جستجوی استاد راهنمای دانشگاهی

Carsten Sørensenمشاهده پروفایل

استاد

• Dynamic Asset Allocation
• Portfolio Theory
• Term Structure of Interest Rates
• +۳ مورد دیگر

Carsten Sørensen is the Head of Department at the Department of Finance, Copenhagen Business School (CBS), and holds a Cand.Scient.Oecon and Ph.D. His research focuses on dynamic asset allocation, portfolio theory, term structure of interest rates, derivatives, and commodity derivatives. He has contributed extensively to understanding strategic investment decisions under uncertainty, particularly in volatile financial markets. He has authored or co-authored over 29 publications, including seminal works on stochastic income modeling, interest rate dynamics, and commodity futures analysis. His work frequently explores the intersection of theoretical finance and practical investment strategies, emphasizing real-world applications of academic insights. Current Roles: Head of Department (Department of Finance), Director of Danish Finance Institute (2019–present) Outside Activities: Academic Committee Member for Danish FSA (2011–present), Teacher at Danish Society of Actuaries (2019) Key Contributions: Pioneered research on mean-reverting returns and inflation uncertainty in asset allocation models His research trends emphasize quantitative methods to address market complexities, with a focus on stochastic processes and dynamic optimization. He has consistently challenged conventional investment recommendations through rigorous empirical analysis. Awards: None explicitly listed Grants: No specific grants mentioned He is actively involved in academic leadership, directing interdisciplinary research initiatives at CBS and advising regulatory bodies on financial education standards.

Guangya Yangمشاهده پروفایل

دانشیار

• Power System Stability
• Offshore Wind Energy
• Cyber-Physical Power Systems
• +۷ مورد دیگر

Guangya Yang is an Associate Professor at the Department of Wind and Energy Systems, Technical University of Denmark (DTU), with expertise in power system stability, control, and protection of low-inertia systems, particularly in offshore wind applications. He has worked full-time as an electrical design and simulation specialist at Ørsted (2020-2021) and maintains active roles in IEEE, IEC standardization, and editorial work as lead editor for IEEE Access PES. PhD in Electrical Engineering (University of Queensland, 2008) Senior Member of IEEE Former expert member of European Technology & Innovation Platform for solar PV His research focuses on electromagnetic transient simulation, cyber-physical energy systems, and grid compliance for wind power plants. He leads the Horizon 2020 InnoCyPES project (€12m+ grants), training 15 early-stage researchers in cyber-physical energy systems. Key contributions include validating synchronous condensers for low-inertia systems and developing industry training programs on offshore wind control strategies. Coordinated Hardware-in-the-Loop test bench standards (IEC61400-21-5) Advances in grid-forming converter stability and fault ride-through assessment Developed digital twins for power grid validation Scientific Recognition: World’s Top 2% Scientists (Elsevier/Stanford, 2024) Advising & Grants: Supervises 5 PhD students in projects related to machine learning, digital twins, and predictive maintenance. Coordinates €12m+ in research grants, including Horizon 2020’s InnoCyPES. Labs & Collaborations: Works with Ørsted, industry partners, and international universities on offshore wind validation and digitalization.

Jon Sporringمشاهده پروفایل

استاد

• Computer Science
• Mathematical Image Processing
• Medical Image Analysis
• +۶ مورد دیگر

Jon Sporring is a Professor at the Department of Computer Science, University of Copenhagen, specializing in theoretical and applied image processing, stochastic geometry, and biomedical imaging. He leads research in mathematical and medical image analysis, computer graphics, and pattern recognition. Education: Ph.D. in Computer Science (1998), Master in Computer Science (1995), both from University of Copenhagen Affiliations: Pioneer AI section, Applied Geometry Lab, and Faculty of Science External Roles: Visiting professor at McGill University (2012-13), co-founder of DigiCorpus Aps (2012-16) His research integrates scale-space theory, statistical shape analysis, and advanced imaging techniques for applications in medical diagnostics, materials science, and neuroscience. Recent work focuses on 3D reconstruction, persistent homology for bias correction, and AI-driven biomedical analysis. Jon teaches computer science at all academic levels, currently offering courses in bioimaging, signal processing, and deep learning. He emphasizes collaborative projects with external partners and has held administrative roles including Vice-Chair for Research at DIKU. His 15 most recent publications reflect expertise in medical imaging, 3D modeling, and AI applications, with subfields spanning neurodegenerative disease analysis, mitochondrial ultrastructure, and multi-scale image processing. Articles demonstrate interdisciplinary impact across medicine, biology, and materials science.

Kristoffer Arnsfelt Hansenمشاهده پروفایل

دانشیار

• Algorithmic Game Theory
• Computational Complexity
• Game Theory
• +۵ مورد دیگر

Kristoffer Arnsfelt Hansen is an Associate Professor at the Department of Computer Science, Aarhus University. His research focuses on algorithmic game theory, computational complexity, and equilibrium computation in multi-player games. He explores topics such as stochastic games, Nash equilibria, convex optimization, and fair division. His work bridges theoretical computer science with economic applications, particularly in mechanism design and market analysis. Selected publications include studies on PPAD-membership via convex optimization, complexity of Pareto-optimal lotteries, and the computational challenges in analyzing Nash equilibria. He has contributed to conference proceedings like WINE 2022 and SAGT 2021, showcasing his engagement with international research communities. Research interests emphasize theoretical foundations of game theory with practical implications for resource allocation, fair division, and multi-agent systems. His work often intersects with complexity theory, exploring boundaries of efficient computation in economic and strategic scenarios. No awards or grants are explicitly mentioned in the provided data. Advising activities and lab affiliations are not detailed here.

Anatoly Schmidtمشاهده پروفایل

استاد مدعو

• Quantitative Finance
• Financial Engineering
• Agent-Based Modeling
• +۷ مورد دیگر

Dr. Anatoly (Alec) Schmidt is an Adjunct Professor in the Department of Finance, Risk and Engineering at the NYU Tandon School of Engineering and also holds a position in the Financial Engineering Department at the Business School of Stevens Institute of Technology. He has previously served as a visiting professor at Nanyang Technological University and Moscow Financial Academy, demonstrating international academic engagement. His research interests lie at the intersection of physics and finance, with a focus on quantitative finance , agent-based modeling of financial markets , trading strategies , and portfolio management . His interdisciplinary background enables innovative approaches to financial modeling using tools from statistical physics and complex systems. The recent publications reflect a consistent trajectory in advancing quantitative methods in investing and market analysis, particularly through computational modeling and data-driven strategy development. His work increasingly integrates machine learning insights with traditional financial theories, especially evident in his 2021 book on modern equity investing. Dr. Schmidt has not been mentioned with any formal scientific awards in the provided text. He has advised students though none are explicitly named. He has not received mention of grants, but his industry role at Kensho suggests strong project funding and applied research support. His academic appointments indicate active mentorship and curriculum development in financial engineering programs. While no formal lab or research team is specified, his work at Kensho Technologies as Lead Research Scientist implies leadership in a data science and market analytics team, likely involving interdisciplinary researchers and engineers focused on financial intelligence systems.

Richard Martin Lusbyمشاهده پروفایل

دانشیار

• Operations Research
• Mathematical Optimization
• Logistics and Supply Chain Management
• +۵ مورد دیگر

Richard Martin Lusby is an Associate Professor in the Department of Technology, Management and Economics at DTU Management, Technical University of Denmark. His academic work focuses on Operations Research with specialization in mathematical optimization applied to transportation and energy systems. His research spans railway scheduling, container logistics, maritime transport, and energy storage optimization. Department: Department of Technology, Management and Economics Section: Section for Operations Research, Division for Management Science Location: Building 358, Room 145A, Academy Road, 2800 Kgs. Lyngby, Denmark Contact: rmlu@dtu.dk, Tel: 45253084 ORCID: 0000-0002-8652-6219 Professor Lusby's research interests center around mathematical optimization methods applied to complex transportation and energy systems. His work spans railway scheduling problems, container logistics optimization, maritime transport operations, and energy storage scheduling. He develops advanced algorithms including Lagrangian Relaxation, Benders decomposition, and stochastic programming approaches to solve challenging real-world problems in these domains. His research has practical applications in improving efficiency and sustainability in transportation networks and energy systems. His recent publications demonstrate a strong focus on optimization techniques for transportation systems, particularly in railway operations and container logistics, as well as energy storage scheduling. The research shows a consistent pattern of developing sophisticated mathematical methods to address complex operational challenges in transportation networks, with increasing attention to sustainability considerations in maritime shipping and energy systems. Professor Lusby has been involved in significant research projects including the SWITCH project (Sustainable Network Design - Electrifying Container Shipping), which received funding from Den Danske Maritime Fond. This project explores how battery-powered ships could replace fossil fuels in global shipping through mathematical modeling and AI-driven optimization. He also supervises PhD students, including Georgios Vassos who completed a thesis on "Procurement Policy Analysis in Intermodal Container Logistics". His work has practical implications for improving efficiency in transportation networks, reducing environmental impact in maritime shipping, and optimizing energy systems operations. Through his research, Professor Lusby contributes to both theoretical advances in optimization methods and their practical applications in critical infrastructure sectors.

Hongyan Jenny Liمشاهده پروفایل

دانشیار

• Operations Research
• Management Science
• Data-Driven Operations Management
• +۵ مورد دیگر

Hongyan Jenny Li is an Associate Professor at the Department of Economics and Business Economics, Aarhus University. Her research spans Operations Research , Management Science , and Data-Driven Operations Management , focusing on Supply Chain Management , Business Analytics , and Risk Management in Operations . She has taught courses at all academic levels and supervised multiple PhD projects.

Konstantin Pavlikovمشاهده پروفایل

دانشیار

• Operations Research
• Stochastic Programming
• Integer Programming
• +۳ مورد دیگر

Konstantin Pavlikov is an Associate Professor at the Department of Business & Management (DBM) under Strategic Organization Design (SOD) at the University of Southern Denmark. His research focuses on Operations Research, Integer Programming, and Stochastic Programming , with particular emphasis on vehicle routing optimization and network flow modeling. Education : PhD in Operations Research (University of Florida, 2014), MSc in Applied Mathematics (Moscow State University, 2007) His work spans combinatorial optimization and network interdiction problems , developing exact and approximate solution algorithms for complex logistics challenges. Recent publications analyze heterogeneous vehicle routing capacity inequalities and two-commodity flow formulations for routing problems. Scientific contributions have been recognized with the Best Reviewer Award (2019). He actively reviews for journals like Computational Management Science and supervises academic works through examination roles.

Baoze Weiمشاهده پروفایل

دانشیار

• Microgrid Control
• Power Electronics
• Renewable Energy Integration
• +۵ مورد دیگر

Baoze Wei is an Associate Professor at Aalborg University's Department of Electric Power Systems and Microgrids, part of the Faculty of Engineering and Science. His research focuses on advanced control strategies for power electronics, microgrid stability, and energy management systems. He leads and collaborates on projects such as the Digital Twin-based Reliability Framework for Aviation Systems and Holistic Optimization of Green Fuel-Powered Microgrids. Key contributions include work on distributed energy systems, fault-tolerant architectures, and predictive maintenance for power electronics. His research emphasizes practical applications in renewable integration, smart grids, and industrial electrification. Wei has supervised one PhD student, Q. He, and contributed to projects funded by entities like Horizon JU and Huawei. Notable collaborations include work on hybrid-electric aircraft systems (HECATE) and advanced control algorithms for distributed converters. His research spans technical areas such as voltage source inverters, uninterruptible power systems (UPS), and DC shipboard microgrids. His publications reflect expertise in model predictive control, energy trading strategies, and condition monitoring. Current research trends include data-driven lifetime prediction for power electronics components and optimization of multi-energy systems. He actively participates in international conferences, contributing to both theoretical advancements and real-world system implementations.

Danny Bøgsted Poulsenمشاهده پروفایل

دانشیار

• Formal Methods
• Model Checking
• Cyber-Physical Systems
• +۳ مورد دیگر

Danny Bøgsted Poulsen is an Associate Professor at the Department of Computer Science, Aalborg University, affiliated with The Technical Faculty of IT and Design. His research focuses on formal methods, model checking, and cyber-physical systems with applications in security analysis and programming languages. He contributes to projects like BEO-COVID (2020–2020) and IDEA4CPS (2011–2015), which explore decision support tools and foundational cyber-physical systems. His academic background includes advanced work in formal verification and statistical model checking. Key research interests include: Formal methods for string constraints and SMT solvers Statistical analysis of security-critical systems Modelling protocols like DTLS and attack-defense scenarios Applications of formal methods in education and public health Recent work highlights include developing SMTQuery for benchmark analysis, statistical evaluation of bit-flip vulnerabilities, and leveraging large language models for educational feedback. His research outputs span over 36 publications across journals and conferences, with active contributions to UPPAAL tool development and open datasets for reproducibility. Poulsen collaborates internationally on projects involving formal verification of embedded systems and cybersecurity protocols. His work bridges theoretical computer science with practical applications in safety-critical systems.

Andres Masegosaمشاهده پروفایل

دانشیار

• Machine Learning
• Bayesian Networks
• Data Streaming
• +۴ مورد دیگر

Andres Masegosa is an Associate Professor at the Department of Computer Science, Aalborg University (AAU), within The Technical Faculty of IT and Design. He is actively involved in the DarkScience project (2022–present), focusing on metagenomic binning and microbial dark matter analysis. His research interests span Bayesian networks, machine learning, probabilistic graphical models, and educational methodologies in computer science instruction. Key research contributions include advancements in PAC-Bayes theory, genome representation learning, and cold posterior effects in Bayesian models. He has published extensively in top venues like Advances in Neural Information Processing Systems and Transactions on Machine Learning Research. His work often bridges theoretical contributions with practical applications in genomics and education. Masegosa leads the development of tools like InferPy for probabilistic modeling and has contributed to open-source projects such as the AMIDST toolbox. His educational research explores learning styles and active learning strategies, emphasizing live coding and programming exercises. Collaborations include interdisciplinary projects with microbiologists and data scientists, reflecting his expertise in computational methods for complex biological systems. His research portfolio demonstrates a strong focus on scalable probabilistic methods and their real-world applications.

Vera Hemmelmayrمشاهده پروفایل

دانشیار

• Combinatorial Optimization
• Logistics
• Operations Research
• +۷ مورد دیگر

Vera Hemmelmayr is an Associate Professor at the Institute for Transport and Logistics Management, School of Business, Vienna University of Economics and Business (WU Vienna). She earned her PhD from the University of Vienna and completed her habilitation at WU. Prior to her current role, she held postdoctoral positions at the University of Vienna and CIRRELT in Montreal, and conducted research collaborations at Georgia Institute of Technology, University of Bologna, and Northwestern University. Research Interests: Vera's research centers on combinatorial optimization in logistics, with emphasis on enhancing solution methods and real-world applications. She specializes in metaheuristics, parallel algorithms, and hybrid exact-heuristic techniques. Her work addresses critical challenges in waste collection, city logistics, nonprofit logistics collaboration, and sustainable urban transport—particularly the integration of cargo bikes into freight distribution networks. Publication Trends: Her recent publications reflect a consistent focus on vehicle routing problems, green logistics, and optimization under uncertainty. Themes include two-echelon delivery, drone-truck collaboration, stochastic demands, and multi-depot systems. Methodologically, she advances matheuristics, adaptive large neighborhood search, and simulation-optimization frameworks applied to urban and humanitarian logistics. Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: While no students are listed, Vera has served as project leader for multiple research initiatives funded by the Austrian Science Fund (FWF) and the Austrian Research Promotion Agency (FFG), indicating leadership in securing competitive grants and managing research teams. Labs and Teams: Although no formal lab name is given, her affiliation with the Institute for Transport and Logistics Management suggests active participation in a research group focused on logistics optimization, likely involving collaboration with national and international partners in both academia and industry.

Yoshiharu Maenoمشاهده پروفایل

استاد

• Data Science and Engineering
• Complex Systems Theory
• Stochastic Process Theory
• +۷ مورد دیگر

Dr. Yoshiharu Maeno is a Professor at the School of Interdisciplinary Mathematical Sciences, Meiji University, where he conducts interdisciplinary research at the intersection of mathematics, data science, and social systems. His work applies advanced mathematical frameworks to real-world complex phenomena in economics, finance, epidemiology, and social networks. Position: Professor Institution: Meiji University School: School of Interdisciplinary Mathematical Sciences Research Interests Dr. Maeno's research focuses on data science and engineering, complex systems theory, and stochastic process theory applied to economics and social sciences. He specializes in modeling reaction-diffusion processes to understand the dynamics of infectious disease spread, financial crises, and misinformation dissemination on social media. His work bridges theoretical mathematics with practical applications in societal challenges. Publication Trends His recent scholarly output demonstrates a consistent focus on applying reaction-diffusion and stochastic models to complex social and economic systems. The publications span interdisciplinary domains including econophysics, computational social science, and mathematical epidemiology, showing a strong trend toward data-driven modeling of real-world dynamic processes. Scientific Awards No specific awards mentioned in the provided text. Advising and Grants While specific students or grant details are not listed, Dr. Maeno's active research program suggests involvement in mentoring graduate students and securing research funding. His participation in events like the Econophysics Colloquium and CSH Workshop indicates collaboration within the global complexity science community. Labs and Teams Dr. Maeno is associated with research initiatives focused on complex systems and data science, likely involving collaborative teams working on interdisciplinary projects. His involvement in workshops and colloquia suggests membership in international research networks studying complexity in economic and social systems.

Rossana Mastrandreaمشاهده پروفایل

استادیار

• Complex Networks
• Economic Networks
• Health Economics
• +۱۴ مورد دیگر

Rossana Mastrandrea is an Assistant Professor at IMT Institute for Advanced Studies Lucca, affiliated with the AXES research unit. Her work integrates methods from mathematics, economics, and complex systems to study economic, social, and biological networks. Research Interests: Her primary fields include Complex Networks, Health Economics, Environmental Economics, Game Theory, and Behavioural Economics. She applies Graph Theory, Statistical Physics, and Agent-Based Modeling to understand macroeconomic networks, innovation diffusion, and human behavior dynamics. A significant focus is on pharmaceutical innovation, particularly mRNA vaccine development through patent citation analysis, and on modeling pro-environmental behavior using evolutionary game theory and peer effects. Recent Research Trends: Her recent publications (2025–2010) reveal a consistent trajectory in network science applied to economic systems. The work increasingly integrates behavioral and cognitive dimensions into network models, with a growing emphasis on health and environmental policy implications. The use of interdisciplinary methodologies—especially from physics and biology—is a hallmark of her approach. Scientific Projects: Local Coordinator, PRIN Project (2023–2025): "The Role of the Public and Private Sectors in Pharmaceutical Breakthrough Innovations (3PBI)" Former member, INET Project: "Empirical and theoretical analysis of macroeconomics networks" Visiting Fellow, Lorenz Institute of Theoretical Physics, Leiden Advising and Grants: While no formal students are listed, her leadership in the PRIN project indicates mentoring and team coordination responsibilities. She has secured competitive research funding through national (PRIN) and international (INET) programs, supporting interdisciplinary work at the intersection of economics, physics, and biology. Labs and Research Groups: She is actively involved with the AXES research unit at IMT Lucca and previously collaborated with the research group of Prof. Garlaschelli at the Lorenz Institute. Her work is embedded in the broader complexity science community, as evidenced by participation in events like the Econophysics Colloquium and CSH Workshop.

• History of Mathematics
• History of Analysis
• History of Mechanics
• +۲ مورد دیگر

Jesper Lützen is an academic historian of mathematics at the Department of Mathematical Sciences , University of Copenhagen . He is renowned for his expertise in the history of mathematics, particularly focusing on the period 1800–1950, analysis, and mechanics. His current status as a Part-time Lecturer reflects continued engagement despite his emeritus title. Born : October 8, 1951, in Svendborg Education : Student exam (mathematical-physical line), Svendborg State School (1970) B.Sc. in Natural Sciences (mathematics major, physics minor), Aarhus University (1976) Licentiate (Ph.D.) in History of Science, Aarhus University (1980) Doctor of Science, University of Copenhagen (1990) Research Interests : Lützen specializes in the history of mathematical impossibility theorems, ranging from ancient Greek antiquity to modern times. His work spans analysis, mechanics, and the philosophical underpinnings of mathematical concepts. He has extensively explored duality, distributions, and the legacy of figures like Hjelmslev and Juel. Academic Engagement : His 15 most recent publications (2000–2024) reveal a consistent focus on mathematical history, methodology, and foundational debates. Key themes include distribution theory, geometric philosophies, and historical critiques of mathematical rigor. Scientific Awards : Fyns Stiftstidende’s Forskerpris (1982) Børge Jessens Diplom for godt foredrag (1988) Det Naturvidenskabelige Fakultets Formidlingspris (2000) Det Naturvidenskabelige Fakultets Undervisningspris (2003) Editorial and Institutional Roles : Lützen has served on editorial boards for Archive for the History of Exact Sciences and Historia Mathematica , and as a committee member in various academic and outreach initiatives. His outreach efforts include lectures for high school teachers, students, and contributions to the Great Danish Encyclopedia .