2023 4th International Conference on Big Data and Social Sciences (ICBDSS 2023)
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Prof. You-Gan Wang

Australian Catholic University, Australia

Research Area:machine learning; statistics. 

Brief:Professor You-Gan Wang 's research interests include developing statistical methodology in the main stream of statistics for analysing correlated data including longitudinal data and time series, robust inferences and model selection and applying advanced techniques that help to solve important problems in environmental research, medical sciences and social sciences. His work is published in top journals in statistics, engineering, hydrology, biology, and medicine. He is a leading author of a recent book Longitudinal Data Analysis with Examples (2022). His current interests include (1) ‘working’ likelihood approach for hyperparameter estimation in machine learning and statistical model selection, (2) integrating statistical learning and machine learning for dependent data analysis and (3) data-driven approach for robust estimation. More recently, he advocates ‘working’ likelihood approaches to parameter estimation but recognizing possibly a different likelihood that generating the observed data in inferencing. This has been found very useful in finding data-dependent tuning parameters in robust estimation and hyper-parameters in machine learning algorithms. He has extensive collaborative relationships internationally. He and his proposed team work on robust statistical modelling for time-series data analysis and demonstrating the power of statistical modelling and the advantages of machine learning. Professor Wang has been invited on a number of occasions to organize/speak at international conferences and to review journal papers. His work has substantial impacts and scientific innovations in statistical modelling and data science. Professor Wang has published 160+ papers in international journals with more than 4,000 SCI citations.

Title: Contemporary Challenges in Applying Data Science to Social Sciences

Abstract: In this presentation, I delve into the dynamic field of data science as it intersects with social sciences, highlighting pertinent challenges and exploring statistical aspects alongside machine learning algorithms. I focus on modern obstacles, including the implications of dataset size, complexity in structures, attribute abundance, and potential sample bias. Emphasizing the importance of statistical considerations, I introduce the utilization of the Lasso technique for variable selection, offering a pathway to dimension reduction applicable not only within statistical frameworks but also within machine learning paradigms. I will also  address a central concern: uncertainty quantification, which plays a pivotal role in the accurate interpretation of data-driven results. This concept is pivotal for enhancing the reliability of insights gained from data analysis. In terms of methodology, I contrast two prevalent approaches: the model-free strategy of nested cross-validation, widely adopted within machine learning, and the model-based inference approach, which holds a significant place in the domain of statistics. By navigating through these challenges and methodologies, my presentation offers a comprehensive perspective on the intersection of data science and social sciences, shedding light on effective strategies to harness the power of data for informed decision-making and understanding complex societal phenomena.


Prof. Neema Ghenim

Oran 2 University Mohamed Ben Ahmed, Algeria

Research Area:Comparative Literature, Culture, History, Art, Communication, Teaching English. 

Title:Exploring Big Data for Social Science Research in Algeria: Pushing the Door of Opportunities and Challenges

Abstract: Big data is revolutionizing social study research in many countries in the world, it is becoming a door of opportunities to analyze social phenomena. Algeria, with its immense heritage, has got a huge potential regarding the use of big data in the development of social science with all the expansion of the internet and digital platforms. My article aims to explore the existing research based on big data and the potential growth of this innovative practice in the study of social phenomena and its possible contribution to effective research and policymaking. Also, my article will explore the benefits of big data in the decolonization of social science as there is an essential burden for this kind of change to rediscover native knowledge that has been repressed during colonization. Emerging local data infrastructure will empower social science by seizing cultural and religious practices and getting insight into some historical biases to test the validity of dominant narratives and contribute to effective decolonization. My article will finally tackle the possible drawback of the promotion of big data in Algeria and the possible misuse of these advanced analytics techniques as it is important to be vigilant in terms of ethics and privacy protection to avoid all kinds of deviation from this revolutionizing practice in social science. 


Prof. HongbingCheng

College of Computer Science and Technology College of Software, Zhejiang University of Technology, China

Research Area: Blockchain technology, network security, cloud privacy protection

Brief: Hongbing Cheng (Member IEEE) is a Professor of School of Computer Science, Zhejiang University of Technology; he received the Ph.D. degree from the Nanjing University of Posts and Telecommunications and completed post-doctoral research in the State Key Laboratory of New Software Technology of Nanjing University. He has published more than 100 technical papers at different venues, such as IEEE ToN, TFS, TSC, TIFS, TNSM, and ICDCS, ICC. Prof. Cheng served as invited editor of several international journals in some international conferences; and has been invited to give keynote speeches and chair committees, reviewed papers for many international journals and conferences. His research interests include blockchain, cryptography, privacy preserving and information security, computer communications and cloud computing security.

Title: The concept, application, and security of big data

Abstract: This presentation will provide detailed analysis and explanation from the perspectives of big data concepts, analysis techniques, and applications. At the same time, it will elaborate on the application fields of big data, and finally, it will preliminarily explore the security and privacy issues in the applications of big data.


A. Prof. Irene Ting Wei Kiong 

Faculty of Industrial Management, Universiti Malaysia Pahang (UMP), Malaysia

Research Area:Contemporary Issues in Finance, Financial Management, Financial Management for Accounting, Financial Markets & Institutions, International Finance, Financial Statement Analysis, Principles of Finance and Investment Analysis

Brief: Dr. Irene Wei Kiong Ting is an associate professor of Finance at Faculty of Industrial Management, Universiti Malaysia Pahang (UMP), Malaysia. She has spent almost two decades in teaching finance courses at tertiary level. She has been teaching at universities since 2007, most of which were Finance subjects such as Contemporary Issues in Finance, Financial Management, Financial Management for Accounting, Financial Markets & Institutions, International Finance, Financial Statement Analysis, Principles of Finance and Investment Analysis, to name just a few. She also taught research methodology at a part-time basis for a semester recently at the postgraduate level. With approximately 20 years of teaching experience, she is adept in teaching skills, teaching-portfolio development skills and supervision skills for research projects. Besides, she has published extensively in top journals, with focuses on performance management, behavioural finance, corporate governance, intellectual capital, capital structure etc. She has received several best paper awards for her research works from various international conferences. She has yielded a well-rounded set of skills via her on-the-job, particularly the experiences being the Deputy Dean of Research and Postgraduate, Director of International Rankings and Branding Division, Director of Career Placement and Development Centre.