Find Academic Supervisors

Georgi Dimitrov MengovView profile

Professor

• Computational Neuroscience
• Behavioral Economics
• Decision Science
• +4 more

Professor Georgi Dimitrov Mengov serves as a full-time faculty member at the Faculty of Economics, Sofia University "St. Kliment Ohridski" since 2005, heading the Center for Modeling Socioeconomic Systems. His interdisciplinary work bridges computational neuroscience and economic decision-making through affiliations including the editorial board of the International Journal of Neural Networks and Advanced Applications and advisory roles at Swiss Innovation Valley. His research focuses on human-oriented decision science , examining neural correlates of economic choices, emotional memory dynamics, and socioeconomic forecasting. Mengov develops computational models predicting intuitive economic behavior using neural network architectures, with particular emphasis on Behavioral economics and risk analysis Neurocomputational modeling of social systems Mathematical-psychological frameworks for decision processes His publication trends reveal consistent interdisciplinary integration: neural network methodologies applied to socioeconomic problems (2006-2018), behavioral economics of digital networks (2021-2025), and foundational work in human decision theory through monographs like Decision Science: A Human-Oriented Perspective (Springer, 2015). Recent work increasingly addresses turbulent economic environments and virtual social networking impacts. Scientific contributions include editorial leadership for major journals and program committee participation in the International Joint Conference on Neural Networks (2013-2019). Notable recognitions include ORCID registration (0000-0001-8157-3246) and ResearchGate profile. As academic advisor and center director, Mengov mentors emerging researchers while leading projects on socioeconomic modeling. His work demonstrates strong integration of theoretical neuroscience with practical economic applications, securing consistent publication output in high-impact journals including Neural Networks and Journal of Behavioral and Experimental Economics . Mengov maintains active research laboratories focused on neuroeconomic modeling and socioeconomic forecasting, with recent work exploring fractal social structures and virtual network economics. Current projects examine motivation dynamics in turbulent economic environments through the ACCESS Press publications.

Bing HanView profile

Professor

• Asset Pricing
• Behavioral Finance
• Investments
• +2 more

Bing Han is a Professor of Finance and the TMX Chair in Capital Markets at the Joseph L. Rotman School of Management, University of Toronto. He holds a PhD in Finance from UCLA and a PhD in Mathematics from the University of Chicago. Research Interests : Behavioral Finance, Asset Pricing, Investment Strategies, Risk Management, and Real Estate Finance. His work bridges mathematical rigor with empirical finance, focusing on market anomalies, investor sentiment, and liquidity dynamics. Publication Trends : His recent work explores option pricing discrepancies, social transmission of consumption beliefs, and cross-border information flows. Articles highlight applications of behavioral biases, volatility modeling, and macroeconomic forecasting using financial instruments. Scientific Awards & Honors : Lifetime Achievement Award (2021) Outstanding Paper Award (2018) Best Paper Award (2016) Outstanding Paper in Asset Pricing Research (2013) CBA Foundation Research Excellence Award (2010) Advising & Grants : Available for Masters/PhD supervision and industry projects. Secured sponsored research funding on Sentiment Risk and Hedge Fund Returns (2016-2017). Previously taught at University of Chicago, Ohio State, and University of Texas at Austin.

Didier SornetteView profile

Professor

• Complex Systems
• Risk Analysis
• Financial Crises and Bubbles
• +11 more

Didier Sornette is Professor of Entrepreneurial Risks at the Department of Management, Technology and Economics (D-MTEC), Swiss Federal Institute of Technology Zurich (ETH Zurich). He is also Professor of Finance at the Swiss Finance Institute, Associate Member of the Department of Physics and Department of Earth Sciences at ETH Zurich, Principal Investigator at the Future Resilient Systems Center at the National University of Singapore, and Specially Appointed Professor at the Institute of Innovative Research, Tokyo Institute of Technology. His research centers on the theory and application of complex systems, particularly focusing on the prediction and control of extreme events—termed 'dragon-kings'—in financial markets, geophysical systems, and socio-economic networks. He employs nonlinear dynamical models, statistical analysis, and feedback mechanisms to detect early warning signals of crises. The available publication highlights his work at the intersection of complexity science and democratic governance, suggesting a growing interest in applying systemic risk methodologies to societal structures. This reflects a broad trend in his research: leveraging quantitative models for real-world systemic instabilities across disciplines. Director, Financial Crisis Observatory (FCO) Co-founder, ETH Risk Center Principal Investigator, Future Resilient Systems, National University of Singapore Specially Appointed Professor, Tokyo Institute of Technology He leads interdisciplinary teams working on InnovWiki, a collaborative platform integrating idea development with prediction markets and data visualization. His lab initiatives emphasize open collaboration, crowd-based evaluation, and real-time risk monitoring. While specific awards and students are not listed in the provided text, his leadership in major research centers and global observatories underscores significant recognition and mentorship activity.

Dimitrios V. SiskosView profile

Assistant Professor

• Finance
• Accounting
• Business Administration
• +13 more

Dimitrios V. Siskos is an Assistant Professor of Finance at the Department of Business Administration, College of Business, Embry-Riddle Aeronautical University (Worldwide Campus). He holds a Doctorate in Finance from the Swiss Management Center, a Master of Science in Project Management from City University of Seattle, and a Bachelor’s in Accounting from Alexander Technological Educational Institution of Thessaloniki. With over two decades of industry experience in finance and accounting, he brings practical insights into his academic work. His research interests span finance, accounting, business administration, project management, and aviation economics . He specializes in financial statement analysis, risk evaluation, investment decision-making, and business venture assessments. His recent publications focus on airport privatization, seaplane transport networks, and financial distress in projects, reflecting a strong interdisciplinary approach combining finance with aviation and public policy. The analysis of his 15 most recent publications reveals a consistent focus on applied finance in real-world contexts—particularly in aviation infrastructure, project evaluation, and financial regulation. His work integrates quantitative methods, risk assessment frameworks, and strategic decision models, often applied to public sector or large-scale projects. Themes such as PESTLE analysis, privatization, Basel III, and performance measurement systems highlight his engagement with both macroeconomic policy and micro-level financial decision tools. Greek Network of Project Management (IPMA), Scholarship to attend and present Paper to the IPMA World Congress 2007, Cracow, Poland Dimitrios Siskos has taught courses including Corporate Finance, Investments, International Finance, and Airport Administration & Finance. He has served as a financial advisor for a team bidding to consolidate the Caribbean aviation industry, preparing consolidated financial statements under the project titled "Unlocking the Aviation Potential in the Caribbean." He has not received externally mentioned grants, but his research output is substantial and disseminated through SSRN, journals, and conferences. He is actively involved in curriculum development and professional training. He maintains an active research presence through his personal website thinkingfinance.info , where he publishes papers, books, teaching materials, and commentary on financial topics. He also contributes to platforms like SSRN, Google Scholar, and ResearchGate, enhancing academic outreach and knowledge dissemination.

Paul WangView profile

Senior Lecturer

• Operations Management
• Supply Chain Management
• Inventory Control
• +7 more

Dr. Paul Wang is a Senior Lecturer of Operations Management and Management Science at Cardiff Business School, Cardiff University . He teaches graduate-level courses including BST514 - Operations Analysis (MBA) and BST124 - Logistics Modelling (MSc), focusing on quantitative decision-making in supply chains. His educational background includes a PhD in Dynamics of Nonlinear Supply Chain Systems from Beihang University, China (2013), an MAdmin and BAdmin in Business Administration. Prior to joining Cardiff, he served as a Lecturer in Logistics Management at Beijing Jiaotong University. Dr. Wang’s research centers on operations and supply chain dynamics , with a strong emphasis on inventory control, the bullwhip effect , stochastic lead times, and demand forecasting. His work integrates system dynamics and mathematical modeling to analyze complex behaviors in production and inventory systems. He has extensively studied food waste in online grocery supply chains and developed models to improve resilience and efficiency. His recent publications reveal a consistent focus on inventory variability , forecasting accuracy , and supply chain resilience , published in top journals such as European Journal of Operational Research , International Journal of Production Economics , and Omega . His research often involves collaboration with scholars like Stephen Disney, Fotios Petropoulos, and Valentina Sanchez Rodrigues. Chinese National Scholarship for Postgraduate Students (2012) Young Scientist Award, 21st International Conference on Production Research (2011) Dr. Wang has advised on industry projects such as the Ocado salads waste project , demonstrating applied impact. He has not listed any PhD students, but his work has contributed significantly to both academic theory and practical supply chain solutions.

Wei KeView profile

Adjunct Associate Professor

• Pricing Algorithms
• Behavioral Pricing
• Marketing Strategy
• +7 more

Dr. Wei Ke is an Adjunct Associate Professor in the Marketing Department at the Leonard N. Stern School of Business, New York University, joining in 2024. He holds a Ph.D. in Decision, Risk & Operations from Columbia Business School and a B.Sc. in Electrical Engineering and Applied Mathematics (summa cum laude) from Columbia University. His professional career is centered at Oliver Wyman, where he serves as a Partner in the pricing, sales, marketing, retail, and business banking practices. Ph.D., Decision, Risk & Operations, Columbia Business School (2009) MPhil, Decision, Risk & Operations, Columbia Business School (2006) B.Sc. (Summa Cum Laude), Electrical Engineering and Applied Mathematics, Columbia University (2003) Wei Ke's research focuses on pricing algorithms and behavioral pricing , exploring how psychological and computational models influence pricing decisions in digital, retail, and financial contexts. His work bridges data science with consumer behavior, emphasizing real-world applications in customer value management and digital sales effectiveness. His recent publications reveal a strong trend in algorithmic and behavioral approaches to pricing across industries such as SaaS, ride-hailing, financial services, and e-commerce. The articles span disciplines including marketing, behavioral economics, data science, and operations research, with recurring subfields like dynamic pricing, consumer segmentation, discount framing, and machine learning for elasticity modeling. His work often combines empirical analysis with strategic implications for firms. Wei has authored over 50 publications in academic and industry journals, contributing significantly to pricing thought leadership. Though no formal awards are listed, his prolific output and consulting leadership underscore his influence in the field. Advises global financial institutions, retailers, and tech firms on pricing and marketing strategy Teaches Pricing Strategies (MKTG-GB.2353.30) at NYU Stern Previously taught at Columbia Business School and Queen’s University Smith School of Business Extensive experience in grant-like consulting engagements with Fortune 500 clients While not affiliated with a formal lab, Wei collaborates closely with industry teams at Oliver Wyman and Simon-Kucher & Partners, contributing to real-world pricing innovation and strategy development in retail, banking, and technology sectors.

Jennifer Alonso-GarcíaView profile

Professor

• Actuarial Science
• Pension Systems
• Retirement Income
• +3 more

Jennifer Alonso-García is a tenured Professor of Actuarial Science in the Department of Mathematics at the Faculty of Sciences, Université Libre de Bruxelles (ULB), a position she has held since October 2019. She concurrently serves as an Associate Investigator at CEPAR, a Netspar Fellow, and treasurer of the PBSS board. Previously, she was a tenure-track Assistant Professor at the University of Groningen's Department of Economics, Econometrics and Finance and a Senior Research Associate at CEPAR. Her academic foundation includes mathematics studies completed in Spain and Germany, culminating in a PhD in Actuarial Science from the Université Catholique de Louvain in 2015. She maintains professional certification as an IA|BE Qualified Actuary by the Belgian Institute of Actuaries and brings industry experience as a Risk Advisor specializing in Solvency II and MCEV frameworks. Dr. Alonso-García's research program centers on actuarial science with emphasis on pension systems, retirement income security, longevity risk quantification, and variable annuity product design. Her work addresses critical challenges in demographic risk management, intergenerational equity, and sustainable pension financing through advanced stochastic modeling techniques. She investigates how socio-economic factors impact mortality patterns and retirement outcomes, with particular focus on fairness in pension design. Analysis of her 15 most recent publications (2021-2025) reveals consistent thematic focus on pension economics and actuarial modeling, characterized by three dominant trends: intergenerational risk-sharing mechanisms in public pension schemes, innovative variable annuity contract designs with hybrid guarantees, and socio-demographic mortality analysis incorporating AI techniques. Her work demonstrates strong methodological rigor in applying risk measures to pension sustainability assessments. Her scholarly contributions have been recognized through prestigious awards: ICA 2018 Best Paper Award IAA Section IAAHS Best Paper Award (2018) IAA Section PBSS Best Paper Award (2019) Dr. Alonso-García actively shapes her field through significant service commitments including Associate Editor for Annals of Actuarial Science, Editorial Board membership at ASTIN Bulletin, and Scientific Board position at Anales del Instituto de Actuarios Españoles. She co-organizes the One World Actuarial Research Seminar and frequently participates in international collaborative projects, evidenced by upcoming engagements including a workshop on pension design in Andros, Greece (September 2025), a research visit to UNSW Sydney (October 2025), and the 1st ASTIN Bulletin Conference in Zürich (January 2026).

Johan BarthelemyView profile

Academic

• Complex Systems
• Agent-based Simulation
• Computer Vision
• +7 more

Dr. Johan Barthelemy is an Honorary Associate Professor at the University of Wollongong's Faculty of Sciences - SAEF, where he leads the SMART IoT Hub and Digital Living Lab. His research focuses on complex systems, agent-based simulation, AI for IoT, and smart cities. He holds a PhD in Applied Mathematics from the University of Namur (Belgium) and has contributed to projects like the mipfp statistical package for R. His work spans environmental monitoring, transportation modeling, and infrastructure resilience. He supervises higher-degree research students and collaborates with NVIDIA as a Deep Learning Institute Ambassador. Education: PhD in Applied Mathematics, University of Namur (2007–2014) MSc in Mathematics, University of Namur (2005–2007) BSc in Applied Mathematics, University of Namur (2003–2005) Research Interests: Agent-based simulation and synthetic population generation AI-driven video analytics for smart cities and environmental monitoring IoT sensor networks and edge computing GPU-based high-performance computing Climate change impact analysis via drones and multispectral imaging Funding & Projects: Lead investigator for ARC grants on future mobility and Antarctic environmental futures CSIRO-funded project on AI-driven sugarcane assessment Multiple University of Wollongong grants for IoT sensors, climate testing facilities, and disaster-resilient transport Labs & Collaborations: SMART Infrastructure Facility (UOW) Namur Center for Complex Systems (Belgium) NVIDIA Deep Learning Institute partnership

• Bioinformatics
• Machine Learning
• Computational Biology
• +7 more

Jan Baumbach is a Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), where he leads cutting-edge research at the intersection of computer science, bioinformatics, and biomedical data science. His work integrates machine learning, network biology, and systems medicine to address complex challenges in health and disease. His research interests include Bioinformatics , Machine Learning , Gene Regulatory Networks , Drug Repositioning , Biomedical AI , and Computational Biology . He applies advanced computational methods to analyze large-scale biological data, with applications in cancer, metabolic diseases, dermatology, and infectious diseases. The 15 most recent publications highlight a strong trend toward biomedical artificial intelligence , network-based analysis , and translational bioinformatics . His work spans from foundational machine learning in healthcare to clinical applications in osteoarthritis, bone regeneration, and skin biology. A consistent theme is the integration of multi-omics data and the development of privacy-preserving federated learning frameworks for distributed healthcare systems. Jan Baumbach has been principal investigator on several major research projects, including: EU Horizon2020: Privacy-preserving federated machine learning in distributed healthcare Danish National Research Foundation: ATLAS Center for Functional Genomics of Tissue Plasticity Villum Foundation: Big Data Bioinformatics (Young Investigator Programme) Carlsberg Foundation: Computational profiling of bacterial volatile metabolomes (ProVol) He has supervised 13 PhD students and has an extensive publication record of 262 works. His research has been featured in high-profile media outlets, emphasizing the societal impact of drug repositioning and AI in medicine. He leads a research group focused on computational systems biology , with strong collaborations across Europe in the fields of genomics, metabolomics, and clinical data science.

Alex WeissensteinerView profile

Professor

• Quantitative Finance
• Financial Engineering
• Asset Allocation
• +4 more

Alex Weissensteiner is a Full Professor of Quantitative Finance and Rector at the Free University of Bozen-Bolzano (unibz). He previously held academic positions at Leopold Franzens University in Innsbruck, the University of Liechtenstein, and served as Professor of Financial Engineering at the Technical University of Denmark from 2013–2015. At unibz, he held leadership roles including Director of the Bachelor's Degree in Economics and Management (2015–2020) and Pro-Rector for Studies (2020–2024) before becoming Rector in 2024. His research focuses on Life-cycle asset allocation Parameter uncertainty in financial models Scenario generation for investment decisions Asset-liability management Market microstructure dynamics Information economics in financial markets Recent publications emphasize portfolio optimization under uncertainty, option-implied risk analysis, and agricultural risk management. His work combines theoretical finance with empirical validation, often applying quantitative methods to banking, insurance, and pension systems. Scientific recognition includes EU grants for "Understanding Pensions in Europe" (2016) and "Understanding Saving in Europe" (2019) Regular contributions to leading journals like Journal of Banking & Finance and Quantitative Finance Invited presentations at major finance conferences (Jackson Hole, AFA, DGF) As Rector, he maintains active research collaborations with scholars including Mogens Steffensen (University of Copenhagen), N. Branger, T. Dangl, and L. Garlappi. He serves on the editorial board of Risks journal and has consulted for provincial education policy bodies.

Martina NARDONView profile

Assistant Professor

• Financial Mathematics
• Actuarial Science
• Option Pricing
• +5 more

Martina NARDON is an Assistant Professor of Mathematical Methods for Economics and Actuarial and Financial Sciences at the Department of Economics, Ca' Foscari University of Venice. She is also affiliated with the Interdepartmental School of Economics, Languages and Entrepreneurship for International Exchanges based in Treviso. Her academic work spans teaching, research, and service as a member of the Economics Degree Commission. Education: Ph.D. in Mathematics for Economic Decisions, University of Trieste, Italy (2002) Laurea degree in Economics (Economia e Commercio), Ca' Foscari University of Venice, Italy (1998) Dr. NARDON's research focuses on quantitative methods in finance, with particular expertise in option pricing, American options, Monte Carlo simulation, stochastic processes, and credit risk. Her work increasingly incorporates behavioral finance perspectives, examining how psychological factors influence financial decision-making and risk assessment. She applies mathematical modeling to practical financial problems, with recent work extending into fundraising management and neural network applications. Analysis of her recent publications (2023-2024) reveals a strong trend toward behavioral finance applications, particularly in probability weighting functions and their implications for portfolio selection and insurance pricing. Her work bridges traditional quantitative finance with behavioral economics, often employing advanced computational methods including artificial neural networks. The research demonstrates consistent focus on practical financial applications while maintaining rigorous mathematical foundations. Professional Service: Member of the Economics Degree Commission Ad hoc referee for European Journal of Operational Research, Decisions in Economics and Finance, and other journals Participant in numerous international conferences including MAF (Mathematical and Statistical Methods for Actuarial Sciences and Finance) series Dr. NARDON teaches advanced courses in Financial and Insurance Products Technique and Quantitative Methods for Financial Choices at the Master's level. Her teaching reflects her research expertise, emphasizing both theoretical foundations and practical applications of quantitative financial methods. She maintains active research collaborations both within Ca' Foscari University and internationally.

George HazelriggView profile

Adjunct Professor

• Systems Engineering
• Engineering Design Decision-Making
• Aerospace Engineering
• +2 more

George Hazelrigg is an Adjunct Professor and Affiliate Faculty in the Department of Mechanical Engineering at George Mason University, with a career spanning academia, industry, and the National Science Foundation (NSF). He earned BS and MS degrees in mechanical engineering from NJIT, and MA, MSE, and PhD in aerospace engineering from Princeton University. Education: PhD, MSE, MA in Aerospace Engineering (Princeton University); MS, BS in Mechanical Engineering (NJIT) Hazelrigg’s research focuses on systems engineering and engineering design decision-making, with current work supported by the NSF titled “Toward a Theory of Systems Engineering.” This project explores mathematical foundations for optimizing design requirements and validating systems engineering processes. His publications from 2019–2025 emphasize systems engineering theory, model validation, tolerancing, decision-making under uncertainty, and pedagogical approaches. Recent work addresses incentive structures, differentiable variables in design, and validation frameworks. Throughout his career, Hazelrigg has taught at prestigious institutions including Princeton University, UC San Diego, and Ajou University in Korea. At the NSF, he managed research programs across four divisions, oversaw $210 million in annual budgets, and served as deputy and acting division director for the Division of Civil, Mechanical, and Manufacturing Innovation (CMMI).

Richard BeckerView profile

Professor

• Environmental Remote Sensing
• GIS Applications
• Hydrogeology
• +7 more

Dr. Richard Becker is a Professor in the Department of Environmental Sciences at the University of Toledo , affiliated with the College of Natural Sciences and Mathematics . He directs the Environmental Remote Sensing Lab , where he employs interdisciplinary methods including remote sensing, geochemistry, hydrologic modeling, and UAV technologies to address geological and environmental challenges. Education: Ph.D. (2008) from Western Michigan University, M.A. and B.A. from Washington University Contact: richard.becker@utoledo.edu | 419.530.4571 | Wolfe Hall, Toledo, OH Research Focus Dr. Becker's work spans three decades, concentrating on: Environmental applications of remote sensing and GIS for geohazard mapping Assessment of land subsidence in arid regions and coastal areas Monitoring toxic algal blooms in the Laurentian Great Lakes Hydrological impacts of engineering projects on wetland systems Climate change effects on groundwater resources in Africa and the Middle East Article Trends His recent publications (2018-2024) demonstrate a consistent focus on: Integration of UAV/drone technologies for high-resolution environmental monitoring Application of remote sensing to track climate change impacts on water systems Development of multi-model ensembles for watershed management Analysis of human-environment interactions through geospatial methods

• Virtual Reality
• Augmented Reality
• Mixed Reality
• +5 more

Alessandro Evangelista is an Assistant Professor at the Polytechnic University of Bari, Italy, within the Department of Mechanics, Mathematics & Management. His scientific-disciplinary sector is ING-IND/15, focusing on Design methods for industrial engineering. His research integrates Virtual, Augmented and Mixed Reality technologies into industrial and training contexts, with strong attention to ergonomics, safety, and human factors. Research Interests Virtual Reality (VR) and immersive simulation for industrial training and safety Augmented Reality (AR) interface design and ergonomic assessment Mixed Reality (MR) applications in product lifecycle and medical prosthesis design Human-computer interaction, cognitive workload, and age-related performance in XR systems Industry 4.0 smart maintenance and real-time data visualization Recent works repeatedly explore how immersive technologies can enhance learning outcomes, safety behaviors, and user experience across manufacturing, retail, maritime navigation and healthcare domains. Studies often adopt comparative user evaluations, ergonomic assessment protocols (e.g., RULA), and multidimensional performance metrics. Publications Trend From 2020 to 2025 Evangelista authored numerous peer-reviewed articles concentrated on immersive technologies. Major themes include: (1) VR training effectiveness for confined spaces and industrial tasks, (2) AR visualization for maintenance and navigation, (3) ergonomic and age-related factors in XR, and (4) application of cinematic VR for safety attitude change and mental-health rehabilitation. His output evidences systematic review work, empirical user studies, and tool prototyping, positioning him at the intersection of design engineering and interactive technologies. Scientific Awards & Grants No specific awards or funded projects are mentioned in the supplied material. Advising & Labs No explicit list of students or research group descriptions are provided; therefore advising activity and laboratory affiliations cannot be detailed at present.

• Mathematical Finance
• Stochastic Processes
• Affine Processes
• +5 more

Christa Cuchiero is a Professor at the Department of Statistics and Operations Research, Faculty of Business, Economics and Statistics, University of Vienna. Her research spans Mathematical Finance, Stochastic Processes, and Machine Learning applications in finance. She has over 48 publications, including recent work on signature-based models for SPX/VIX options, polynomial McKean-Vlasov SDEs, and infinite-dimensional Wishart processes. Her projects include 'Dynamic Uncertainty Modeling in Finance' and a long-term study on 'Universelle Strukturen in Finanzmathematik' (2020–2028). Research Interests: Signature methods for financial modeling Affine and polynomial processes Machine learning in finance Measure-valued stochastic differential equations Volterra equations and rough path theory Portfolio optimization and risk management Scientific Awards: Bruti-Liberati Visiting Fellowship (2018) Fellow at the Center for Advanced Study (CAS), Norwegian Academy of Science and Letters (2024) ETH Medal for Ph.D. thesis (2012) Recent Publications (2023–2025) focus on signature methods, stochastic portfolio theory, energy markets, and robust calibration techniques. Her work integrates advanced mathematical theory with practical financial applications, emphasizing nonlinear SPDEs, polynomial models, and machine learning frameworks.