Anton Evgrafov is an Associate Professor in the Department of Mathematical Sciences at Aalborg University (AAU), affiliated with The Faculty of Engineering and Science. His research focuses on optimal design, nonlocal nonlinear diffusion, and control theory, with applications in electrical engineering and material science. He holds a Ph.D. in Applied Mathematics from Chalmers University of Technology (2004), specializing in topology optimization problems. Key contributions include advancements in nonlocal complementary energy principles, dual approaches to optimal control, and sparsity-promoting evaluation methods for power semiconductors. Research interests span nonlocal mechanics, peridynamics, and computational methods for engineering systems. Recent work emphasizes energy minimization principles, coefficient optimization in nonlinear systems, and design under vanishing material constraints. He actively participates in conferences and workshops, such as EUROMECH Colloquium 643 and the Qiskit Global Summer School, and delivers guest lectures on topics like nonlocal bond-based peridynamic diffusion.
Carsten Witt is a Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), working within the Algorithms, Logic and Graphs section. His research is centered on theoretical aspects of evolutionary computation, with a strong emphasis on runtime analysis, genetic algorithms, and randomized search heuristics. He is actively involved in guiding PhD research and has a substantial publication record in top-tier conferences and journals. PhD in Computer Science, Technical University of Dortmund, Germany Postdoctoral research at Max Planck Institute for Informatics Professor at DTU since appointment His primary research interests lie in evolutionary algorithms , runtime analysis , and probability theory in algorithmics . He investigates how bio-inspired optimization techniques such as genetic and compact genetic algorithms perform on benchmark problems like OneMax and LeadingOnes. His work often involves rigorous mathematical analysis to derive bounds on expected runtime and convergence behavior. The recent articles show a consistent trend in the theoretical foundations of evolutionary computation , particularly focusing on multi-valued representations, dynamic mutation strategies, neuroevolution models, and self-adjusting mechanisms. These works span subfields such as stochastic optimization, adaptive parameter control, and algorithmic analysis under probabilistic models. The dominant keywords include Computer Science, Theoretical Computer Science, Optimization, and Artificial Intelligence. Carsten Witt has not been explicitly listed with any scientific awards in the provided text. He has supervised several PhD students, including Adak, Rajabi, and Gießen, in projects related to nature-inspired algorithms and theoretical analysis. While specific grant names are not listed, his involvement in multiple funded PhD projects indicates active participation in research funding and academic leadership. Supervision roles include both main supervisor and examiner positions across various DTU research initiatives. Carsten Witt is affiliated with the Algorithms, Logic and Graphs group at DTU, which functions as a research lab focusing on foundational aspects of computing. This team conducts high-level theoretical research in algorithm design, discrete mathematics, and computational complexity, particularly in the context of heuristic and evolutionary methods.
Maryamsadat Tahavori is an Associate Professor at the Technical University of Denmark (DTU), affiliated with the Department of Engineering Technology and Didactics Energy Technology and Computer Science. Her research focuses on sustainable energy systems, asset management, control systems, and fault diagnosis in robotics and district heating networks. She leads projects addressing district heating network optimization, prescriptive analytics, and soil sustainability through sensor technologies. Her academic contributions include advancements in model reduction techniques for bilinear systems and multi-objective optimization algorithms. She supervises PhD candidates like Jens Grønborg and collaborates internationally on initiatives like the IEA DHC Annex for district heating asset management. Key awards include IEEE Senior Member (2021). Her work bridges theoretical control systems with practical applications in energy infrastructure, agriculture, and autonomous systems. She actively participates in conferences, organizes academic events, and serves as an editor for the Sensors journal.
Marco Chiarandini is an Associate Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), with a secondary affiliation to the SDU Climate Cluster. His research focuses on Operations Research, Optimization Algorithms, and their applications in domains such as transportation, healthcare, and education. He has led or contributed to projects addressing dynamic traffic estimation, dementia care app design, and sustainable software development. Chiarandini has supervised students including P. Tampakis and C. McCarthy, and his work has been featured in interdisciplinary collaborations with institutions globally. His recent articles explore topics like goal-scoring prediction in football and urban traffic modeling, reflecting his expertise in data science and algorithmic design. His academic contributions span over 50 publications, emphasizing methodological advancements in optimization and heuristic algorithms. He actively participates in conferences and peer review, and has coordinated EU-funded projects like Data Science for University Management (2019–2023). Chiarandini’s teaching includes courses on linear programming and metaheuristics, integrating practical applications with theoretical foundations.
Jakob Gulddahl Rasmussen is an Associate Professor at the Department of Mathematical Sciences, Aalborg University, within The Faculty of Engineering and Science. His research focuses on spatial statistics, point processes, and statistical modeling with applications in electrical engineering and network analysis. He is actively involved in projects related to smart distribution grids, semiconductor layout design, and problem-based learning methodologies. Research Projects: Data Analytics in Smart Distribution Grids (2024–2028) Statistics-Based Layout Design Tool for Paralleled Semiconductors (2020–2022) PBL og matematik: Hvordan kan PBL fungere på universitetets grundfag? (2018–2019) Point process on linear networks (2013–2018) Research Interests: Statistical modeling of complex systems Applications of point processes in engineering Network analysis and stochastic processes Integration of PBL in university-level mathematics education His recent publications highlight advancements in anomaly detection in power grids, statistical network modeling, and pedagogical innovations in STEM education.
Juan Carlos Parra-Alvarez is an Associate Professor at Aarhus University's Department of Economics and Business Economics, with adjunct roles at Aalborg University and research fellowships at CREATES and the Danish Finance Institute. He holds a PhD in Economics and Business from Aarhus University. His research focuses on quantitative methods for macroeconomic and financial analysis, including dynamic equilibrium economies, asset pricing, and disaster risk modeling. Key interests span continuous-time econometrics, heterogeneous agent modeling, and consumption-based capital asset pricing. Recent publications demonstrate concentrated work on refining estimation techniques for DSGE models, solving peso problems in asset pricing, and developing risk-sensitive approximation methods. Awards include the William E. Brigman Award for outstanding graduate research.
Mogens Steffensen holds key positions at the University of Copenhagen's Faculty of Science: Head of the Department of Mathematical Sciences (since 2023) Professor of Life Insurance Mathematics (permanently since 2012, initially appointed 2008) Editor of the Scandinavian Actuarial Journal (since 2006) Associate Editor of Insurance: Mathematics and Economics (since 2013) His research spans core areas in quantitative finance and insurance: Actuarial mathematics with emphasis on life insurance and pension systems Financial mathematics including stochastic portfolio optimization Applications of Markov processes and jump-diffusion models in risk management Recent publications (2024-2025) demonstrate interdisciplinary innovation across actuarial science and financial engineering, addressing challenges like epidemic impacts on insurance, fairness in risk classification, and optimal reinsurance design. These works consistently employ advanced mathematical techniques including stochastic control theory and smoothing methods to solve real-world problems in pension planning and market valuation. Scientific Awards: No specific awards were mentioned in the provided text. Advising and Grants: The available documentation does not specify student supervisees or research grants. As department head and active researcher, Professor Steffensen undoubtedly oversees academic mentoring and secures funding, but concrete details remain unreported in the source materials.
