Rate My Professor Lyron (Pronounced Lee-Ron) Winderbaum (He/Him)

Dr. Lyron Winderbaum (pronounced Lee-Ron, he/him) serves as Lecturer in Mathematical Sciences at Adelaide University, within the College of Sciences. He obtained his PhD in Statistics from the University of Adelaide in 2016, focusing on the statistical treatment of proteomic imaging mass spectrometry data. His academic qualifications also include a Master of Teaching (2019), Honours in Statistics (2011), Bachelor of Science majoring in Chemistry (2011), and Bachelor of Computer and Mathematical Sciences majoring in Pure Mathematics (2010), all awarded by the University of Adelaide. Winderbaum's career encompasses diverse roles in academia and research. He commenced as Lecturer at Adelaide University in 2026. Previously, he was Lecturer at the University of South Australia from 2022 to 2025, Data Analyst at the Royal Australasian College of Surgeons in 2021, Research Fellow at the University of Western Australia from 2019 to 2021, Postdoctoral Research Associate at the University of South Australia in 2017, Research Associate at the University of Adelaide from 2015 to 2016, and Tutor at the University of Adelaide's Mathematics Learning Centre and School of Mathematical Sciences from 2012 to 2019.

Winderbaum's research specializations include high-dimensional multivariate statistical methods applied to proteomics mass spectrometry data in oncology and plant biology, reproducible research practices using tools like Quarto, decision-making processes for practical impact, continuous glucose monitoring data for diabetes management, inductively coupled plasma mass spectrometry for geological trace element analysis, and interests in wealth inequality economics and diversity in education. His contributions to mathematics education emphasize equity, accessibility, maths anxiety mitigation, bridging and enabling programs, and their role in socio-economic mobility. Key publications feature 'Feature extraction for proteomics imaging mass spectrometry data' (Annals of Applied Statistics, 2015, with I. Koch, O. Gustafsson, S. Meding, P. Hoffmann), 'Classification of MALDI-MS imaging data of tissue microarrays using canonical correlation analysis based variable selection' (Proteomics, 2016, with I. Koch, P. Mittal, P. Hoffmann), 'Lymph node metastasis of primary endometrial cancers: associated proteins revealed by MALDI imaging' (Proteomics, 2016, with P. Mittal et al.), 'Annexin A2 and alpha actinin 4 expression correlates with metastatic potential of primary endometrial cancer' (Biochimica et Biophysica Acta - Proteins and Proteomics, 2017, with P. Mittal et al.), 'Cross-validation for supervised learning with tuning parameters' (Journal of Statistics and Computer Science, 2022, with I. Koch), and 'Principal component analysis of standard and spherical covariances from the population and random samples to real and simulated data' (American Journal of Theoretical and Applied Statistics, 2022, with I. Koch, K. Naito).