Professor Craig Costello is a leading cryptographer at the Queensland University of Technology (QUT) , affiliated with the Faculty of Science and the School of Computer Science . His work focuses on post-quantum cryptography , particularly isogeny-based and lattice-based cryptographic constructions , contributing to global efforts in securing digital infrastructure against quantum computing threats. Notable research trends include: Advancements in supersingular isogeny key exchange (SIKE/SIDH) Exploration of pairing-friendly abelian varieties for cryptographic cycles Efficient genus 2 isogeny algorithms and Kummer surface optimizations Development of twin smooth integer detection for cryptanalysis His publications emphasize quantum-resistant protocols , mathematical foundations , and practical cryptographic implementations . Contact: craig.costello@qut.edu.au
Enno Siemsen is a Professor in the Management Information, Decisions & Operations group at the School of Management, University of Bath. His research lies at the intersection of operations management, behavioral decision-making, and supply chain analytics. He actively contributes to high-impact journals in the field and explores how human judgment interacts with quantitative models in forecasting and planning contexts. His research interests include Operations Management , Behavioral Operations , Demand Planning , Forecasting , Inventory Management , and Decision Making . His work often employs field studies and experimental methods to understand real-world decision-making by practitioners, particularly in demand forecasting and production planning settings. He investigates cognitive biases such as anchoring, the role of team structures, and the integration of human insight with algorithmic predictions. The recent trend in his publications shows a strong focus on improving forecasting accuracy through simple, frugal methods, understanding cultural influences on knowledge transfer, and enhancing digital supply chain decision-making by blending human and machine intelligence. His articles frequently appear in top journals such as Journal of Operations Management and Production and Operations Management . Enno Siemsen has contributed to the UN Sustainable Development Goals, particularly those related to responsible consumption and production through operational efficiency and cost-saving innovations. His research promotes sustainable operations via improved planning and reduced waste. He collaborates with researchers globally and has co-authored studies with scholars from various countries. While no formal list of advisees is provided, his senior academic role suggests he mentors PhD and Master’s students in operations and decision sciences. There is no mention of external grants, but his active publication record implies ongoing research support. His work is associated with the Management Information, Decisions & Operations research group at Bath, which focuses on data-driven decision-making, analytics, and behavioral insights in business operations. This team engages in both theoretical and applied research with industry relevance.
Marcin Bownik is a Professor in the Department of Mathematics at the University of Oregon, part of the College of Arts and Sciences. He has been at the University of Oregon since 2003, progressing from Assistant Professor (2003-2008) to Associate Professor (2008-2014) and finally to Professor (2014-present). He has also held visiting positions at the Institute of Mathematics of the Polish Academy of Sciences (2009-2010, 2016-2017, 2023-2024). Education: Ph.D. in Mathematics, Washington University in St. Louis, 2000 (Thesis Advisor: Richard Rochberg) M.A. in Mathematics, Washington University in St. Louis, 1997 Magister in Mathematics, University of Warsaw, Poland, 1995 Marcin Bownik's research focuses on Harmonic Analysis, Wavelets, and Frames . His work spans several interconnected areas including non-isotropic function spaces such as anisotropic Hardy, Besov, and Triebel-Lizorkin spaces; construction of wavelets with arbitrary dilations; theoretical aspects of wavelets and frame wavelets; the structure of shift-invariant spaces in L 2 (R n ); Gabor systems; and weighted norm inequalities. His recent publications demonstrate continued innovation in anisotropic analysis, frame theory, and applications to operator theory. His work often bridges pure mathematics with applications in signal processing and geometric analysis. Bownik serves as editor for several prestigious journals including the Journal of Fourier Analysis and Applications (2019-present), Applied and Computational Harmonic Analysis (2020-present), and Dissertationes Mathematicae (2020-present). He has organized numerous conferences and special sessions on Wavelets, Frames, and Related Expansions, demonstrating his leadership in the field. Ph.D. Students: Kenneth Hoover (2007) - Dimension functions of rationally dilated wavelets John Jasper (2011) - Infinite dimensional versions of the Schur-Horn theorem Li-An Daniel Wang (2012) - Multiplier theorems for anisotropic Hardy spaces Joey Iverson (2016) - Frames generated by actions of locally compact groups Martin Hiserote (2019) - A characterization of anisotropic H 1 (R N ) by smooth homogeneous multipliers Bownik maintains an active teaching schedule at the University of Oregon, regularly teaching advanced courses in Real Analysis, Complex Analysis, and specialized topics in Harmonic Analysis. His teaching spans from undergraduate calculus courses to graduate-level seminar courses in his research specialty areas.
Rumen Kostadinov Uluchev is an Associate Professor in the Department of Numerical Methods and Algorithms at the Faculty of Mathematics and Informatics, Sofia University "St. Kliment Ohridski". His research focuses on numerical analysis, approximation theory, and interpolation techniques, particularly involving Radon projections, bivariate polynomials, and shape-preserving methods. Specializations: Numerical Analysis, Approximation Theory, Interpolation, Polynomial Optimization Contact: rumenu@fmi.uni-sofia.bg His work emphasizes the use of Radon projections for data smoothing and surface reconstruction, leveraging polynomial interpolation and approximation in both theoretical and practical applications. He has explored extremal problems in Blashke products and critical point analysis for polynomials, contributing to geometric interpolation methods with parametric splines. Key article trends include bivariate polynomial interpolation for mixed-type data, Hermite interpolation with exponential box splines, and harmonic function fitting via Radon projections. His research spans theoretical proofs (e.g., Foster and Krasikov conjecture) and computational algorithms for numerical stability and shape preservation. Professor Uluchev's academic contributions include a dissertation on optimal interpolation (1990) and textbooks such as Applied Mathematics and Formulas in Higher Mathematics for engineering students. His publications span journals, conference proceedings, and book chapters since 1984.
Grażyna Krech, Ph.D., serves as an Assistant Professor at the Department of Mathematical Analysis and Applications within the Faculty of Applied Mathematics at AGH University of Science and Technology in Kraków, Poland. Her primary responsibilities include teaching duties and active research in mathematical analysis, with office locations documented in both Building C-7 (Czarnowiejska 36, Room 615) and Building B-7 (Czarnowiejska 70, Room 35), the latter being her current consultation venue for the winter semester 2021/22. Her research centers on classical approximation theory , specifically investigating: Rate of convergence for linear operators Voronovskaya type asymptotic theorems Boundary value problems Approximation properties of Poisson integrals Behavior of positive linear operators Her work frequently employs Hermite and Laguerre polynomial systems, Gamma operators, and Durrmeyer-type constructions across univariate and bivariate function spaces. Analysis of her 15 most recent publications (2013-2018) reveals a cohesive research program focused on quantitative approximation theory. She consistently develops direct and converse results for operator sequences in L p and exponential weighted spaces, with particular emphasis on convergence rates and asymptotic behavior. Her contributions bridge classical analysis and numerical methods, maintaining strong theoretical rigor while addressing practical approximation challenges through Poisson integrals and specialized operator families. No scientific awards or major honors are documented in the available materials. Information regarding student supervision, grant funding, or collaborative research teams was not included in the source documents, though her active conference participation suggests engagement with the approximation theory community. Her consultation schedule indicates direct student interaction during academic semesters.
Kazım Sari is a Professor at Industrial Engineering Department , Faculty of Engineering and Architecture , Istanbul Beykent University. He serves as Vice Rector while maintaining active research in green logistics , supply chain management , and operations research . His work bridges theoretical modeling with real-world applications in diverse sectors. Doctor Lecturer (2006) Associate Professor (2013-2014) Professor (2018) His research explores green performance metrics , collaborative forecasting , and supplier selection models . Key trends include multi-criteria decision analysis in food and healthcare sectors, plus bullwhip effect mitigation in supply chains.
Dr. Eszter Novák-Gselmann is an Associate Professor at the University of Debrecen , affiliated with the Faculty of Science and Technology and the Institute of Mathematics . Her research focuses on functional equations, operator theory, and hypergroup structures, with significant contributions to the characterization of derivations and differential operators. Primary research areas: Functional Equations, Operator Theory, Hypergroups Key methodological interests: Stability of information measures, Polynomial identities, Spectral synthesis Recent publications explore topics such as higher-order differential operators, monomial functions, and moment functions on hypergroups, demonstrating interdisciplinary connections between algebra, analysis, and information theory. Scientific Awards : Gróf Tisza István Foundation Publication Award (2022) for gene regulatory mechanism research Gróf Tisza István Foundation Publication Award for poultry nutrient supplementation studies She collaborates with researchers like László Székelyhidi , Gergely Kiss , and Csaba Vincze , and her work appears in journals such as Aequationes Mathematicae , Results in Mathematics , and Acta Mathematica Hungarica .
Babak Jamhiri holds a Doctoral Researcher position with expertise in structural health monitoring and reliability analysis. He is affiliated with the 3DCP and Construction Automation Research Group, focusing on AI-driven simulations, infrastructural risk assessment, and probabilistic modeling. His research spans geoenvironmental reliability, machine learning algorithms for signal processing, and risk assessment in construction materials. Education: BSc, MSc, and PhD in relevant disciplines (institutions unspecified). Current projects include structural health monitoring of 3DCP components, machine learning for signal processing, and probabilistic crack propagation in problematic soils. Recent work involves performance assessment of post-tensioned concrete beams and developing compressed earth bricks with marl sediment. Research interests emphasize geotechnical challenges such as expansive soils, desiccation cracking, and soil stabilization using industrial byproducts. He explores Bayesian inference, Markov decision chains, and fractal approaches in clay-based materials for nuclear waste disposal applications. Contributions include YouTube tutorials on information value theory, signal processing for anomaly detection, and probabilistic modeling with R. His work bridges theoretical advancements with practical engineering solutions, emphasizing uncertainty quantification and decision-making under uncertainty.
George Terrell is an Associate Professor in the Department of Statistics at Virginia Polytechnic Institute and State University. He holds degrees from Rice University, including a B.A. (1970), M.A. (1974), and Ph.D. (1978) in Mathematics. His research focuses on mathematical statistics, probability, and statistical computing, with specialties in nonparametric density estimation, multivariate nonparametric methods, and projection pursuit methods. His work emphasizes methodological advancements in statistical theory and computational techniques. Terrell has held significant editorial roles, including Associate Editor of Computational Statistics (1992–2001) and Journal of Computational and Graphical Statistics (1999–present). He has contributed to academic governance through roles such as Faculty Associate of Baker College (1984–1986) and membership on curriculum and dean review committees within the College of Science. His publications span foundational statistical theory, including seminal work on kernel density estimation, cross-validation, and saddlepoint approximations. He authored Mathematical Statistics: A Unified Introduction (Springer, 1999), a textbook synthesizing statistical principles. Terrell has received the Fellow of Scientia (1983–1987) and contributed reviews for influential texts in applied probability and smoothing techniques.
Kandrika Pritularga is a Lecturer in Management Science at Lancaster University, UK. He holds a BSc from Universitas Gadjah Mada (Indonesia, 2011), MSc in Operations Research (Lancaster University, 2016), and PhD in Business Forecasting (Lancaster University, 2023). His core research focuses on statistical forecasting models, particularly in mitigating parameter and model uncertainty in exponential smoothing and vector models, with applications in business, healthcare, and tourism. He examines hierarchical forecasting structures and estimation procedures for univariate/multivariate models. Current teaching includes courses on business statistics, forecasting, data mining, and analytics visualization. Research projects include exploring 'trustworthy business forecasting' (2025) and stochastic coherency in forecast reconciliation. He is affiliated with the Centre for Health Futures and Centre for Marketing Analytics & Forecasting. Kandrika advises on PhD topics involving theoretical forecasting, model estimation, and multivariate/hierarchical methodologies.
Dr. Alisa Yusupova is a Lecturer in Marketing Analytics at the Management Science department, Lancaster University Management School (LUMS). Her expertise bridges quantitative methods and financial forecasting. PhD in Money, Banking and Finance (Lancaster University, UK) BSc in Banking (State University of Economics and Finance, Saint-Petersburg, Russia) Research focuses on time-series modelling and forecasting , particularly: Dynamic linear models with adaptive discounting Time-varying parameters in exponential smoothing House price forecasting Forecast combinations Her 2023 publication in the International Journal of Forecasting explores Bayesian adaptive learning methods in time-series analysis. She actively participates in academic conferences like the International Symposium on Forecasting and contributes to the Centre for Marketing Analytics & Forecasting.
Richard Seeber is a Researcher at the Institute of Control and Automation (Institut für Regelungstechnik und Automation) at TU Graz. His academic titles include Privatdozent (Priv.-Doz.), Diplom-Ingenieur (Dipl.-Ing.), Doctor of Engineering (Dr.techn.), and Bachelor of Science (BSc). His work focuses on advanced control theory, nonlinear systems, and observer design. He holds a teaching authorization in system dynamics and control theory, reflecting his dual role in research and education. Research interests include robust exact differentiators, sliding mode control, observer design for linear and nonlinear systems, and applications in thermal management and energy systems. He has contributed to methodologies addressing actuator saturation, discretization challenges, and real-time control implementation. His recent work emphasizes predefined-time convergence algorithms and stability analysis under bounded noise or disturbances. Selected projects involve heater modeling for fuel cell stacks, frequency converter nonlinearity compensation, and control strategies for biomass furnaces. His contributions are often applied to industrial systems requiring precise control under uncertainty, such as gas engine power plants and transient operating conditions. He collaborates within TU Graz's Institute of Control and Automation, contributing to both theoretical advancements and practical tool development. His research portal (https://irt.tugraz.at/) hosts publications and tools related to robust control methodologies.
Luca Tamanini is a Tenure-Track Assistant Professor (RTDb) at Università Cattolica del Sacro Cuore in Brescia, Italy. He holds the Italian Habilitation (Abilitazione Scientifica Nazionale) as Associate Professor in sector 01/A3 (Mathematical Analysis, Probability and Statistics). His research focuses on optimal transport theory, metric measure spaces (especially RCD spaces), and their applications to PDEs, stochastic analysis, and functional inequalities. Research interests include: Entropic optimal transport and Sinkhorn algorithms Geometric and analytic properties of RCD spaces Hamilton-Jacobi equations in non-smooth settings Functional inequalities and Markov semigroups Large deviations and stochastic processes His recent work explores stability of entropic plans, Hessian estimates for Sinkhorn potentials, and geometric interpretations of optimal transport divergences. Key contributions include advancements in semiconcavity theory and applications to algorithm convergence rates. Awards: Italian Habilitation for Associate Professorship (2023). Future activities include research visits to Université Paris Saclay (July 2025) and Universität Bonn (July 2025), and participation in specialized conferences.
Peter Kritzer is a Senior Scientist and Scientific Coordinator at the Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences in Linz, Austria. He holds a Master's degree (2003) and a Doctoral degree (2005, 'Sub Auspiciis Praesidentis') from the University of Salzburg, followed by a Habilitation in Mathematics (2012) from Johannes Kepler University Linz. His research focuses on high-dimensional algorithms, quasi-Monte Carlo methods, discrepancy theory, and information-based complexity. Affiliations: RICAM, Austrian Academy of Sciences (since 2015); previously at University of Salzburg, UNSW Australia, and Johannes Kepler University Linz. His work emphasizes numerical integration, tractability analysis, and algorithm design for high-dimensional problems. Notable contributions include advancements in lattice rules, digital nets, and hybrid function spaces. He has received awards such as the Information-Based Complexity Young Researcher Award (2011) and the Kardinal Innitzer Förderungspreis (2013). His recent articles explore topics like reduced digital nets, QMC matrix-vector products, and tractability in Hilbert spaces. He actively contributes to Monte Carlo and quasi-Monte Carlo research communities, editing volumes like Monte Carlo and Quasi-Monte Carlo Methods 2022 .
Sunil Dhar is a Professor in the Department of Mathematical Sciences at the New Jersey Institute of Technology (NJIT). His research spans interdisciplinary areas including biostatistics, cardiovascular science, and statistical modeling. He has contributed to studies on catheter material strength, muscle-fascia interactions during exercise, and bivariate geometric distributions. Research Interests: His work focuses on applying statistical methods to biomedical problems, including cardiovascular hemodynamics, muscle physiology, and clinical device evaluation. He also explores theoretical probability distributions and their real-world applications. Recent Publications: Over 30 peer-reviewed articles, with notable contributions in Anesthesia and Analgesia , Journal of Bodywork and Movement Therapies , and Communications in Statistics . Key themes include material science for medical devices, biostatistical modeling, and clinical hemodynamic measurements. Advising & Grants: No specific student advising or grant information provided in the texts. His research has been supported through institutional and collaborative efforts.
