Invited Speakers

2023 8th International Conference on Intelligent Information Technology (ICIIT 2023) aims to gather professors, researchers, scholars and industrial pioneers all over the world. ICIIT is the premier forum for the presentation and exchange of past experiences and new advances and research results in the field of theoretical and industrial experience. The conference welcomes contributions which promote the exchange of ideas and rational discourse between educators and researchers all over the world. We aim to building an idea-trading platform for the purpose of encouraging researcher participating in this event. ICIIT 2023 is welcome qualified persons to delivery a speech in the related fields. If you are interested, please send a brief CV with photo to the conference email box: iciit@cbees.net.

Invited Speaker I

Prof. Vinod A. Prasad

Singapore Institute of Technology, Singapore

Vinod A Prasad received his B. Tech. degree in Instrumentation & Control Engg. From University of Calicut, India in 1993 and the Master of Engineering (by Research) and Ph.D. degrees from School of Computer Engineering, Nanyang Technological University (NTU) Singapore in 2000 and 2004 respectively. In May 2022, Vinod joined the Information Communication Technology Cluster, Singapore Institute of Technology (SIT), Singapore, as a Professor. He also served as a Visiting Associate Professor in Electrical & Computer Engg. Dept., University of British Columbia, Canada, during June-July 2013. Vinod’s research interests include digital signal processing, VLSI signal processing circuits and systems for wireless communications, Brain-Computer Interface and its applications in neurofeedback, neurorehabilitation, neuroprosthetics and assistive technology devices. He is an Associate Editor of five journals - IEEE Transactions on Human-Machine Systems, IEEE Transactions on Neural Systems and Rehabilitation Engineering, IEEE Transactions on Cognitive and Developmental Systems, IEEE Systems Man & Cybernetics Magazine, and Circuits, Systems & Signal Processing (Springer).

 

Invited Speaker II

Assoc. Prof. Minh Nguyen

Auckland University of Technology, New Zealand

Associate Professor Minh Nguyen MSc, PhD, FHEA, MIITP, is currently the Head of the Computer Science and Software Engineering (CSSE@AUT) Department in The School of Engineering, Computer and Mathematical Sciences at Auckland University of Technology (AUT). The Computer Science and Software Engineering department is one of the largest departments at AUT, with 50 academic staff, including ten full professors and nine associate professors. Our teaching and research staff are among the best in New Zealand and internationally; and over 90% of our department have PhD degrees. Minh is a Fellow of the Higher Education Academy (UK Professional Standards Framework for teaching and learning support in higher education) and a Full Member of IT Professionals New Zealand. He obtained a PhD degree from the University of Auckland in 2014 and is currently the deputy director of the Centre for Robotics & Vision @ AUT. His research focused on the computational theory and practice of Computer and Robot Vision, Image Processing, Virtual Reality and Augmented Reality for Educational and Medical purposes. He has produced over 50 publications, organised many international research conferences, and received several grants, including three Callaghan Innovation R&D Student-Fellow Grants, an External Fund for Multidisciplinary Computational Anatomy, a Collaborative Research, Innovation and Development Programme grant, etc.

Invited Speaker III

Prof. Chuan-Ming Liu

National Taipei University of Technology, Taiwan

Dr. Chuan-Ming Liu is a professor in the Department of Computer Science and Information Engineering (CSIE), National Taipei University of Technology (Taipei Tech), Taiwan, where he was the Department Chair from 2013-2017 as well as the Head of the Extension Education Center at the same school from 2018-2021. Dr. Liu received his Ph.D. in Computer Science from Purdue University in 2002 and joined the CSIE Department in Taipei Tech in the spring of 2003. In 2010 and 2011, he has held visiting appointments with Auburn University, Auburn, AL, USA, and the Beijing Institute of Technology, Beijing, China. He has services in many journals, conferences and societies as well as published more than 100 papers in many prestigious journals and international conferences. Dr. Liu was the co-recipients of many best paper awards, including ICUFN 2015, ICS 2016, MC 2017, WOCC 2018, MC 2019, MC 2021, and WOCC 2021. His current research interests include big data management and processing, uncertain data management, data science, spatial data processing, data streams, ad-hoc and sensor networks, location-based services.

Invited Speaker IV

Assoc. Prof. Hai Van Pham

Hanoi University of Science and Technology, Vietnam

Hai Van Pham is received Doctor of Engineering degree (Ph.D.) at Ritsumeikan University (Japan) in 2013. He is currently an Associate Professor at School of Information and Communication Technology, Hanoi University of Science and Technology. His major includes Artificial Intelligence, Big data, Soft Computing, Machine learning and Fuzzy Systems. He also serves as Chairs and Co-chairs of organized several sessions at international conferences such as KSE 2021, KSE 2019, KSE 2017, KSE 2015, SOICT 2014, etc. His publications are over 100 research papers in Artificial Intelligence with 60 publications in ISI indices. He is an expert of International projects such as WB experts, FORMIS II, MOC02-WB, and US Asian Foundation, in previous years, conducting in applied AI international and domestic projects and applications.

Speech Title: "Applied AI in Healthcare in Covid-19 Pandemic"

Abstract: Recently, AI technologies and tools play a key role in every aspect of the COVID-19 pandemic. AI tools and techniques can support policymakers and medical doctors identify COVID-19 virus together with treatments by rapidly the world. The purpose of this talks is to give an overviews of applied AI in COVID-19 pandemic in detecting, diagnosing the virus, predicting its evolution monitoring the recovery and improving early warning tools. In addition, an assistance of preventing virus' spread is through surveillance and contact tracing human. This talks are also given in demonstrations of COVID applications in real-world problems to show how combined engineering and science in new challenges of Covid-19 pandemic.

 

Invited Speakers of ICIIT 2022

 

Prof. Xingbo Wang

Foshan University, China

Dr. & Prof. Xingbo Wang got his Master and Doctor’s degrees at National University of Defense Technology (NUDT) of China. Since 1994, he had worked at NUDT on CAD/CAM/CNC technologies till 2010. Since 2010, he has been a professor in Foshan University with research interests in intelligent manufacturing system and computer applications. Prof. Wang is now in charge of Guangdong Engineering Center of Information Security for Intelligent Manufacturing System, where a lot of cryptography problems have to be dealt with the elementary number theory. He then set up a new method to study odd integers by means of perfect full binary tree and derived out many new properties of the odd integers, including genetic property that makes it easier to factorize an odd integer. Now Prof. Wang is devoting himself to developing a fast algorithm to integer factorization and intending to solve the hard problem of integer factorization.

Speech Title: "Progress in Applying Valuated Binary Tree to Factorize Big Integers"

Abstract: Finding new methods to solve the hard problem of integer factorization has gone on for tens of years in cryptography but better methods are still in need. Even in the era of quantum computing, conventional approaches are necessary as a part of science researches. The method derived from valuated binary tree, which was raised in 2016, has revealed rigorous power in studying odd integers. This paper overviews the method from its origination to its achievements so as to make people know the method well. Four characteristics of symmetric property, genetic property, boundary property and connection property are introduced with their main traits. Achievements are exhibited briefly in integer factorization of both general purpose and special purpose. The paper shows that, the new method might be rigorous and prosperous in the future.

Assoc. Prof. Xiaolong Li

University of Electronic Science and Technology of China, China

Xiaolong Li was born in Jiangxi, China. He received the B.S. and the Ph.D. degrees from the University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2011 and 2017, respectively. Since 2017, he has been a Faculty at the School of Information and Communication Engineering, UESTC. From 2018 to 2019, he was a Visiting Researcher with the Department of Electrical and Computer Engineering, National University of Singapore, Singapore. He is currently an Associate Professor at UESTC. His research interests include radar moving target detection, weak signal parameter estimation, and MIMO radar signal processing and radar imaging, with an emphasis on coherent integration technique for high speed maneuvering target detection. He was the recipient of the Prize for Excellent Ph.D. degree dissertation of the Chinese Institute of Electronics in 2017. In 2020, he was selected in the Young Talents Program of the China Association for Science and Technology. He was the Section Chair of the 2019 ICCAIS, 2020 IET International Radar Conference, and 2021 CIE International Conference on Radar. He is the Guest Editor of the Journal of Radars and frequently a Reviewer of IEEE TSP, IEEE TGRS, IEEE GRSL, SP, DSP, and many international conferences.

Speech Title: "Signal Integration Processing Method for Radar High Speed Moving Target Detection"

Abstract: With the development of science technology, more and more moving objects with high speed appear in the radar detection filed. These moving targets are often with fast flight velocity, long attack range and strong stealth ability, which bring great challenges to modern radar signal processing field. How to improve the radar detection ability for the high-speed moving targets also attracts much attentions in the recent years. It is well-known that the signal-to-noise ratio (SNR) of radar returns and detection performance could be enhanced significantly via long-time signal integration of different sampling pulses. However, because of the target’s high velocity and maneuverability, some issues, such as range migration and Doppler spread, should be addressed within the l signal integration processing. Otherwise, the integration performance of traditional moving target detection (MTD) algorithm will be severely degraded. In this presentation, we will analyze the problems of high-speed target coherent integration processing and establish the corresponding target echo signal model. At the same time, we will introduce the research progress of our group in signal coherent integration processing area.