11.11.2025: Vortrag von Gastwissenschaftler Prof. Dr. George Mengov „Socioeconomic Forecasting in Turbulent Times”

30. Oktober 2025

english version below

Im November 2025 ist Prof. Dr. George Mengov zu Gast bei uns am Fachbereich Sozialökonomie. Er ist Professor für Entscheidungswissenschaften an der Fakultät für Wirtschaftswissenschaften und Betriebswirtschaftslehre der Universität Sofia St. Kliment Ohridski. Prof. Dr. George Mengov hat zahlreiche Beiträge zu seinen Forschungsschwerpunkten in Büchern und (internationalen) Fachzeitschriften veröffentlicht. Er promovierte 2001 in Angewandter Kybernetik an der Technischen Universität Sofia. Von 2001 bis 2004 war er wissenschaftlicher Mitarbeiter an der Bulgarischen Akademie der Wissenschaften. Zuvor war er von 1995 bis 2000 als IT-Berater bei Unisys Corporation tätig und arbeitete an Projekten zur Entwicklung von Finanzsoftware in der City of London, Leeds, Sofia und St. Petersburg. Er ist Mitglied des Beirats des Swiss Innovation Valley, einem IT-Gründerzentrum.

Der Aufenthalt von Prof. Dr. George Mengov bei uns erfolgt im Rahmen der DAAD-Förderlinie "Ostpartnerschaften“ und wird durch Prof. Dr. Ulrich Fritsche unterstützt.

Herzlich willkommen!

Es besteht die Möglichkeit, Herrn Mengov bei einem öffentlichen Vortrag kennenzulernen und mit ihm zu diskutieren. Alle Interessierten sind hierzu herzlich eingeladen:

• Prof. Dr. George Mengov
• Thema: „Socioeconomic Forecasting in Turbulent Times: A Neurocomputational Approach“
• Termin: 11.11.2025, ab 15 Uhr
• Ort: Welckerstraße 8, Raum 2.16

Der Vortrag wird auf Englisch stattfinden. Mehr Informationen zum Vortrag.

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November 11, 2025: Lecture by visiting scholar Prof. Dr. George Mengov, “Socioeconomic Forecasting in Turbulent Times”

In November 2025, Prof. Dr. George Mengov will be visiting our Department of Social Economics. He is Professor of Decision Sciences in the Faculty of Economics and Business Administration at Sofia University St. Kliment Ohridski. Prof. Dr. George Mengov has published numerous articles on his main areas of research in books and (international) journals.He completed his Ph.D. in Applied Cybernetics at Technical University of Sofia in 2001. During 2001–2004 he was a Research Associate at the Bulgarian Academy of Sciences. Previously, he was IT consultant in Unisys Corporation (1995–2000) working on projects for financial software development in the City of London, Leeds, Sofia, and St. Petersburg. He is a member of the Advisory Board of Swiss Innovation Valley, an IT business incubator. 

Prof. Dr. George Mengov's stay with us is part of the DAAD's “Eastern Partnerships” funding program and is supported by Prof. Dr. Ulrich Fritsche.

Welcome!

There will be an opportunity to meet Mr. Mengov at a public lecture and discuss with him. All interested parties are cordially invited to attend:

• Prof. Dr. George Mengov
• Topic: “Socioeconomic Forecasting in Turbulent Times: A Neurocomputational Approach”
• Date: November 11, 2025, starting at 3 p.m.
• Welckerstraße 8, room 2.16

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Socioeconomic Forecasting in Turbulent Times: A Neurocomputational Approach

The advent of versatile big data, powerful computing capabilities, and machine learning algorithms created new opportunities for analysis and understanding of the socioeconomic reality. Neural networks have been at the forefront of this progress. Their ability to deal with noisy and imprecise data, and their modelling flexibility, made them quite useful in forecasting business, economic, and social processes.

This talk presents a set of neural models, successfully applied in problems of macroeconomics, international trade, economic choice predictability, and human work motivation. They are based on mathematical neuroscience and are closer to the actual brain mechanisms than some widely used deep neural networks. With their help, a variety of new findings emerged: (1) When people take economic decisions in a virtual social network, they become more predictable; (2) Under economic shocks, neurocomputational forecasting is as good as the state-of-the-art econometric models; (3) In turbulent times, human work characteristics, attitudes, and dispositions remain stable, yet the employees rethink unpredictably their commitment, loyalty, and overall relationship with their organization. For some of these results a new computationally efficient, explainable, and novelty-detecting neural network was used for the first time.