جستجوی استاد راهنمای دانشگاهی

Peter Løchte Jørgensen is a Professor of Finance at Aarhus University's Department of Economics and Business Economics. He has been a full professor since 2003, specializing in asset pricing theory and derivatives. He holds a PhD in Finance from Aarhus School of Business (1994) and a master's in Mathematical Economics (1991). His research focuses on financial economics, ESG investing, risk management, and pension systems. He is affiliated with the Danish Finance Institute (DFI) and the CoRE energy economics center. He chairs the Carlsberg Foundation's investment committee (since 2019) and serves on the Danish National Research Foundation's committee (2018–present). He has held board roles at pension funds DIP, JØP, and P+, and currently sits on Asset Advisor A/S and Selected Investments' boards. Teaching includes the MSc Finance course on Asset Management, emphasizing quantitative methods in portfolio strategy. He actively supervises theses and has advised on topics like derivatives valuation and sustainable finance. Key awards include the Robert I. Mehr Award (2012) and the 2011 ForskerFight title. His recent work explores ESG investment risks and regulatory frameworks in finance.

• Financial Economics
• Asset Pricing Theory
• Derivatives Pricing
• +۳ مورد دیگر

Jing Qin is an Associate Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), where she contributes to research and teaching in mathematical statistics and applied probability. She is also affiliated with the SDU Climate Cluster, reflecting her interdisciplinary engagement in climate and health modeling. Research Interests: Her work spans actuarial mathematics, financial mathematics, bioinformatics, and mathematical modeling. She specializes in extreme value theory, conditional risk measures, tail dependence, and statistical methods for RNA folding. Her research integrates rigorous theoretical development with practical applications in insurance, finance, and biomedical data analysis. The recent publications indicate a strong trend in developing robust, nonparametric estimators for conditional extremes, particularly in bivariate and covariate-adjusted settings. Her work often involves asymptotic analysis and simulation studies, with applications in reinsurance, epidemiology, and genomics. Collaborative research with Y. Goegebeur and A. Guillou is prominent. Scientific Awards: No specific awards listed in the provided text. Advising and Grants: Jing Qin supervises BA, MA, and PhD students in mathematical and statistical research. She is actively involved in externally funded projects, including as Principal Investigator (PI) on a research project analyzing the impact of extreme weather on emergency hospital demand. She has participated in projects funded by the Novo Nordisk Foundation, Carlsberg Foundation, and the Danish Research Council, covering areas from intellectual disability genetics to RNA bioinformatics. Labs and Teams: She is part of collaborative networks in statistical extremes and bioinformatics, and contributes to the SDU Climate Cluster, suggesting active participation in interdisciplinary research teams focused on climate, health, and data science.

• Actuarial mathematics
• Financial mathematics
• Bioinformatics
• +۹ مورد دیگر

Nicolai Siim Larsen is an Assistant Professor (Tenure track) in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), specializing in statistical modeling with applications in finance and healthcare analytics. His work bridges theoretical statistics and real-world data challenges. Education : Ph.D. in Stochastic Financial Models based on Matrix-Analytic Methods, Technical University of Denmark (2022) Dr. Larsen's research centers on multivariate phase-type distributions and matrix-analytic methods , with significant contributions to financial risk modeling and healthcare analytics . His expertise spans survival analysis, sensor data processing, and price optimization frameworks, addressing complex stochastic phenomena in insurance and disease progression monitoring. Analysis of his publications reveals a cohesive focus on advancing numerical computational methods for multivariate data structures. His 2022 Ph.D. thesis established foundations for joint density functions and infinitely divisible distributions, with subsequent work directly applied to commercial pricing strategies and edema patient monitoring systems. Statistical analysis and price optimisation of DJ rental services (2022) AI Denmark: Monitoring disease progression in Oedema patients (2022) KomDigital: Optimal pricing strategies for price monitoring (2022) Stochastic Financial Models based on Matrix-Analytic Methods (PhD project 2018-2023) He actively contributes to academic service as an internal examiner for Statistical Genetics (2025) and instructor for R-based data science workshops, demonstrating commitment to both research leadership and pedagogical development within DTU's Statistics and Data Analysis section.

• Statistics
• Data Science
• Stochastic Processes
• +۳ مورد دیگر

Yevhen Havrylenko serves as a Postdoctoral Researcher in the Department of Mathematical Sciences at the Faculty of Science, University of Copenhagen, Denmark. His appointment is based at Universitetsparken 5, 2100 København Ø, where he conducts advanced research in quantitative finance and actuarial modeling, with contact details including phone +4535327906 and email yh@math.ku.dk. His research program integrates mathematical finance, actuarial science, and machine learning to solve complex risk management problems. Key focus areas include stochastic volatility modeling for portfolio optimization under value-at-risk constraints, neural network applications for detecting variable interactions in generalized linear models, and game-theoretic approaches to risk-sharing mechanisms in insurance products. This interdisciplinary work bridges theoretical mathematics with practical financial and insurance industry challenges, emphasizing computational rigor and real-world applicability. Analysis of his recent publications reveals a cohesive research trajectory centered on mathematical innovation in risk assessment. His work consistently employs dynamic programming, stochastic processes, and machine learning to address market incompleteness, variable interaction detection, and strategic insurer-reinsurer dynamics. The publications demonstrate strong methodological synergy across finance and insurance domains, with increasing emphasis on computational techniques for complex risk modeling. No scientific awards, student advisement records, or research grants are documented in the available profile. Similarly, no affiliations with specific research laboratories or collaborative teams beyond publication co-authors (Escobar-Anel, Zagst, Heger, Hinken) are specified.

• Quantitative Finance
• Actuarial Science
• Machine Learning
• +۳ مورد دیگر

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.

• Actuarial mathematics
• Financial mathematics
• Portfolio Choice
• +۳ مورد دیگر

Frederik Hytting Jørgensen serves as a Research Fellow at the Department of Mathematical Sciences, University of Copenhagen. His research spans critical domains in quantitative analysis: Actuarial Science with emphasis on fairness frameworks Statistical causal inference methodologies Machine learning ethics in insurance applications Risk modeling for insurability assessment Algorithmic bias mitigation techniques His 2024 publication in the European Actuarial Journal pioneers connections between plurality of perspectives, causal mechanisms, and insurability constraints, establishing foundational work for ethically robust actuarial models that balance technical precision with social responsibility in algorithmic decision-making systems.

• Actuarial Science
• Statistics
• Machine Learning
• +۲ مورد دیگر