Biography
Prof. Tao Gong
Prof. Tao Gong
Donghua University, China
Title: An improved immune algorithm for solving path optimization problem in deep immune learning of gene network
Abstract: 
The immune algorithm was analyzed and improved to overcome the defects of the general immune algorithm for solving path optimization problem in deep immune learning of gene network. Firstly, the diversity of the solution population was enhanced in the evolution process by improving the memory cell processing method. Moreover, in the process of population evolution, the effective gene information was dynamically extracted from the gene of the excellent antibody to prepare a vaccine. Poor antibodies were optimized by vaccinating poor antibodies, and the convergence speed was accelerated. Finally, the feasibility of the improved immune algorithm was verified by solving the classic NP problem in deep immune learning of gene network.
Biography: 
Prof. Tao Gong received the MS degree in Pattern Recognition and Intelligent Systems and PhD degree in Computer Science from the Central South University respectively in 2003 and 2007. He is a professor of deep learning / computational immunology / immune computation at Donghua University, China, and he was a visiting scholar at Department of Computer Science and CERIAS, Purdue University, USA. He is the General Editors-in-Chief of the first leading journal Immune Computation in its field, and an editorial board member of some international journals. He was a Technical Committee Chair of ISEEIP 2012, and a Publicity Chair of ISA 2012 and ICSI3 2015. He was Invited Speaker for some conferences such as SecTech 2012, ICAMR 2014, ITA 2016, CSA 2016 and ICBEB 2019. He was also a program committee member of some international conferences such as IEEE ICNC 2011, IEEE BMEI 2011, WMSE 2011, ICARIS 2012, AITS 2012, CCA 2012, ASP 2012, IST 2012, ISA 2012 and SIS2013 etc. He is a Life Member of Sigma Xi, The Scientific Research Society, a Vice-Chair of IEEE Computer Society Task Force on Artificial Immune Systems (2012-2018), and Chen Guang Scholar of Shanghai. His research has been supported by National Natural Science Foundation of China, Shanghai Natural Science Foundation, Shanghai Educational Development Foundation and Shanghai Education Committee etc. He has published over 100 papers in referred journals and international conferences, and over 20 books such as Artificial Immune System Based on Normal Model and Its Applications, and Advanced Expert Systems: Principles, Design and Applications etc. His current research interests include deep learning, computational immunology and immune computation. He is also a committee member of intelligent robots committee and natural computing committee in the Association of Artificial Intelligence of China.