Invited Speakers

Prof. Yanan Sun
Sichuan University, China

Yanan Sun is currently a professor at the College of Computer Science, Sichuan University, China. He received his Ph.D. degree in computer science from Sichuan University in 2017. From June 2017 to March 2019, he was a postdoctoral fellow at Victoria University of Wellington, New Zealand. His research focuses on evolutionary computation, neural networks, and their applications in neural architecture search. In this research area, he has published 31 peer-reviewed papers including 12 first (correspondence)-authored papers in top IEEE Trans. journals. As PI/Co-PI, he has received five research grants from the Science & Technology Department of Sichuan Province, one from the Chengdu Science and Technology Bureau, and one from the National Natural Science Foundation of China. In 2016, he received the best student paper award of IEEE CIS Chengdu Chapter, National Scholarship of China, and IEEE student travel grant. In 2020, he was awarded as the Innovative talent of science and technology in Sichuan Province (priority funding).

He was invited to be the organizing committee, program committee, special session chair, and tutorial chair of nine international conferences. He was the Thought Leader of Evolutionary Deep Learning from one of the six research focuses established at Victoria University of Wellington. He is the leading organizer of one workshop and two special sessions on the topic of Evolutionary Deep Learning, and the founding chair of IEEE CIS Task Force on Evolutionary Deep Learning and Applications. He is also the Guest Editor of the Special Issue on Evolutionary Computer Vision, Image Processing and Pattern Recognition in Applied Soft Computing, and the Guest Editor of the Special Issue on Evolutionary Deep Neural Architecture Design and Applications in IEEE Computational Intelligence Magazine.

Prof. Haiguang Chen
Shanghai Normal University, China

Haiguang Chen is currently a professor at Shanghai Normal University, China. He received his Ph.D degree in computer science at Fudan University, in 2008, and as Postdoctoral of Biomedical Engineering at Fudan University in 2012. From Feb 2015 to May 2016, he was a Visiting Professor in Yale University, U.S.

He serves as a TPC member for ICUT2009, METI 2009, IMETI 2010, The 17th International Conference on Software Telecommunications and Computer Networks, ICRSA2016, INC 2016, FTC2016, ICACTE 2016, ICIMP 2016, ICSCA 2016, INTELLISYS 2016 etc. He is also a reviewer of The Academic Journal of communication, International Journal of Sensors and Sensor Reviewer, International Journal of Engineering Research and Technology, SAI 2017, etc.

His research interests include security, big data analysis, IoT. His research is partly supported by China 863 Project, NSFC, and other supported by enterprise, etc. He has published more than 30 scientific papers in journals and conference proceedings.

Prof. Zheng-Ming Gao
Jingchu University of Technology, China

Zheng-Ming GAO, Male, born in 1979. He received his Doctor degree of Engineer in 2010 from the engineering university of PLA Rocket Force. He retired from the military in 2018 and was employed as a teacher in school of computer engineering, Jingchu university of technology, Jingmen, China. He is now mainly focusing on the intelligent information technology and equipment designing now. After three-year employment, he is now hosting five research projects and two research groups engaging in the intelligent information technology, machine learning and its applications respectively.
He has published more than forty papers and 4 of them are indexed in SCI and twenties of them are indexed in EI, and published six monograph books; obtained more than 30 patents; 30 computer program certificates.

Assoc. Prof. Wei Shen
Shanghai Jiao Tong University, China

Wei Shen is a tenure-track Associate Professor at the Artificial Intelligence Institute, Shanghai Jiao Tong University, since October 2020. Before that, he was an Assistant Research Professor at the Department of Computer Science, Johns Hopkins University, worked with Bloomberg Distinguished Professor Alan Yuille. He received his B.S. and Ph.D. degrees from Huazhong University of Science and Technology in 2007 and in 2012, respectively. In 2012, he joined Shanghai University, served as an Assistant Professor and then an Associate Professor until Oct 2018. He also worked as a research intern with Prof. Zhuowen Tu at Microsoft Research Asia.

He is an associate editor of Neurocomputing. He also serves as an EAC for VALSE. His research interests lie in the fields of computer vision, machine learning, deep learning, and medical image analysis, particularly in shape based object representation and detection, deep learning algorithms under various learning paradigms and their application to medical image analysis. His research is supported by National Natural Science Foundation of China. He has over 40 peer-reviewed publications in computer vision and machine learning related areas, including IEEE TPAMI, IEEE TIP, IEEE TMI, NIPS, ICML, ICCV, CVPR, ECCV and MICCAI.

Speech Title: Deep Random Forests: Algorithms and Applications
Abstract: Random forests (RFs), or randomized decision trees, are a popular ensemble predictive model, which have a rich and successful history in machine learning in general and computer vision in particular. Deep networks, especially Convolutional Neural Networks (CNNs), have become dominant learning models in recent years, due to their end-to-end manner of learning good feature representations combined with good predictive ability. However, combining these two methods, i.e., Random forests and CNNs, is an open research topic that has received less attention in the literature. A main reason is that decision trees, unlike deep networks, are non-differentiable.

In this talk, I will introduce my recent work on integrating RFs with CNNs (Deep Random Forests) to address various machine learning problems, such as label distribution learning and nonlinear regression. I will show their applications to computer vision problems, such as facial age estimation. I will demonstrate how to learn the Deep Random Forests for different learning tasks by a unified optimization framework.

Assoc. Prof. Kuang Kun
Zhejiang University, China

Kun Kuang, Associate Professor in the College of Computer Science and Technology, Zhejiang University. He received his Ph.D. in the Department of Computer Science and Technology at Tsinghua University in 2019. He was a visiting scholar at Stanford University. His main research interests include causal inference and causally regularized machine learning. He has published over 30 papers in major international journals and conferences, including SIGKDD, ICML, ACM MM, AAAI, IJCAI, TKDE, TKDD, Engineering, and ICDM, etc.

Assoc. Prof. Zhen Wang
Dianzi University, China

Zhen Wang is an associate professor with School of Cyberspace, Hangzhou Dianzi University, China. He received B.Sc, M.Eng., Ph.D. degree in Software Engineering from Dalian University of Technology, China, in 2007, 2009, and 2016. From 2014 to 2016, he was a research fellow at Nanyang Technological University, Singapore. His current research interests include: network security, artificial intelligence security, complex networks, reinforcement learning and algorithmic game theory. He has over 80 peer-reviewed publications in major international journals and conferences, including IJCAI, AAAI, COSE, TCSS, PRE, EPL, etc.

Prof. Helder Gomes Cost
Fluminense Federal University, Brazil

Helder Gomes Costa received his PhD in Mechanical Engineering from Pontifícia Universidade Católica do Rio de Janeiro (1994), Brazil. He is currently full professor and the header of the Decision Analysis Group at Universidade Federal Fluminense (UFF), Brazil, acting on the following subjects: decision multicriteria decision making. clustering and performance evaluation. Nowadays, he is the President of the National Association of Post-Graduation and Research in Production Engineering (ANPEPRO), Brazil.


Assoc. Prof. Rasha Ismail
University of Hertfordshire – GAF, Egypt

Rasha Ismail is currently a Programme Leader of Business Administration at University of Hertfordshire-GAF (UH-GAF), Egypt. She also serves as an Associate Professor and moderation coordinator for Business Administration faculty. She received her Ph. D degree in MIS/E-business from University of the West of England, in 2010. From August 2006 to September 2012, she worked in the career of teaching until she got promoted to Assistant Professor at the Arab Academy for Science and Technology and Maritime Transport (AASTMT), Egypt. She joined American university of the Middle East, Kuwait as an Assistant Professor in 2012 and then she got promoted to Associate Professor in 2015 until she left in 2019.

She is a member of International Association of Computer Science and Information Technology (IACSIT) and she was also a Committee Member in International Conference on Computer Technology and Development (ICCTD 2011). She reviewed a number of researches for several conferences.

Her research interests include Process automation and improvements. She has published a number of researches about business process modeling, the transition to e-business and process improvements in education and manufacturing. Rasha Ismail was awarded certificates for attending conferences and presenting papers, she was also awarded a certificate of appreciation as a reviewer from IBIMA, in addition to certificates of appreciation from AUM for her efforts at work.