AI for Energy Finance (AI4EFin)

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Mini Track Chair:

Stefan LESSMANN, Humboldt-Universität zu Berlin, Germany
Roxana CLODNITCHI, Bucharest University of Economic Studies, Romania

Energy finance highlights the interdependency of energy and financial markets. While the traditional viewpoint of energy markets being a source of shocks in financial markets remains valid, the increasing financialization of energy products renders the linkage between those markets far more complex. Understanding these relationships and answering the crucial question of how to fuel world economies’ hunger for energy while decreasing greenhouse gas emissions requires a new family of tools that turn the vast amounts of data in the energy finance ecosystem into insights for decision-making and ultimately enhance the efficiency, resilience, and sustainability of energy operations and their financing. The initiative AI for Energy Finance (AI4EFin) speaks to these challenges. Within the session and the like-named Research Project, we are exploring novel machine learning (ML) and artificial intelligence (AI) instruments for pattern extraction, explanation, and forecasting of the high-dimensional, nonstationary, temporal data encountered in energy finance.

Beyond their merit for risk management, the research findings should also guide policymakers in devising/revising regulatory programs and other market interventions, and facilitate estimating the effectiveness of these interventions.

The main topics covered by the hereby call for papers are related to:

Energy Finance
Artificial Intelligence
Explainable deep neural networks
Machine Learning
Risk management

Stefan LESSMANN
completed his PhD and habilitation at the University of Hamburg in 2007 and 2012, respectively. He then joined the Humboldt-University of Berlin in 2014, where he heads the Chair of Information Systems. He serves as an associate editor for DSS, IJF, and other international journals and department editor of BISE. Stefan has secured substantial amounts of research funding and published several papers in leading international (EJOR, DSS, TSE, etc.) and conferences (ICML, ICIS, ECOS, etc. His research concerns machine learning and artificial intelligence (MLAI) methodologies and their use cases in managerial decision support. Stefan specializes on MLAI applications in the broad scope of marketing and risk analytics. Stefan actively participates in knowledge transfer and consulting projects with industry partners; from start-up companies to global players and not-for-profit organizations.

Roxana CLODNITCHI
is a University Lecturer and Vice-Dan for Research and International Relations of the Faculty of Business Administration in Foreign Languages, within the Bucharest University of Economic Studies. She holds a PhD in Business Administration and has more than 10 years of experience in International Project Management, Communication and Business Consulting with the European Commission and the German Chamber of Commerce in Romania. Within the Bucharest University of Economic Studies, Dr. Clodnitchi was active for years as a guest lecturer in Decision Theory, Strategies and Entrepreneurship with focus on Energy Economics and also as a Business Relations Officer.