Professor Oliver Johnson is a faculty member at the School of Mathematics, University of Bristol, UK, where he serves as Head of School and holds the Professor of Information Theory position. His research bridges information theory, probability, and statistics, focusing on entropy convergence, group testing, and fundamental limits in data analysis. Current PhD students: Kieran Morris, Conor Crilly Ex-PhD students: Matt Aldridge, Leonardo Baldassini, Dan Cowley, Vaia Kalokidou, Tom Kealy, Jennifer Chakravarty, Zichen Gui, Chrys Paschou Ex-postdoc: Erwan Hillion His work includes ORCiD profile and collaborations across information theory, cybersecurity, and ecological modeling.
Eric C.K. Cheung is an Associate Professor in the Department of Statistics and Actuarial Science at the University of New South Wales (UNSW), where he has worked since July 2017. Previously, he held positions at the University of Hong Kong (HKU) from 2010 to 2017, including Assistant Professor (2010–2016) and Associate Professor (2016–2017). He earned his BSc (Actuarial Science) from the University of Hong Kong and MMath and PhD in Actuarial Science from the University of Waterloo. His research focuses on insurance risk theory, ruin theory, stochastic processes, and financial mathematics. He has secured multiple grants, including from the Australian Research Council and the Society of Actuaries. Currently, he supervises PhD and Honours students in areas like risk analysis and financial modeling. Cheung teaches actuarial science courses at UNSW, HKU, and the University of Waterloo. His work appears in top journals like Insurance: Mathematics and Economics , and he is an Associate Editor of this journal. He has advised over 10 students at HKU and UNSW.
Zhenyu Cui is an Associate Professor of Financial Engineering at the School of Business, Stevens Institute of Technology. He holds a PhD in Statistics from the University of Waterloo and a BS in Actuarial Science from the University of Hong Kong. His research focuses on financial engineering, insurance analytics, and operations research, with notable contributions to stochastic volatility models, Monte Carlo simulation, and financial systemic risk. He has published in top journals such as Mathematical Finance, SIAM Journal on Financial Mathematics, and European Journal of Operational Research. Education: PhD (2013, Statistics, University of Waterloo); MS (2010, Quantitative Finance, University of Waterloo); BS (2008, Actuarial Science, University of Hong Kong). Research Interests: Financial Systemic Risk, Monte Carlo Methods, Stochastic Volatility, Option Pricing, and Risk Management. His work bridges theoretical finance and practical applications, emphasizing robust pricing techniques and computational methods. Grants include leadership roles in NSF-funded projects on quantum algorithms for financial risk management and collaborations with institutions like Accenture and the Society of Actuaries. Awards include recognition for top-cited articles and editorial excellence.
Prof. habil. dr. Jonas Kazys Sunklodas serves as an Affiliated Professor in the Interdisciplinary Statistical Research Group at Vilnius University's Institute of Data Science and Digital Technologies. His academic career spans decades of rigorous research in probability theory and mathematical statistics, maintaining an active publication record through 2023. His research focuses on asymptotic analysis of stochastic processes , particularly examining normal approximation techniques for various dependent and independent random variable structures. Key contributions include advancements in central limit theorems for φ-mixing processes, m-dependent sequences, and random sums with applications in theoretical statistics. Analysis of his 15 most recent publications reveals consistent specialization in convergence rates , distributional approximations , and limit theorems across diverse stochastic models. His methodological innovations frequently employ characteristic function analysis and L p norm convergence metrics. While no formal awards or student advisement records appear in the provided documentation, his sustained scholarly output demonstrates significant contributions to probability theory. His editorial work on Vytautas Statulevičius' Selected Mathematical Papers (2006) further establishes his standing in Lithuania's mathematical community. Professor Sunklodas maintains institutional affiliation through Vilnius University's Akademijos St. 4 facility (room 220), though no active research grants or laboratory affiliations are documented in the current materials. His textbook Tikimybių teorijos kursas (2003) remains a notable educational contribution to Lithuanian mathematics pedagogy.
Michael Boutsikas is an Associate Professor in the Department of Statistics and Insurance Science at the University of Piraeus. His academic career includes roles such as teaching Statistics II: Hypothesis Testing, Reliability Theory, and Stochastic Finance. He holds a PhD in Applied Probability from the University of Athens (2000), an MSc in Statistics and Operations Research (1998), and a Mathematics Diploma (1995). His research focuses on stochastic orders, probability metrics, reliability theory, and extreme value theory. Key contributions include work on scan statistics, compound Poisson approximation, and risk models. Recent studies address surplus processes in jump diffusion models and exit time analysis under barrier conditions. Teaching spans courses like Multivariate Statistical Analysis and Statistical Software Packages. His work often intersects actuarial science and financial modeling, with applications in insurance mathematics and risk management. Office hours are arranged via email.
Dr. Susan Pitts is a Lecturer in the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge. Her research focuses on functional limit theorems, queueing theory, and insurance risk modeling, with particular emphasis on nonparametric estimation methods and ruin theory applications. Her primary research interests include probability theory , statistical inference , and actuarial science , with applications in insurance mathematics and stochastic modeling. Key thematic areas involve developing approximations for complex risk scenarios and analyzing time-to-ruin probabilities in financial contexts. Dr. Pitts' publications demonstrate consistent focus on risk modeling and stochastic processes , with recent work emphasizing practical applications in insurance analytics. Her articles frequently employ nonparametric statistical methods to solve actuarial problems, particularly in ruin theory and compound Poisson models. The research trajectory shows deepening exploration of multidimensional risk assessment and computational approaches.
David Stanford is a Professor in the Department of Statistical and Actuarial Sciences at the University of Western Ontario. He earned his Ph.D. from Carleton University in 1981. His office is located in WSC 211 and he can be contacted via phone (519-661-2111 x83612) or email. Research Focus: Dr. Stanford's research spans several interconnected domains including: Queueing Theory : Specializing in multi-server systems, priority queues, and service optimization Actuarial Science : Risk modeling, ruin theory, and insurance mathematics Healthcare Operations : Applying stochastic models to transplant systems and patient flow Environmental Modeling : Forest fire prediction using compound Poisson processes His work frequently combines theoretical stochastic processes with practical applications in healthcare and environmental systems. Publication Trends: Analysis of recent publications shows a strong focus on queueing theory applications in healthcare systems, particularly modeling patient flow and organ transplant logistics. His actuarial research emphasizes advanced ruin probability calculations and risk process modeling. Environmental applications feature stochastic approaches to natural disaster prediction.
Michael V. Boutsikas is an Associate Professor in the Department of Statistics and Insurance Science at the University of Piraeus , Greece. Since 2000 he has held progressively senior academic posts, beginning as Lecturer and becoming tenured Assistant Professor before his promotion to Associate Professor in 2016. He earned his Diploma (1995), M.Sc. (1998) and Ph.D. (2000) in Mathematics from the University of Athens, all awarded with distinction. His research lies at the intersection of applied probability, actuarial science and reliability theory . Core interests include risk models, stochastic dependence, probability metrics, extreme value theory, scan statistics, urn models and compound Poisson approximation . These themes are unified by the aim of quantifying and bounding the behaviour of complex stochastic systems. Across more than twenty-five peer-reviewed articles published in leading journals such as The Annals of Applied Probability , Journal of Applied Probability , Bernoulli , Insurance: Mathematics and Economics and Naval Research Logistics , a clear trajectory emerges: developing sharp approximations and limit theorems for rare events, system reliability, and aggregate claims in risk processes. While the text does not list formal awards, it notes that his work has attracted at least 150 citations from international journals and monographs and that he maintains an h-index of 9 . He is an active referee for more than twenty journals and a reviewer for Mathematical Reviews . Teaching duties span undergraduate courses ( Risk Management, Stochastic Processes, Simulation ) and postgraduate offerings ( Simulation Methods, Extreme Price Theory, Stochastic Financial Models ). He has also authored sixteen sets of detailed teaching notes and lecture notes covering reliability, risk management and statistical software. No specific doctoral students or grant details are provided, but his long-standing presence and prolific output indicate sustained supervisory and research funding activity within the Department of Statistics and Insurance Science.
Torkel Erhardsson is an Associate Professor (Docent) in the Department of Mathematics at Linköping University, Sweden. He is affiliated with the Division of Applied Mathematics (TIMA), where he conducts research in probability theory, stochastic processes, and statistical inference. His research interests include: Bounds for distances between probability distributions using Stein's method and couplings Applications to normal and compound Poisson approximations Bayesian nonparametric inference and asymptotics of posterior distributions Higher-dimensional autoregressive processes with random coefficients Reciprocal chains and reciprocal random fields on undirected graphs His recent publications (2008–2023) in journals such as Journal of Applied Probability , Advances in Applied Probability , and IEEE Transactions on Automatic Control reflect a strong focus on theoretical probability and its applications, particularly in approximation methods and stochastic modeling. The work shows increasing emphasis on graphical models and reciprocal processes in recent years. There are no listed scientific awards or honors in the provided materials. Torkel Erhardsson actively contributes to the academic life at Linköping University, participating in seminars in statistics and mathematical statistics. There is no public information indicating student advising, grant funding, or leadership of specific research labs or teams.
Ruihua Liu is a Professor in the Department of Mathematics at the University of Dayton, College of Arts and Sciences. He has been a full-time faculty member since 2004, achieving tenure as Associate Professor in 2010 and promotion to Full Professor in 2016. Educational Background: Ph.D., Engineering Science (Control Theory and Application), Nankai University, China, 1994 Ph.D., Mathematics, University of Georgia, 2001 M.S., Computer Science, University of Georgia, 2001 M.E., Engineering Science, Nankai University, 1988 B.E., Engineering Science, Nankai University, 1985 Ruihua Liu's research lies at the intersection of financial mathematics and stochastic control. His work emphasizes computational finance , particularly in developing numerical methods such as recombining trees and lattice models for pricing options under complex dynamics. A central theme in his research is the use of regime-switching models to capture structural changes in financial markets. He investigates optimal investment and consumption strategies , often incorporating realistic features like proportional transaction costs. His analytical focus includes stochastic optimal control, optimal stopping, and singular control problems, with applications in portfolio optimization and stock liquidation strategies. The 15 most recent publications show a consistent trajectory in applying advanced stochastic analysis to financial decision-making under uncertainty. Key trends include the development of computational algorithms for regime-switching frameworks, solving optimal control problems with state-dependent switching rates, and modeling market behaviors using multi-scale and diffusion processes. These works span top journals in applied mathematics, control theory, and financial engineering, indicating a strong interdisciplinary impact. Scientific Awards and Honors: No specific awards mentioned in the provided text. Advising and Grants: While no formal list of students is provided, his extensive publication record with multiple collaborators suggests active involvement in mentoring graduate students and junior researchers. Though specific grants are not listed, his research output in high-impact journals implies successful acquisition of external funding to support his work in financial mathematics and stochastic modeling. Laboratories and Research Teams: Ruihua Liu is affiliated with the Department of Mathematics at the University of Dayton. While no named lab or center is mentioned, his collaborative work with researchers such as G. Yin, Q. Zhang, and P. Eloe suggests participation in a research group focused on stochastic systems and financial applications.
Χατζηκωνσταντινίδης Ευστάθιος is a Professor at the University of Piraeus in the Department of Statistics and Actuarial Science. His academic career spans decades with significant contributions to actuarial mathematics and statistical theory. He teaches undergraduate courses in Actuarial Mathematics, Risk Theory, and Reliability Theory, and postgraduate courses in Generalized Linear Models and Risk Management. Education: PhD in Mathematics (1990) - Aristotle University of Thessaloniki (Grade: Excellent) BSc in Mathematics (1985) - Aristotle University of Thessaloniki (Grade: Excellent) Research Focus: His work centers on risk theory, bankruptcy modeling, compound Poisson processes, and optimal experimental designs. He has developed innovative approaches to: Perturbed risk models with diffusion processes Copula-based dependence modeling in insurance Gerber-Shiu function analysis for dividend strategies Recursive methods for compound distributions His research bridges theoretical mathematics with practical actuarial applications. Publication Trends: Analytical studies of stochastic processes dominate his recent work, focusing on: Ruin probabilities and deficit distributions Dependence modeling using copulas Optimal dividend strategies Computational methods for risk models Earlier publications emphasize experimental design optimization and reliability theory. Administrative Leadership: Chair of Department of Statistics and Actuarial Science (2007-2009) Director of Postgraduate Program in Actuarial Science & Risk Management Member of Senate of University of Piraeus Deputy Chair of Ministry of Finance's Actuarial Examination Committee Research Projects: Has participated in multiple funded projects including: 'Optimal Experimental Designs' (Greek Ministry of Education) 'Modern Model for Actuarial Studies Preparation' (University of Piraeus) EPEAEK programs on statistical applications
Filip Lindskog is a Professor of Insurance Mathematics at Stockholm University (SU) , where he heads the Mathematical Statistics division within the Department of Mathematics . With a background in financial mathematics and actuarial science, his research focuses on quantitative risk management, non-life insurance pricing, and applications of biostochastics and biostatistics. He has co-authored the textbook Risk and Portfolio Analysis: Principles and Methods (Springer, 2012) and supervises PhD students in actuarial mathematics. Education \n \n MSc in Engineering Physics, KTH Royal Institute of Technology (2000) \n PhD in Mathematical Statistics, ETH Zürich (2004) \n Research Interests Filip's work spans actuarial mathematics , financial risk modeling , and insurance analytics . He investigates stochastic processes in regime-switching environments, capital requirements for insurers, and mathematical frameworks for claims reserving. His recent publications emphasize machine learning applications in risk adjustment, asymptotic analysis of Poisson models, and regulatory compliance under IFRS 17.\n Scientific Contributions \n \n Editor, Scandinavian Actuarial Journal (2018–present) \n Director of SU's Master's Program in Actuarial Mathematics (2016–present) \n Head of SU's Mathematical Statistics Division (2018–present) \n \n Students and Collaborations Current and former PhD students include Nils Engler , Lina Palmborg , Jonas Alm , and Johan Nykvist . Former postdocs include Julie Thøgersen , Abhishek Pal Majumder , and Kristoffer Lindensjö . His research group explores discrete random structures, financial applications of biostatistics, and insurance modeling under capacity constraints.\n
Yasutaka Shimizu is a Professor at the Department of Applied Mathematics , Waseda University , with prior positions at Osaka University and as Visiting Professor at the Institute of Statistical Mathematics. His work bridges mathematical statistics , stochastic processes , and actuarial science . Education : Ph.D. in Mathematical Science (University of Tokyo, 2007) Key Research : Survival energy models for mortality prediction, threshold estimation for jump-diffusions, ruin theory, fractional Brownian motion inference Recent Publications focus on high-frequency data analysis, survival energy hypothesis applications, and statistical methods for financial/actuarial risks. His 2023 work includes threshold estimation under small noise and survival energy models with functional data analysis. Scientific Awards include the Research Achievement Award (Japan Statistical Society), Ogawa Research Encouragement Award , and Competition Outstanding Report Award . Grants from Japan Society for the Promotion of Science cover topics like statistical modeling of stochastic processes, mortality prediction, and financial risk measurement. He maintains professional memberships in the Japan Statistical Society, Mathematical Society of Japan, and Institute of Actuaries of Japan.
