Md Mostafizur Rahman, a student in the Department of Management Information Systems at Lamar University, Texas, has been recognised as a co-author of a Best Paper Award-winning research paper at the 8th International Conference on Smart Computing and Informatics (SCI-2026).

The conference was held at Swinburne Vietnam, Hanoi Location, Vietnam, on 28–29 April 2026. The award-winning paper, titled “Neuro-Symbolic Financial Fraud Analytics Using Decentralised Ledger Intelligence and Graph Attention Networks”, was presented at the international conference and received the Best Paper Award from the conference committee.

Rahman was among the authors representing Lamar University’s Department of Management Information Systems, alongside researchers from institutions including the University of Dhaka, Jahangirnagar University, Bangladesh Army University of Engineering & Technology, and Lamar University.

The research explores advanced financial fraud detection by integrating neuro-symbolic analytics, decentralised ledger intelligence, and graph attention networks. The study reflects the increasing importance of artificial intelligence, data analytics, and financial technology in identifying complex fraud patterns and enhancing decision-making processes within financial systems.

According to the conference organisers, the paper is currently under editorial production by Springer Nature for publication in the Springer Lecture Notes in Networks and Systems (LNNS) series, which is indexed in Scopus.

Rahman stated that the recognition represents an important milestone in his academic and professional journey. With a background spanning business, marketing, management information systems, data analytics, and financial technology, he aims to continue contributing to research that connects AI-driven analytics with real-world business and financial challenges.

The award further highlights his growing involvement in international research and strengthens his academic profile in the areas of management information systems, artificial intelligence, financial fraud analytics, and data-driven decision support.