Our Speakers



Assoc. Prof. Zhao-Rong Lai

Jinan University, China

Zhao-Rong Lai is currently an associate professor with the Department of Mathematics, College of Information Science and Technology, Jinan University. His current research interests include mathematical programming, machine learning, and mathematical finance. Ahead of the career in Jinan University, he was an industry manager with the Departments of Corporate Financing and Investment Banking, Industrial and Commercial Bank of China, Guangdong Headquarter.

He is the FIRST AUTHOR of 9 journal papers in Journal of Machine Learning Research (JMLR, top-ranked, 2 papers), IEEE Transactions on Neural Networks and Learning Systems (TNNLS, 2 papers), IEEE Transactions on Cybernetics (TCYB), IEEE Transactions on Image Processing (TIP, 2 papers), Data Mining and Knowledge Discovery (DMKD), and IEEE Transactions on Systems, Man and Cybernetics: Systems (TSMC-S). He is the corresponding author of 1 journal paper in Pattern Recognition (PR).

He is an invited senior program committee member for the top-ranked AI conferences IJCAI 2020 and IJCAI 2021, and a program committee member for IJCAI 2018, IJCAI2019, AAAI2019, AAAI2020, and AAAI2021. He is also an invited reviewer for IEEE TNNLS and IEEE TKDE (Transactions on Knowledge and Data Engineering). He is a member of IEEE.

Topic: Machine Learning Methods for Portfolio Optimization based on the Exponential Growth Rate Model


Abstract: Portfolio optimization (PO) has caught significant attention from both academics and practitioners since the proposal of the mean-variance approach. On the other hand, the exponential growth rate (EGR) approach for PO focuses on the wealth change along with time, which originates from the Kelly's criterion in the information theory. Recently, many machine learning methods based on EGR have motivated a hot topic in PO. This speech introduces the concept of EGR and several state-of-the-art machine learning methods for PO, and illustrates the differences between them and the traditional mean-variance methods.

 

Assoc. Prof. João Alexandre Lobo Marques

University of Saint Joseph, Macau, China

Associate Professor at the University of Saint Joseph - USJ, Macau SAR, China (2017-). Visiting Associate Professor at the Chinese Academy of Sciences (CAS) - Shenzhen Institutes of Advanced Technologies (SIAT) (2018-). Post Doctorate and Honorary Research Fellow from the University of Leicester-UK. Adjunct Professor - Federal Institute of Education, Science, and Technology (IFCE) – Brazil. Member of the Board of Advisors - Master in Global Marketing Management - Boston University Metropolitan College (BU-MET) – USA. PhD in Engineering. Has large experience in Artificial Intelligence, Data Sciences, Big Data, Business Analytics and Applied Mathematics developing and managing applied research in different areas of management, engineering, health and others. Experience in designing new Undergrad and Post Graduate programs. Solid international career with academic positions and relevant research developed in Asia (China), Europe (England, Germany and Portugal), Africa (Angola) and America (United States and Brazil). Strong leadership and team development skills in several international research projects. Author of 5 books (Book Author and Book Chapter Author). More than 80 papers published in high impact international journals such as IEEE, ELSEVIER, NATURE, SPRINGER, among others and relevant international conferences. IEEE Member. Highly skilled in software design and development in different platforms such as Python, C++, R scripting, etc. Specialist in Project Management frameworks application in international projects, including PMBOK and Agile. More than 2,000 professionals trained in Brazil, Portugal, Angola and China.

Topic: Neuroeconomics Applications based on Multiple Monitoring Tools


Abstract: The development of experimental research based on the participant biosignals monitoring in real-time is a key challenge to improve effectiveness and reliability in economics and marketing research areas. In this presentation we are going to present the Neuroeconomics Lab at the University of Saint Joseph, in Macau SAR, China. Different biometrics are measured in parallel, such as eye tracking, facial expressions recognition to identify emotions, electrodermal activity (EDA), heart rate and electroencephalogram (EEG). A specific module for EEG analysis was developed and validated. The synchronization platform is based on the iMotions software. Promising preliminary results obtained for researches with international collaborations from Brazil and Portugal are presented, such as: website communication effectiveness; analysis of tourism advertisement; decision making; branding and consumer awareness, among others.

 

Assoc. Prof. Bambang Leo Handoko

Bina Nusantara University, Indonesia

Associate Professor Bambang Leo Handoko, academics and practitioners in the field of Auditing. Experience as auditor in public accounting firm, internal auditor for corporations and auditor for securing vital objects of the National Police Headquarters. He is an expert in financial auditing, forensic accounting, information technology auditing and also e-business. He has had many international publications in reputable journals and proceedings with many citation and acknowledgement from international researchers. He had won a lot of research grant from institution and government. Currently work as Subject Content Coordinator Auditing in Accounting Department, Faculty of Economic and Communication, Bina Nusantara University of Indonesia. He also technical committee in many reputable journal publisher and earn Scopus hi Index.

Topic: Robotic Process Automation in Audit 4.0

Abstract: Currently we have entered the era of the industrial revolution 4.0 where all aspects of the business have changed, including auditing. Manual audits are increasingly being abandoned, currently referred to as audit 4.0, which is characterized by automation in the inspection and audit process. Audit has long used a computerized system, as stated in the audit standard, that one of the audit procedures is computer assisted audit techniques, which is software that is executed by the auditor. However, in this era of 4.0, software has again evolved into a robot, which can carry out the audit process itself automatically without having to be run by humans like generalized audit software. Our research discusses the development of the robotic auditing process, we use a descriptive qualitative approach. We used primary data obtained from inquiry and literature review. Our research results state that although the auditing process automation robot has many advantages including being able to lighten the work of auditors, increase efficiency and effectiveness, there are also weaknesses and challenges that must be addressed, such as resistance from the auditors themselves and issues of legality, legal liability and responsibility of robot if negligence occurs.