Prof Victor Chang
Aston University, Teesside University
Research areas: Computer Science · Information Systems · Cloud Computing and Resource Management · IoT and Edge/Fog Computing · Cloud Data Security Solutions
0000-0002-8012-5852
About
Prof. Victor Chang is a Professor of Business Analytics at Aston Business School, Aston University, UK since mid-May 2022. He will be involved in a leading a Research Center later on. He was previously a Professor of Data Science and Information Systems at the School of Computing and Digital Technologies, Teesside University, UK. He led Cybersecurity, Information Systems and AI Research Group at Teesside University.
He was a Senior Associate Professor, Director of Ph.D. (June 2016- May 2018) and Director of MRes (Sep 2017 - Feb 2019) at International Business School Suzhou (IBSS), Xi'an Jiaotong-Liverpool University (XJTLU), Suzhou, China, between June 2016 and August 2019. He was also a very active and contributing key member at the Research Institute of Big Data Analytics (RIBDA), XJTLU. He was an Honorary Associate Professor at the University of Liverpool. Previously he was a Senior Lecturer at Leeds Beckett University, UK, between Sep 2012 and May 2016. Within 4 years, he completed Ph.D. (CS, Southampton) and PGCert (Higher Education, Fellow, Greenwich) while working on several projects at the same time. Before becoming an academic, he achieved 97% on average in 27 IT certifications. He won a European Award on Cloud Migration in 2011, IEEE Outstanding Service Award in 2015, best papers in 2012, 2015 and 2018, the 2016 European special award, Outstanding Young Scientist 2017 and INSTICC Service Award 2017-2021. He is a visiting scholar/Ph.D. examiner at several universities, an Editor-in-Chief of IJOCI & OJBD journals, former Editor of FGCS, Associate Editor of IEEE TII, JGIM, Expert Systems, IJBSR and IJEBM, Cybersecurity & Applications journals, & Editor of Information Fusion, Scientific Report and IDD journals, founding chair of two international workshops and founding Conference Chair of IoTBDS and COMPLEXIS since the Year 2016. He has been the founding Conference Chair for FEMIB since the Year 2019.
Prof Chang published 3 books as sole author and the editor of 2 books on Cloud Computing and related technologies. He published 2 books on COVID-19, 1 book on web development and 1 book on Neo4j. He gave 30 keynotes at international conferences. He is in the Top 2% of Scientists in 2017/2018, 2019/2020 and 2020/2021 periods. He is a Highly Cited Researcher awarded by Clarivate Analytics in 2021. He is widely regarded as one of the most active and influential young scientists and experts in IoT/Data Science/Cloud/security/AI/IS, as he has the experience to develop ten different services for multiple disciplines.
Prof Chang is one of the most highly cited researchers apart from being an international leading young scientist with reputation and track records. He worked on every project with details known. He is a highly efficient, effective, organized, responsible and self-disciplined scholar to make things happen. His most recent publications can be viewed: https://scholar.google.com/citations?hl=en&user=IqIYZ14AAAAJ&view_op=list_works&sortby=pubdate
His focus will be on funding and building more funded projects between academia, and between academia and industry.
Employment
- 2022 - Present
- ? - 2022
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (461)
- Continual graph learning: A survey Save
- CPFTransGAN: A Cross Perception Fusion Transformer-Based Generative Adversarial Network for Head and Neck Cancer Dose Prediction in Radiotherapy Save
- DEFF: A Distributed Edge Fusion Framework for Cybersecurity Incident Prediction Save
- Prediction of bank credit worthiness through credit risk analysis: an explainable machine learning study Save
- EarlyBirdFL: Leveraging Early Bird Ticket Networks for Enhanced Personalized Learning Save
- FaRS: A Performance-Driven Approach to Role Similarity in Graphs Save
- Introduction to the Special Issue on Big Data and the Internet of Things in Complex Information Systems Save
- Leveraging asymmetric price limits for financial stability in industrial applications: An agent-based model Save
- Towards an Open Science—An Academic Recommendation Cloud Platform Save
- A fair multi-attribute data transaction mechanism supporting cross-chain Save
- A Systematic Review of Working Memory Applications for Children with Learning Difficulties: Transfer Outcomes and Design Principles Save
- Credit Risk Prediction Using Machine Learning and Deep Learning: A Study on Credit Card Customers Save
- Machine Learning for Predicting Tourist Spots' Preference and Analysing Future Tourism Trends in Bangladesh Save
- Predicting Economic Trends and Stock Market Prices with Deep Learning and Advanced Machine Learning Techniques Save
- Football Analytics: Assessing the Correlation between Workload, Injury and Performance of Football Players in the English Premier League Save
- Investigating Credit Card Payment Fraud with Detection Methods Using Advanced Machine Learning Save
- Graph Sparsification-Based Secure Federated Learning for Consumer-Driven Internet of Things Save
- Credit Risk Evaluation on Technological SMEs in China Save
- Towards data and analytics driven B2B-banking for green finance: A cross-selling use case study Save
- The Ensemble Learners: Machine Learning Classification of Diabetic Patient Readmission Save