and
Associate Editor of Cognitive Robotics. He is also a
Senior member of IEEE, a Senior member of both CCF
(China Computer Federation), and a Senior member of
CSIG (China Society of Image and Graphics).
Speech Title: Large-scale Model Distillation
Abstract: Large-scale model distillation is a
core technology of empowering large-scale models for
various downstream applications with low-cost and
high-efficiency. On the basis of briefly introducing
the development of large-scale models and
summarizing the relevant technologies of large model
compression, the theory, algorithms, and
applications of model distillation are reviewed, the
series of works on diversity-driven knowledge
distillation are further presented, and the latest
large language model distillation is reported.
Finally, the prospects of large-scale model
distillation are given.
Prof. Mariofanna Milanova
University of Arkansas, USA
Dr. Mariofanna Milanova is a professor in
the Department of Computer Science at UA Little Rock
and has been a faculty member since 2001. She
received a M.Sc. in Expert Systems and Artificial
Intelligence and Ph.D. in Engineering and Computer
Science from the Technical University, Sofia,
Bulgaria. Dr. Milanova conducted post-doctoral
research in visual perception at the University of
Paderborn, Germany. Dr. Milanova has extensive
academic experience at various academic and research
organizations worldwide.
Dr. Milanova is an IEEE Senior Member, Fulbright
U.S. Scholar, and NVIDIA Deep Learning Institute
University Ambassador. Dr. Milanova’s work is
supported by NSF, NIH, DARPA, DoD, Homeland
Security, NATO, Nokia Bell Lab, NJ, USA and NOKIA,
Finland. She has published more than 120
publications, over 53 journal papers, 35 book
chapters, and numerous conference papers. She also
has two patents.
Assoc. Prof. Md Shakhawat Hossain
Kochi University of Technology, Japan
Md Shakhawat Hossain, PhD, is an Associate Professor
at the School of Informatics, Kochi University of
Technology (KUT), Japan, where he leads the AI for
Medical Imaging (AIM) Laboratory. He received his
Ph.D. from the Tokyo Institute of Technology, Japan,
in collaboration with the Memorial Sloan Kettering
Cancer Center (MSK) in the USA. He subsequently
worked as a Research Fellow at MSK and later
accepted a Senior Researcher position in Machine
Learning for Medical Imaging at the University of
Oxford, UK.
Dr. Hossain has developed a clinically validated
AI-based HER2 grading system for breast cancer,
which was recognized by the Association of Pathology
Informatics (API) in the USA. In addition, he has
developed AI-driven diagnostic and decision-support
systems for patients with ovarian, breast, and
colorectal cancer, aiming to improve diagnostic
accuracy, guide therapeutic decision-making, and
support precision oncology in real-world clinical
settings. His research focuses on designing
clinically deployable, lightweight, and explainable
AI solutions for medical image analysis. Dr. Hossain
is a member of IEEE and the Association of Pathology
Informatics, USA.