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Associate Professor
Manuel Morales is an Associate Professor at the Department of Mathematics and Statistics , Faculty of Arts and Sciences , University of Montreal. His research focuses on Financial Mathematics , Actuarial Science , and Applied Machine Learning in banking and responsible investment.
Professor
Dr. A.J. Vermeulen is a Professor of Mathematical Economics & Game Theory at Maastricht University, affiliated with the Department of Quantitative Economics in the School of Business and Economics. His research focuses on game theory, economic modeling, and strategic interactions in various contexts such as cooperative and non-cooperative games, algorithmic approaches, and applications in economics and operations research. His academic contributions span topics like graph-restricted games, behavioral strategies, strategic rationing, and multiagent learning in dynamic environments. He frequently collaborates with researchers such as János Flesch, Mathijs Stevens, and others. His work often appears in top-tier journals such as Games and Economic Behavior and Mathematics of Operations Research . Dr. Vermeulen is also involved in academic leadership, as evidenced by his role in the Graduate School of Business and Economics at Maastricht University.
Professor
Professor Vjekoslav Kovac is a full professor at the Department of Mathematics, Faculty of Science, University of Zagreb. He holds a PhD from UCLA (2011) under Christoph Thiele and was a Fulbright Scholar at Georgia Tech (2019-20). His research spans harmonic analysis, singular integrals, combinatorics, and number theory, with a focus on Fourier restriction problems and Erdős-type conjectures. Kovac leads the HRZZ-funded 'Fourier Analysis and Applications' grant (2023-2027) and has previously directed projects like 'Multilinear Harmonic Analysis' (2018-2023). Education: PhD, UCLA (2011); MSc, University of Zagreb (2006) Research Interests: Singular integrals, real harmonic analysis, geometric measure theory, additive combinatorics, ergodic theory He is renowned for solving longstanding open problems, including Erdős conjectures on unit fractions and irrationality. Kovac has authored/co-authored over 40 publications and mentored multiple PhD and diploma students. His awards include the Croatian National Science Award (2023) and the Brdo Award (2025 nomination). Teaching roles include courses on mathematical analysis, Fourier analysis, and competition mathematics. Grants: Current FANAP (HRZZ), Previous MUNHANAP (HRZZ), MZO/DAAD grants Media Highlights: Coverage in 'What's New' (Tao), 'TotalCroatia', and Croatian TV for resolving 40-year-old mathematical problems
Professor
Máté Wierdl is a Professor in the Department of Mathematical Sciences at the University of Memphis. He holds a Ph.D. from The Ohio State University (1989) and a B.S. from Eötvös Lóránd University (1985). His research focuses on ergodic theory, almost everywhere convergence, number theory, and the foundations of thermodynamics, particularly thermokinetics. He has held visiting positions at institutions like the University of Tours (France) and the University of Maryland. Research Interests : Wierdl explores ergodic theory’s applications to physical systems, addressing time-average convergence challenges. His work on thermokinetics redefines thermodynamics by modeling evaporation and condensation processes using differential equations. He collaborates internationally, emphasizing interdisciplinary connections with Fourier analysis, probability, and number theory. Publications : His recent work includes studies on ergodic averages’ fluctuations, stochastic processes, and sublacunary sequences. He has contributed to prestigious journals like the Transactions of AMS and Indiana J. of Math. Awards : Honors include the Erdos Professorship (2020–2022) and a 2008 membership at the Mathematical Sciences Research Institute. He was also a recipient of the Presidential Fellowship (1988). Teaching & Service : Teaches advanced courses in analysis, complex analysis, and ergodic theory. Served on University committees, including the Faculty Senate, and chairs the Undergraduate Committee. Actively mentors students and advises on research projects. Outreach : Engages in public education advocacy and has presented mathematics to high school students. Served as President of the Tennessee chapter of the American Association of University Professors.
Professor
Professor Jens Perch Nielsen is a Professor of Actuarial Science at Bayes Business School, City St George's, University of London. With a background as an actuary from Copenhagen and a statistician from UC-Berkeley, he has extensive experience in both academia and industry, having served as research director of RSA and worked as an entrepreneur. His educational background includes: PhD, University of California, Berkeley, United States (1988-1990) Actuary, University of Copenhagen, Denmark (1982-1988) Professor Nielsen's research focuses on three main areas: In-Sample Forecasting, Defined benefit advantages adapted to defined contribution products, and Asbestos mortality forecasting. His work spans risk management, actuarial statistics, financial econometrics, and simulation methods, with applications in insurance, pension funds, and broader financial markets. He has made significant contributions to statistical methodology in actuarial science, particularly in developing new approaches to forecasting and risk modeling. His recent publications demonstrate a strong trend toward machine learning applications in forecasting stock returns and insurance risk, with particular emphasis on telematics data in motor insurance. This reflects his ability to bridge theoretical statistics with practical industry applications. Professor Nielsen has received several professional recognitions: Honorary Professor (Adjungated professor) from University of Copenhagen (2006) Associated member, Institute of Actuaries, London (since 2014) Fellow, Royal Society of Statistics, London (since 2013) Full qualified member and former board member, Danish Institute of Actuarial Science (since 1993) As an advisor, Professor Nielsen has supervised numerous PhD students including Stephan Bischofberger, Peter Vodicka, and Parastoo Mousavi. His research has been supported by various grants related to actuarial science, risk modeling, and statistical methodology, with applications spanning insurance, finance, and pension systems. Professor Nielsen is actively involved in editorial work for multiple journals and frequently presents at major conferences, demonstrating his leadership in advancing actuarial science methodology while maintaining strong industry connections through his roles with ScienceFirst and Emergent.
Professor
Ivan Nourdin is a Full Professor of Stochastic Modelling in the Department of Mathematics at the University of Luxembourg. He holds a PhD in Mathematics from Université de Lorraine (2004) and has held academic positions at Université Pierre et Marie Curie (2005–2010) and Université de Lorraine (2010–2014). His research focuses on probability theory, stochastic analysis, and their applications to statistics, geometry, and data science. He co-founded GrewIA, a startup focused on AI and mathematics education. **Research Interests**: Malliavin calculus, Stein’s method, functional inequalities, free probability, rough paths theory, inference for high-dimensional problems. He has authored/co-authored over 80 journal articles and two monographs, including the award-winning Normal Approximations with Malliavin Calculus (2012). **Awards**: 2015 FNR Award for Outstanding Scientific Publication, 2013 France Scopus Researcher Award, 2011 Fondation des Sciences Mathématiques de Paris Prize. **Advising & Teams**: Leads a research group including postdocs and PhD students. Former advisees include Simon Campese, Federico Dalmao, and Guangqu Zheng. His team explores topics like stochastic processes, limit theorems, and applications in AI. **Contact**: Office MNO E05 0515090, Maison du Nombre, University of Luxembourg. Phone: (+352) 46 66 44 6380. Email: ivan.nourdin@uni.lu.
Assistant Professor
Dr. Xiaohui Qi is an Assistant Professor in the Department of Mechanical and Construction Engineering at Northumbria University since 2020. His research focuses on reliability analysis of geotechnical structures, probabilistic site investigations, and data-driven methods for predicting geotechnical and geological properties. Prior affiliations include postdoctoral roles at Nanyang Technological University (2017-2020) and the University of Macau (2015-2017), alongside a PhD from Wuhan University (2015) and an exchange at the National University of Singapore (2012-2015). His work addresses uncertainty in geotechnical engineering through Bayesian back-analysis, spatial variability characterization, and AI-driven predictive modeling. Key interests include slope stability, braced excavations, and soil parameter estimation using limited data. Recent research trends emphasize integrating machine learning (e.g., Bayesian methods, generalized additive models) with geostatistical techniques for 3D site reconstruction and geological interface prediction. His studies often compare methodologies (e.g., coupled Markov chains vs. stochastic simulations) to optimize spatial prediction accuracy. Collaborations span institutions in Singapore, China, and elsewhere, with a focus on applications like subway construction and foundation design uncertainties. No scientific awards are listed, but his 1625 citations highlight impactful contributions to geotechnical reliability and data analytics.
Associate Professor
Mariusz Mirek is an Associate Professor at Rutgers University's Department of Mathematics and a full Professor at the University of Wrocław's Mathematical Institute. He holds a PhD from the University of Wrocław (2011) and habilitation degrees from the University of Bonn (2016) and Wrocław (2017). His research focuses on convergence phenomena in analysis and ergodic theory, interacting with Fourier analysis, number theory, additive combinatorics, and probability. Recently, he explores high-dimensional effects and dimension-free estimates in convex geometry. He has held visiting positions at the Institute for Advanced Study (IAS) in Princeton during 2016/2017 and 2022/2023. His research is supported by NSF grants DMS-2154712 (2022-2025) and DMS-2236493 (2023-2028). He organizes the ETA(η) Ergodic Theory & Analysis Seminar (online via Zoom) and co-organizes the Current Trends in Mathematics workshop at Rutgers' DIMACS (June 2024). His work spans 70+ publications, emphasizing maximal functions, ergodic theorems, polynomial averages, and stochastic processes. Key contributions include dimension-free estimates for discrete operators and applications to additive number theory.
Lecturer
Dr. Enrico Marchioni is a Lecturer in the Agents, Interaction and Complexity research group at the University of Southampton. He holds a PhD in Mathematical Logic from the University of Salamanca (2006) and has held postdoctoral positions at institutions including the Spanish National Research Council (IIIA-CSIC) and Paul Sabatier University (France). His research focuses on formal models of strategic decision-making in multi-agent systems under uncertainty, integrating game theory, mathematical logic, and AI principles. He has taught courses such as Programming I, Theory of Computing, and Intelligent Agents. Current research interests include reasoning under uncertainty, game-theoretic models, and multi-agent systems. He supervises PhD students in Computer Science and has contributed to EPSRC-funded projects. His work spans theoretical frameworks for strategic interactions and formal methods in AI. Key research areas include mathematical logic, game theory, and reasoning under uncertainty, with applications in multi-agent systems and decision-making under incomplete information.
Assistant Professor
Lina Li is an Assistant Professor in the Department of Mathematics at the University of Mississippi within the College of Liberal Arts. She joined the faculty after completing postdoctoral positions at Iowa State University under Ryan Martin and the University of Waterloo under Luke Postle. Her academic background includes: B.S. in Mathematics from Xi'An Jiaotong University (2014) M.S. in Mathematics from the University of Illinois at Urbana-Champaign (2018) Ph.D. in Mathematics from the University of Illinois at Urbana-Champaign (2020) supervised by József Balogh Dr. Li's research centers on extremal and probabilistic combinatorics with specific expertise in enumeration problems, (hyper)graph colorings, and graph tilings. Her methodological approach combines combinatorial, probabilistic, and algebraic techniques to address fundamental questions in discrete mathematics. Current investigations include structural properties of hypergraphs and extremal set theory. Her 14 publications demonstrate consistent contributions to combinatorics, with recent work focusing on Hamming cube colorings, rainbow Turán problems, and hypergraph chromatic numbers. Key trends include probabilistic analysis of extremal structures and connections between graph theory and combinatorial geometry, primarily published in top venues like Combinatorica and Journal of Combinatorial Theory. Dr. Li actively disseminates her research through international invited talks at institutions including Shandong University, Georgia Institute of Technology, and the Institute for Basic Science in South Korea, reflecting her growing influence in the global combinatorics community.
Shvedov Aleksey Sergeevich is a Professor at the Faculty of Economic Sciences of the National Research University Higher School of Economics (HSE), affiliated with the Department of Applied Economics. He has been working at HSE since 1993 with 44 years of scientific and teaching experience. His office is located at Pokrovsky Boulevard, 11, office S524 in Moscow. Professor (1997) Doctor of Physical and Mathematical Sciences (1992) Specialist in Mathematics from Lomonosov Moscow State University, Faculty of Mechanics and Mathematics (1978) Additional education at London School of Economics (1998) and Sorbonne (2000) Professor Shvedov's research focuses on the intersection of fuzzy logic, probability theory, and economic applications. His work primarily explores fuzzy-random optimization, econometric analysis, mathematical economics, and random matrix theory. He has developed innovative approaches to modeling economic phenomena using fuzzy-probability analysis, particularly in financial time series, game theory applications, and regression models with fuzzy data. His research bridges theoretical mathematics with practical economic applications, especially in financial markets and decision-making under uncertainty. His recent publications (2020-2024) demonstrate a consistent focus on advancing fuzzy set theory applications in economics, with particular emphasis on game theory (Cournot and Bertrand oligopoly models with fuzzy parameters), statistical decision theory with fuzzy losses, and financial modeling using fuzzy systems. The work shows increasing sophistication in handling fuzzy-random variables and developing computational methods for economic applications. Scientific awards and recognition: Medal "Recognition - 25 years of successful work" (2023) Honorary Worker of Higher Professional Education of the Russian Federation (2016) Certificate of Honor from Ministry of Education and Science (2012) Multiple academic work allowances and publication bonuses Prize from Moscow Mathematical Society (1987) Inclusion in Who's Who in the World (2016) Professor Shvedov has supervised multiple doctoral dissertations, including works on portfolio theory and covariance matrix estimation. He has led research grants, notably an RFBR project on computational financial mathematics (2000-2002). His teaching portfolio includes advanced courses in probability theory, statistical analysis of financial time series, and specialized courses on fuzzy-probability analysis and financial market models. He has been actively presenting research at major international conferences, particularly the annual conferences named after S.A. Ayvazyan.
Assistant Professor
Panagiotis Xenos is an Assistant Professor of Actuarial Science at the Department of Statistics and Actuarial Science, School of Economics, Business & International Studies, University of Piraeus. His academic career spans teaching, research, and participation in significant national and international research programs focused on insurance, health economics, and organizational efficiency. PhD from University of Piraeus Postgraduate studies at Brandeis University (USA) Postgraduate studies at Boston University (USA) Specialized workshop at York University (UK) Dr. Xenos specializes in Actuarial Science with a particular focus on Insurance Economics, Health Economics, and Productivity Analysis. His research examines the efficiency and productivity of public and private insurance and health institutions, methods of compensation for medical professions, morbidity risk management, social security system sustainability, and insurance portfolio solvency. His work bridges theoretical actuarial science with practical applications in healthcare and social security systems, particularly in the context of economic crises and austerity measures. His publication record demonstrates consistent scholarly output from 2013 through 2023, with a concentration on Greek healthcare and insurance systems but with broader implications for international contexts. The research shows a clear progression from technical actuarial methods toward more comprehensive analyses of healthcare systems, social security sustainability, and economic policy implications. His work frequently employs advanced quantitative methods including Data Envelopment Analysis, Stochastic Frontier Analysis, and Malmquist productivity indices to assess organizational efficiency in healthcare and insurance sectors. Dr. Xenos actively participates in international academic discourse, having presented his research at conferences across Europe, Asia, and Australia, including the World Health Organization conference in Barcelona (2015) on health system financing. He serves as a reviewer for scientific journals and is a member of relevant scientific societies. In addition to his research activities, Dr. Xenos maintains an active teaching role across multiple academic programs. At the undergraduate level, he teaches Introduction to Insurance, Business Insurance, and Personal Insurance. At the postgraduate level, he teaches Health Insurance in the Master's Degree Program in Actuarial Science and Risk Management, Contemporary Issues in Commercial and Insurance Law in the Interdepartmental Master's Program in Law & Economics, and Economic and Financial Management of Health Services in the Postgraduate Program in Healthcare Unit Management at the Hellenic Open University. His teaching reflects his research expertise, connecting theoretical frameworks with practical applications in insurance and healthcare management.
Associate Professor
Yanghui Liu is an Associate Professor in the Department of Mathematics at Baruch College, CUNY, affiliated with the Weissman School of Arts and Sciences. His research focuses on stochastic processes, numerical analysis, and financial mathematics, particularly in the context of fractional Brownian motion and rough volatility models. He holds a Ph.D. in Mathematics from the University of Kansas and has authored numerous publications in high-impact journals like the Annals of Applied Probability and Stochastic Processes and their Applications. Education: Ph.D. in Mathematics, University of Kansas M.S. in Mathematics, Chinese Academy of Sciences B.S. in Mathematics, Nanchang University His research emphasizes numerical methods for stochastic differential equations, limit theorems, and applications to financial markets. Key contributions include work on Euler schemes for fractional Brownian motion-driven processes and statistical inference for rough volatility models. Dr. Liu has received a Lang Junior Faculty Research Fellowship and actively participates in academic service, including reviewing for journals like the Annals of Probability and serving on grant review panels. Grants & Awards: Eugene M. Lang Junior Faculty Research Fellowship (2022) PSC-CUNY Awards (2021, 2023) Funding applications pending with the Simons Foundation and NSF He teaches advanced courses such as Numerical Methods for Differential Equations and Probability Theory, and leads research projects on stochastic dynamical systems and their financial applications.
Professor
Prof Anthony Dooley is a Professor and Head of the School of Mathematical and Physical Sciences at the University of Technology Sydney (UTS). He previously held positions at the University of Bath (UK) and UNSW, serving as Head of School and leading strategic roles. His research focuses on Modern Analysis, including harmonic analysis and dynamical systems, with over 90 peer-reviewed publications and continuous ARC grants for 20 years. He has supervised 18 PhD students and held visiting roles at institutions like Yale, Kyoto University, and the Mittag-Leffler Institute. Education: PhD from ANU; Diplôme des Études Approfondies from Paris 6. Awards: Fellow of the Australian Institute of Company Directors. Research interests span ergodic theory, Lie groups, and stochastic processes. Contributions include work on non-singular ergodic theorems, G-measures, and entropy in dynamical systems. Service roles: Board memberships at NIDA, Australian Graduate School of Management, and international research panels. Grants: Chief Investigator for the ARC Centre of Excellence for Mathematics and Statistics of Complex Systems (MASCOS). Active in governance across academia and research institutions.
Assistant Professor
Yunran Wei is a Tenure-track Assistant Professor at the School of Mathematics and Statistics, Carleton University. His research focuses on Quantitative Risk Management, Actuarial Science, Mathematical Finance, and FinTech/InsurTech. He holds a Ph.D. in Actuarial Science from the University of Waterloo, with supervisors Ruodu Wang and Gord Willmot, and has earned credentials including the Associate of the Society of Actuaries (ASA). Education: Ph.D. in Actuarial Science, University of Waterloo (Supervisors: Ruodu Wang, Gord Willmot) MMath in Statistics, University of Waterloo (Supervisor: Carole Bernard) BMath, Double Major in Pure Mathematics and Mathematical Finance, University of Waterloo Research Interests: Dr. Wei’s work bridges theoretical advancements in risk management and practical applications in financial markets. His research explores Cryptocurrency Market Risk , Risk Sharing Mechanisms , and Statistical Methods for Actuarial Applications . Recent projects analyze vulnerability in financial systems using conditional risk measures and investigate optimal allocations under heterogeneous beliefs. Awards & Funding: NSERC Discovery Grant (2023–2028) James C. Hickman Scholar Fellowship (2018–2019) Grants & Advising: As sole PI of NSERC grants totaling $39,500 CAD annually, Dr. Wei leads research teams focusing on risk analytics. His advising includes collaborations on cryptocurrency risk modeling and parametric risk measures. Professional Activities: Active contributor to journals like Mathematical Finance and Insurance: Mathematics and Economics , with a focus on advancing quantitative methods in finance and insurance.
