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Aurélien ALFONSIView profile

Professor

• Numerical Probability
• Financial Computing
• Mathematics
• +3 more

Aurélien ALFONSI is a Professor at École des Ponts ParisTech and Director of the Centre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique (CERMICS). His primary affiliation is within the Mathematical and Computer Engineering Information department. He also holds a teaching position at the École Polytechnique, where he leads the Finance course in the Master’s program in Mathematics and Applied Computer Science. He specializes in Numerical Probability , Financial Computing , and Mathematics , with a focus on stochastic processes, optimal transport, and computational finance. His work bridges theoretical developments (e.g., Wasserstein distance analysis, stochastic Volterra equations) with practical applications in derivative pricing, risk management, and climate finance. ALFONSI’s research emphasizes high-order numerical schemes for stochastic models (e.g., Heston, Cox-Ingersoll-Ross processes) and innovative methods for solving complex financial and mathematical problems, such as the stochastic sewing lemma and dual approaches to option hedging. His contributions span Monte Carlo methods, volatility modeling, and the interplay between stochastic calculus and optimal transport theory. Though no specific awards are listed, his prolific publication record reflects sustained academic engagement. His role as department director suggests leadership in research and educational initiatives. He actively collaborates on projects involving financial engineering, climate derivatives, and computational methods for stochastic systems.

Jean-Michel PEREIRAView profile

Professor

• Geomechanics
• Energy Production
• Geotechnical Heat Exchangers
• +4 more

Jean-Michel PEREIRA is a Professor at École nationale des ponts et chaussées, serving as Deputy Chairman of the Civil Engineering and Construction Department and a researcher at the Navier Laboratory. He holds a Doctorate in Civil Engineering (2005) and a Habilitation to Supervise Research (2014). His expertise lies in geomechanics, focusing on energy production-related challenges such as geotechnical heat exchangers, CO2 geological storage, and hydrocarbon production. He teaches soil and rock mechanics, emphasizing advanced geotechnical studies. His research explores coupled thermal-hydro-mechanical behaviors of soils, with applications in energy geotechnics and sustainable infrastructure. Recent studies include experimental and numerical analyses of energy piles, frost heave dynamics, and multiphase flow in porous media. Collaborations involve advanced imaging techniques (MRI, X-ray tomography) to study material behavior at microstructural scales. Key contributions include advancing understanding of geothermal systems, CO2 storage mechanics, and structural responses under thermal cycling. His work bridges fundamental geomechanics with practical engineering solutions for energy transition challenges.

• Virtual Reality in Rehabilitation
• Biomechanics
• Motion Analysis
• +3 more

Mark Simonlehner is a Junior Researcher at the Institute of Health Sciences, Department of Health Sciences at Steyr University of Applied Sciences. His work focuses on applying virtual reality (VR) and advanced motion capture technologies to study human movement biomechanics and rehabilitation engineering. He holds an MSc in Biomedical Engineering and has contributed to projects such as VReeze, ULTRASKEL3D, and ReMoCap-Lab, exploring applications of VR in healthcare and motion analysis. Education: Master's in Health and Rehabilitation Technology (2017–Present), Bachelor's in Biomedical Engineering (2013–2017). Prior to academia, he worked as a carpenter and attended the Holztechnikum Kuchl (2004–2009). Research interests include gait analysis, wearable sensor technologies, and improving clinical assessment methods through VR. His publications emphasize the effects of VR on dynamic balance, motion variability, and joint alignment in rehabilitation contexts. Key collaborations involve studies on exergame development for physical activity promotion and biomechanical validation of VR systems against traditional force plate measurements. His work bridges clinical needs with innovative engineering solutions in health sciences.

Laurent Saloff-CosteView profile

Professor

• Analysis
• Probability Theory
• Stochastic Processes
• +7 more

Laurent Saloff-Coste is the Abram Rogers Bullis Professor of Mathematics at Cornell University , affiliated with the College of Arts and Sciences . His research focuses on analysis , probability theory , stochastic processes , and their interplay with Riemannian geometry and geometric group theory . He explores heat diffusion on manifolds, random walks on groups (both finite and infinite), and quantitative estimates for ergodic Markov chains. Education: Ph.D. in Mathematics (1983), Université Paris VI Doctorat d'État (1989), Université Paris VI Research Interests: His work bridges analysis and probability, studying properties of heat kernels, potential theory, and functional inequalities. He investigates geometric aspects of large-scale structures, such as Cayley graphs, and the relationship between group algebraic properties and random walk behavior. Key areas include: Heat kernel estimates on manifolds and graphs Isoperimetric profiles and their applications Mixing times of Markov chains Sub-elliptic diffusions on Lie groups Recent Trends in Publications (2023–2025): His recent work emphasizes geometric analysis of heat kernels, long-range random walks on nilpotent groups, and functional inequalities. He explores applications to stochastic processes on discrete and continuous spaces, including studies of Lévy processes on nilpotent groups and transient subgraphs. Notable themes include: Estimates for hitting times and Harnack inequalities Perturbation methods for Dirichlet eigenfunctions Uniform doubling properties in Lie group geometries Awards: 2022 Simons Fellow Advising and Grants: No specific advisees or grant details are listed in the provided materials. His research has been supported by collaborations with institutions like the Institute of Mathematics in Wrocław, Poland, and participation in events such as the Midwest Probability Colloquium. Labs/Teams: No dedicated lab or team is explicitly mentioned, though his work involves interdisciplinary collaborations in geometric analysis and probability.

Erich Walter FarkasView profile

Associate Professor

• Quantitative Finance
• Risk Management
• Sustainable Investments
• +4 more

Erich Walter Farkas is an Associate Professor of Quantitative Finance at the University of Zurich (UZH) and an Associate Faculty member at ETH Zurich's Department of Mathematics. He serves as Program Director for the joint UZH-ETH Zurich Master of Science in Quantitative Finance, established to bridge expertise in finance and mathematics. His research focuses on risk management, sustainable investments, and mathematical finance, emphasizing holistic approaches that integrate quantitative analysis with behavioral factors. Education: Farkas earned his doctorate and habilitation in Germany, later moving to Switzerland. He holds a Master's and Licentiate in Mathematics from the University of Bucharest, and a Certificate in Advanced Studies for Board Members from Bern-Rochester. Research Interests: Mathematical Finance, Quantitative Risk Management, Volatility Modeling, Sustainable Investment Impact, and Risk Measures. He leads projects like the Data-Driven Financial Risk (DaDFiR3) initiative and co-initiated the Finance Roundtable 2025 on AI and Big Data in finance. Advising & Grants: Supervises theses in quantitative finance and risk management. Active in organizing conferences such as ETH Risk Days and serves on boards like the Swiss Risk Association and Swiss Finance Institute. Professional Roles: Member of the Executive Education Board at UZH, Director of the Teaching Center at the Department of Finance, and founder of the Swiss Risk Association. His work bridges academia and industry, emphasizing practical applications of theoretical frameworks.

IMMACULATE OLIVAView profile

Associate Professor

• Mathematical Finance
• Portfolio Allocation
• Derivative Valuation
• +3 more

Immaculate Oliva is an Associate Professor at the Department of Methods and Models for Economy, Territory and Finance within Sapienza University of Rome's Faculty of Economics. She teaches Quantitative Finance, Methods and Models for Finance, and Financial Mathematics courses for undergraduate and graduate programs in Finance and Economics. Her office hours are held weekly on Mondays from 14:30 to 16:30, available both in-person and remotely via scheduled appointments. Her research specializes in mathematical finance with focus areas including: Optimal portfolio allocation in continuous-time models Derivative valuation and structured products design Counterparty credit risk management frameworks Portfolio insurance strategies (CPPI/TIPP) Stochastic processes with jumps and co-jumps Actuarial solutions for longevity risk Recent publications (2020-2025) demonstrate strong focus on portfolio insurance mechanisms, derivatives pricing under jump diffusion models, counterparty risk quantification, and computational methods for financial equations. Her work frequently combines theoretical rigor with practical applications in energy markets, pension systems, and cryptocurrency trading. She coordinates research projects including: Facing emerging risks: an actuarial perspective Actuarial and financial risk management solutions in a pandemic mortality framework and supervises thesis students through structured guidance documented in her Vademecum.

Fabian HollsteinView profile

Professor

• Empirical Asset Pricing
• Financial Econometrics
• Quantitative Methods in Finance
• +7 more

Prof. Dr. Fabian Hollstein is a Professor of Quantitative Methods in Economics and Finance at Saarland University, affiliated with the Faculty of Human and Business Sciences. He heads the Chair of Quantitative Methods in Economics and Finance and currently serves as Dean of Studies, which has influenced his recent teaching load. His research is centered on empirical asset pricing, financial econometrics, and quantitative finance, with a strong focus on risk modeling and market dynamics. His research interests include empirical asset pricing, financial econometrics, beta and volatility modeling, tail risk measurement, machine learning applications in finance, factor models, and commodity markets. He employs advanced quantitative techniques to analyze financial data, with a particular emphasis on high-frequency data and predictive modeling. The most recent publications highlight a consistent trend in advancing empirical methods in asset pricing, particularly through machine learning, robustness testing of factor models, and deep analysis of risk components such as volatility-of-volatility and tail risk. His work spans global equity, bond, and commodity markets, demonstrating both methodological rigor and broad applicability. Special Prize from the Deutsche Bundesbank for 'Measuring Tail Risk' (2025) Best Paper Award at the Spanish Finance Forum (2023) Editor's Choice Article in Review of Asset Pricing Studies (2023) Lead Article in Financial Management (2024) Ranked 24th under 40 and 66th overall in WirtschaftsWoche ranking (2020–2024) Prof. Hollstein has secured multiple research grants from the German Research Foundation (DFG), including funding for 'Advances in Empirical Asset Pricing' (€176,077) and 'Market Jumps: Causes and Investor Reactions' (€362,386). He supervises doctoral students, as indicated by active job postings for PhD positions, and contributes to academic training through bachelor’s, master’s, and doctoral seminars. His team includes research associates and student assistants working on econometric and financial modeling projects. The Chair of Quantitative Methods in Economics and Finance, under his leadership, conducts cutting-edge research and offers courses in econometrics, statistical programming (R), and asset pricing. The team collaborates with researchers from Leibniz University Hannover and other institutions, fostering a strong interdisciplinary and international research environment.

Josip ArnerićView profile

Researcher

• Econometric methods and models
• Financial time-series and volatility
• Univariate and multivariate GARCH models
• +3 more

Josip Arnerić, PhD, is a researcher at the Department of Statistics within the Faculty of Economics & Business at the University of Zagreb. His work focuses on econometric modeling, financial time-series analysis, and high-frequency data applications. Academic affiliation: Faculty of Economics & Business, University of Zagreb Research focus: Financial econometrics, volatility modeling, neural networks Email: jarneric@efzg.hr Research Interests Arnerić specializes in econometric methods for financial markets, with particular expertise in: Univariate and multivariate GARCH models Stochastic processes and volatility dynamics High-frequency data analysis Machine learning applications to financial forecasting Market risk modeling and portfolio optimization Publication Trends His work spans econometric modeling of stock market volatility (2023-2025), housing affordability analysis (2024), and neural network applications in inflation forecasting (2021). He has also explored: Price jump identification techniques Gold as safe-haven asset Interdependencies between traditional and cryptocurrency markets

Xiao HuangView profile

Professor

• Econometrics
• Financial Economics
• Quantitative Analysis
• +2 more

Xiao Huang is a Professor in the Department of Economics, Finance & Quantitative Analysis at Kennesaw State University. He holds a Ph.D. in Economics from the University of California, Riverside, and a B.A. in Economics from Fudan University. Ph.D. in Economics, University of California, Riverside (2005) B.A. in Economics, Fudan University (2000) His research focuses on econometric methodologies for analyzing financial and economic data, particularly addressing challenges in dynamic panel modeling, cross-sectional dependence, and stochastic processes. Key areas include quasi-maximum likelihood estimation, nonparametric techniques, and applications to vector autoregression frameworks. Research outputs emphasize econometric theory, financial modeling, and computational methods. Publications investigate multivariate diffusions, jump-diffusion processes, and panel data structures with cross-sectional interactions. Coles College of Business Faculty Research Award Xiao Huang's academic contributions span econometric theory development and applied financial modeling. He has presented at major conferences including the Econometric Society and Midwest Econometrics Group meetings.

Jean-François BéginView profile

Associate Professor

• Actuarial Science
• Financial Mathematics
• Financial Econometrics
• +9 more

Jean-François Bégin is an Associate Professor in the Department of Statistics and Actuarial Science at the Faculty of Science, Simon Fraser University. He is a Fellow of both the Society of Actuaries and the Canadian Institute of Actuaries, underscoring his expertise and leadership in actuarial science and financial risk modeling. He obtained his academic training from leading Canadian institutions: a PhD in Administration (Financial Engineering) from HEC Montréal under the supervision of Geneviève Gauthier; an MSc in Mathematics (Applied Mathematics) from Université de Montréal supervised by Mylène Bédard and Patrice Gaillardetz; and a BSc in Mathematics (Financial Mathematics) from the same university. His thesis work centered on simulation schemes for stochastic models in finance. His research lies at the intersection of actuarial science, financial econometrics, and quantitative finance, with major themes including stochastic volatility modeling, filtering methods, option pricing, pension economics, mortality forecasting, credit risk, and climate risk. He develops advanced statistical and computational methods to model financial and insurance risks under uncertainty. His recent publications—appearing in journals such as Management Science , Journal of Econometrics , Insurance: Mathematics and Economics , and North American Actuarial Journal —reflect a strong trend toward integrating econometric modeling with practical applications in pensions, insurance, and derivatives. His work increasingly explores collective risk-sharing mechanisms in pension pools, model uncertainty in economic scenario generation, and the use of high-frequency and aggregated data in risk modeling. His scientific contributions have been recognized through fellowships in two of the most prestigious actuarial bodies: Fellow of the Society of Actuaries Fellow of the Canadian Institute of Actuaries He is an active supervisor of graduate and undergraduate students, mentoring research in areas such as financial econometrics, Bayesian estimation, pension pooling, climate risk, and option pricing. He has advised numerous Master’s and doctoral students and welcomes new applicants with strong quantitative skills. He has also contributed to funded research and industry-oriented reports, particularly through collaborations with the Society of Actuaries and the Canadian Institute of Actuaries. He teaches advanced courses in financial economics, stochastic processes, Monte Carlo simulation, and actuarial communication at SFU, and previously taught at HEC Montréal and Université de Montréal. His research group engages with interdisciplinary challenges in risk modeling and continues to develop innovative frameworks for actuarial and financial decision-making.

Irene FonsecaView profile

Professor

• Applied Mathematics
• Materials Science
• Computer Vision
• +3 more

Irene Fonseca is the Kavčić-Moura University Professor of Mathematics and Director of the Center for Nonlinear Analysis at Carnegie Mellon University’s Mellon College of Science. Her research focuses on applied mathematics at the interface of physical sciences and engineering, emphasizing variational techniques for materials science (e.g., shape memory alloys, thin films, epitaxy) and computer vision (image segmentation, denoising). She holds leadership roles including past SIAM President (2012) and has been honored with prestigious awards like the European Academy of Sciences Fellowship and knighthood in Portugal’s Military Order of St. James (1997). Education: Ph.D., University of Minnesota, Minneapolis Research Interests: Calculus of variations and nonlinear partial differential equations Mathematical modeling of materials microstructures Anisotropic surface energies and thin film growth Image processing via variational methods Epitaxial thin film growth mechanics Articles Trends: Recent work emphasizes Homogenization theory and multiscale modeling Nonlinear elasticity in thin structures Advanced image denoising algorithms Dislocation dynamics and defect formation Γ-convergence applications in phase transitions Awards: SIAM Fellow American Mathematical Society Fellow 2014 University Professor appointment 2018 Kavčić-Moura Professorship Grants & Labs: Leads the Center for Nonlinear Analysis, managing NSF-funded programs. Active in training next-generation applied mathematicians through interdisciplinary initiatives. Labs/Teams: Core contributor to CMU’s CNA, collaborating on projects bridging mathematics with materials science and imaging challenges.

• Nano- and micro-particle transport
• Surface interactions in porous media
• Trace element biogeochemistry
• +5 more

William Johnson is a Professor in the Department of Geology & Geophysics at the University of Utah's College of Engineering, with a 30-year track record in colloid transport research and trace element biogeochemistry. He directs advanced facilities including ICP-MS and light scattering laboratories while maintaining active collaborations in environmental engineering, hydrology, and contaminant dynamics. Current research focuses on multi-scale colloid transport mechanisms in porous media Investigates mercury and selenium cycling in aquatic systems like Great Salt Lake Develops groundwater remediation strategies for mining-impacted environments His recent publications demonstrate theoretical advances in colloid filtration theory, including interception history models and nanoscale heterogeneity impacts. Over $5M in research grants from NSF, EPA, and state agencies support his work on contaminant transport, with particular emphasis on mercury isotope tracing and polymer-modified remediation materials. Mentoring 12 PhD and 34 MSc students, he maintains active teaching roles in graduate geochemistry and contaminant hydrology courses. Fundamental contributions to non-exponential transport behavior Established mercury source apportionment frameworks for saline lakes Developed lateral channel filtration for placer mining mitigation His research website (www.wpjohnsongroup.utah.edu/research.html) provides additional details about current projects and instrumentation capabilities.

Stefanie KlattView profile

Professor

• Sports Science
• Cognitive Psychology
• Motor Learning
• +4 more

Stefanie Klatt is a Professor in the Department of Cognition in Team Sports at the German Sport University Cologne. Her research focuses on integrating cognitive factors into the analysis and optimization of training and movement processes in sports games. Current academic leader in team sports cognition Active editorial contributor to sports science journals International collaborations with institutions like University of Brighton Her research spans Sports Science , Cognitive Psychology , and Motion Analysis , particularly examining attention mechanisms, decision-making dynamics, and cognitive-motor integration in high-pressure sports scenarios. Recent work explores stress responses in referees and novel training interventions for athletes. Key publication trends include team sports cognition , performance optimization , and health promotion initiatives. Awards include the DOSB Science Prize (2016) and Honorary Research Fellowship at University of Brighton (2020). DOSB Science Prize 2016 DVS Publication Prize 2015 Karl Hofmann Research Prize 2015 Honorary Research Fellow, University of Brighton 2020 Excellence in Research Award 2023 She supervises junior researchers like PhD student Benjamin Noël and leads third-party funded projects on referee training, movement analysis, and public health interventions through insurance partnerships.

Herbie LeeView profile

Professor

• Bayesian statistics
• Computer models
• Spatial inverse problems
• +7 more

Herbie Lee is a Professor in the Department of Statistics at the Jack Baskin School of Engineering, University of California, Santa Cruz. He also serves as the Interim Dean of Social Sciences. His faculty office is located in 537A Baskin Engineering, and he can be reached at 831-459-1655 (though email is preferred). Lee completed his educational journey with a strong foundation in mathematics and statistics: B.S. in Mathematics from Yale University with a specialty in statistics Ph.D. in Statistics from Carnegie Mellon University (1998), advised by Larry Wasserman Post-doctoral work at Duke University's ISDS department Professor Lee's research focuses on Bayesian statistics, particularly in the areas of computer models, spatial inverse problems, simulator emulation, adaptive experimental design, and optimization. His work bridges theoretical statistics with practical applications across diverse domains including cosmology (dark energy modeling), aircraft damage detection, electronic health records analysis, and environmental monitoring. He has made significant contributions to the understanding of neural networks within a statistical framework. An analysis of his recent publications reveals a strong emphasis on Gaussian process modeling, Bayesian optimization, and nonstationary spatial statistics. His work increasingly addresses complex real-world problems requiring sophisticated statistical approaches for mixed data types, constrained optimization, and real-time decision making. The interdisciplinary nature of his research is evident in collaborations with institutions like Lawrence Livermore National Laboratory and the Naval Postgraduate School. Among his notable achievements: Supervised PhD student Bobby Gramacy won the prestigious Savage Award Authored two books on Bayesian optimization and multiscale modeling Published over 50 peer-reviewed articles in top statistics and machine learning journals Professor Lee has supervised numerous graduate students, with his most recent PhD student graduating in 2024. His research has been supported by various grants, though specific funding sources aren't detailed in the provided text. His teaching portfolio includes courses on Bayesian statistics, design and analysis of computer simulation experiments, and statistical methods for biological, environmental, and health sciences. He is actively involved in several professional statistical societies including the International Society for Bayesian Analysis (ISBA), American Statistical Association (ASA), and Institute of Mathematical Statistics (IMS).

• Financial Mathematics
• Econometrics
• Risk Management
• +5 more

Ayşegül İşcanoğlu ÇEKİÇ is an Associate Professor in the Department of Econometrics at Trakya University's Faculty of Administrative Sciences. She holds dual doctoral degrees from Middle East Technical University (2011) and Technische Universität Kaiserslautern (2010), both in Financial Mathematics. Her academic career spans roles as a Research Assistant at Middle East Technical University (2004-2011), Assistant Professor at Selçuk University (2011-2014), and Associate Professor at Trakya University since 2014. Education: B.Sc. in Statistics, Middle East Technical University (2003) M.Sc. in Financial Mathematics, Middle East Technical University (2005) Ph.D. in Financial Mathematics, Middle East Technical University (2011) Second Ph.D. in Financial Mathematics, Technische Universität Kaiserslautern (2010) Her research focuses on financial mathematics, econometrics, and risk management. Key areas include portfolio insurance strategies, credit scoring, debt obligations, and stochastic modeling in financial markets. She has extensively studied Constant Proportion Portfolio Insurance (CPPI), risk-return dynamics in emerging markets, and generalized additive models in finance. Her work frequently addresses Turkey's financial sector through empirical analyses of BIST indices, pension funds, and environmental disclosures. Her publications demonstrate methodological rigor in computational finance, with applications to Turkish and international markets. She explores cross-correlations, multifractal analysis, and heavy-tailed distributions for risk assessment, alongside shrinkage estimators and Bayesian approaches for portfolio optimization. Scientific Awards: ULAKBIM UBYT (International Scientific Publications Incentive) - TÜBITAK (2014) ÇEKİÇ has served on editorial boards for the Social Sciences Research Journal and International Journal of Mathematics and Statistics . She has refereed for prestigious journals including Annals of Operations Research and Mathematical Problems in Engineering . Active in international conferences, she organized the 16th International Symposium on Econometrics (2015) and held leadership roles in sessions at European Conference on Operational Research.