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Fosters collaboration and teamwork.
Inspires students to aim high and excel.
Creates a safe and inclusive space.
Inspires students to love their studies.
Brings enthusiasm and expertise to class.
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About Karol
Dr. Karol Binkowski is a Senior Lecturer in Statistics and Teaching & Leadership Academic (FHEA) in the School of Mathematical and Physical Sciences within the Faculty of Science and Engineering at Macquarie University. He leads the Statistical Consulting Hub, which connects research, industry, and data-driven practices. Binkowski completed a Master of Science in Mathematics at Jagiellonian University in Poland and a PhD in Statistics at Macquarie University. After obtaining his doctorate, he gained seven years of professional experience as a Quantitative Analyst at Westpac Institutional Banking before returning to academia. There, he has taught statistics at undergraduate and postgraduate levels, including large-enrolment units such as STAT1170 Introductory Statistics, STAT2170 Applied Statistics, STAT2173 Introduction to Probability, STAT2579 Operations Research I, STAT3102 Graphics, Multivariate Methods, and Data Mining, STAT3110 Statistical Inference, STAT8150 Bayesian Data Analysis, and STAT8310 Statistical Theory, delivered in both face-to-face and online modes. His teaching engages diverse student cohorts through upbeat live lectures utilizing GenAI-enhanced active learning, Peer Instruction, and a strong focus on real-world applications.
Binkowski's research interests lie in applications of statistics and stochastic processes, including multi-factor state-space modelling, robust frameworks for contingent claims, and management of liquidity provisioning for automated market makers; he has supervised Higher Degree Research students in these areas. His contributions to statistics education include innovations in pedagogical practices and active participation in international conferences as an elected member of the International Statistical Institute (ISI). Key publications encompass 'A comparison of strategies used by lecturers to improve students' perceived feelings toward statistics—A study that is Stat-tastic!' (Riach et al., 2025, Teaching Statistics), 'Investigating links between student awareness and use of generative AI tools, and student anxiety and confidence when studying statistics' (Shaker et al., 2025, IASE Satellite Conference), 'Quantifying the benefits to students of faking your fluency in English in recorded lectures' (Binkowski & Baker, 2025, IASE Satellite Conference), 'Designing peer instruction questions for statistical concepts' (Binkowski, 2024, IASE Roundtable Conference), and earlier works such as 'Models for option pricing based on empirical characteristic function of returns' (Binkowski & Kozek, 2010, Banach Center Publications). In 2023, he received the Faculty Award for Excellence in Early Career Teaching for his innovative implementation of Peer Instruction in introductory statistics lectures. He has also served as Primary Chief Investigator on a consultancy project providing statistical analysis services to the National Acoustic Laboratories (2025).
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