• Smart-contract Language
• Distributed Ledger Technology
• Blockchain Systems
• Ontology Engineering
• Business Processes
• Consensus Algorithms
• Requirement Engineering
• Digital Twins
• Digital Image Processing

• Best paper award at 9th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA 2021)
• Received IT Academia scholarship 
• Received XRP Ledger Trust scholarship 
• Received AICTE PG (GATE) Scholarship
• Received a grant of 75000 euro by European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 957338 for the project title "Multi-Factor Self-Sovereign Identity Authentication"

Vimal Dwivedi received the PhD and in Computer Science and Engineering from Tallin University of Technology, Tallinn, Estonia. His PhD project was partially sponshered by Qtum foundation, Singapore. As a part of Ph.D. research, he has developed a XML-based smart contract language that allows non-IT blockchain practioners to write smart contract for buisness use cases. He is working as a Research Fellow in the School of Electronics, Electrical Engineering and Computer Science (EEECS) at the Queen's University Belfast (QUB), Northern Ireland, United Kingdom, with Prof. Karen and Assistant Professor Vishal Sharma, under a project entitled, Digital twin and blockchain for business decision modeling. Before coming to QUB, he was a Lecturer in the Institute of computer science at the University of Tartu, Tartu, Estonia. Prior to this, he was an Early Stage Researcher with the Information Systems Group at TalTech. He serves as an Guest Editor for Mathematics and Computer Science.

Vimal received his MTech and BTech degrees in Computer Science and Engineering from Guru Gobind Singh Indraprastha University, India and Dr. A.P.J. Abdul Kalam Technical University, India, respectively. Before starting his Ph.D., He worked as an Assistant Professor at A.P.J. Abdul Kalam Technical University for 2 years, and taught subjects including Automata, Data Structure, Graph Theory, Machine Learning and Web Technologies.