💢 Very exciting email today from the Journal of Forecasting!
💢 A distinction for our research team, as our paper is among the 10 most cited papers in the Journal of Forecasting!
Our paper link: https://lnkd.in/dq3EJ7Ar
Machine Learning
Complex Networks
Econometrics
Great News!
💢 Very exciting email today from the Journal of Forecasting!
💢 A distinction for our research team, as our paper is among the 10 most cited papers in the Journal of Forecasting!
Our paper link: https://lnkd.in/dq3EJ7Ar
Welcome to the official page of the Emerging Methodologies in Economics and Finance (EMEF) Lab at Democritus University of Thrace!
Our lab is at the forefront of innovative research, bridging theoretical insights and practical applications in the fields of economics and finance. Here, professors, students, researchers, and industry professionals collaborate to tackle complex economic challenges and contribute to the global dialogue on economic policy and strategy.
Explore our projects, publications, and opportunities to get involved in our dynamic and impactful community.
THE TEAM. Our research team operates within the Department of Economics, Democritus University of Thrace, Greece. Our research efforts were funded by a Research Grant from the European Union (Research Funding Program THALES) under the title “Study and Forecasting of Economic Data Using Machine Learning”, MIS 380292. Also, two PhD candidates are funded for their research from Hellenic Foundation for Research & Innovation (H.F.R.I.) and State Scholarship Foundation (ΙΚΥ).
MEMBERS. The research team is led by professors Periklis Gogas an economist (B.A., M.A., Ph.D.) and Theophilos Papadimitriou a mathematician (B.A.) and electrical engineer (M.Sc., Ph.D).
Researchers, Post Docs and PhD candidates are actively working for the team.
RESEARCH INTERESTS. Our group's research interests include both classic Econometrics and also emerging methodologies of as they are applied to Economics and Finance. We currently work with: a) Machine Learning: Support Vector Machines for Classification and Regression and Deep Learning Architectures and b) Complex Networks: Threshold – Minimum Dominating Set, Weighted Dominating Set, and Multivariate Networks.