QUEEN’S BUSINESS SCHOOL INFORMATION TECHNOOGY, ANALYTICS & OPERATIONS (ITAO) SEMINAR SERIES

Thursday 5^th March

12pm

“Transforming SCOPE 3 Emissions Reporting with AI-Driven Decision Support”

Christos Papadopoulos – Filelis

Democritus University of Thrace

Abstract

CSRD compliance is raising the bar for corporate sustainability reporting, particularly in the measurement and disclosure of Scope 3 emissions. Companies face increasing regulatory scrutiny, significant penalties for non-compliance, and mounting operational complexity. Manual data collection across fragmented supplier networks, inconsistent emissions factors, and unstructured documentation makes Scope 3 reporting time-consuming, error-prone, and difficult to audit. At the same time, the lack of real-time emissions visibility limits informed procurement and strategic decision-making.

This talk introduces an AI-powered system that combines structured enterprise data with unstructured emissions tables, standards, and documentation using a Retrieval-Augmented Generation (RAG) architecture. The platform enables real-time, product-level Scope 3 tracking, automatically flags potential miscalculations, and suggests corrections aligned with GHG Protocol and IPCC methodologies. By embedding validation, auditability, and tokenized data integrity into the workflow, the system transforms emissions reporting from a compliance burden into a reliable, decision-ready intelligence layer.

Short Bio

Christos K. Filelis - Papadopoulos is an Assistant Professor in the Department of Electrical and Computer Engineering at the Democritus University of Thrace, specializing in Mathematical and Computational Physics. He holds a Diploma (2005–2010) and a PhD (2010–2014) in Electrical and Computer Engineering from the same institution awarded with distinction.

His research focuses on high-performance computing, numerical linear algebra, parallel and distributed algorithms, cloud computing, and large-scale simulation. He has authored a significant number of publications in leading international journals and conferences and has contributed to major EU-funded projects including CloudLightning, GHOST and RECAP as well as SFI funded projects, namely FINTECHNEXT, focusing on subjects such as Cloud and Edge Computing, Big Data, Large Scale Simulation, Machine Learning and FinTech. His work spans advanced computational methods, sparse approximate inverse preconditioning, multilevel techniques, time-series modeling, cloud-scale resource optimization, machine learning methods, computational physics and high performance computing. He is the author of more than 90 scientific papers in peer-reviewed International Journals and Conferences.

Dr. Filelis - Papadopoulos has extensive teaching experience at undergraduate and postgraduate levels, has supervised PhD, MSc and diploma theses, and actively contributes to the academic community as a reviewer, program committee member, and guest editor for international journals and conferences.

QBS Student Hub, Executive Education Flexible Teaching Space, 01.019

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