Meet Our Faculty

Elizabeth Johnson

Elizabeth Johnson was part of a program that offered free classroom-ready activities and resources that help students understand real-world applications of statistics.

  • Johnathan Auerbach headshot

    Assistant Professor, Statistics, College of Engineering and Computing

    Jonathan Auerbach's research covers a wide range of topics at the intersection of statistics and public policy. He has measured selection bias in mortality studies (with Andrew Gelman) and traffic safety studies (with Shaw-Hwa Lo and Tian Zheng) and assessed the quality of the 2020 census (with Paul Biemer and Joseph Salvo).
  • Assistant Professor, Statistics, College of Engineering and Computing

    Pramita Bagchi’s research focuses on modelling and analysis of dependent data. Dependence among observed data is a phenomenon that arises naturally in important problems, especially in time series and spatial data.She is specifically interested in large complex objects, e.g. functional time series data or spatial surface data. These have emerged as an important object in recent years with the advancement of technology and availability of high-dimensional and high-resolution data, with numerous applications in climate science, geography, finance etc.
  • Assistant Professor, Statistics, College of Engineering and Computing

  • Statue of George Mason

    Professor, Statistics, College of Engineering and Computing

  • Tokunbo Fadahunsi

    Assistant Professor, College of Engineering and Computing

    Tokunbo Fadahunsi’s teaching philosophy is learner-focused and uses active-learning pedagogies. As an instructor, he encourages critical thinking by integrating relatable examples drawn from his students’ diverse backgrounds and majors into his classroom and assignments. As an educator with research interests within the statistical sciences, Fadahunsi focuses on encouraging the critical thinking skills of his students while aiding their retention of statistical concepts. He also endeavors to develop within his students a desire to learn how to draw and communicate information from data.
  • Instructor, Statistics, College of Engineering and Computing

  • Associate Professor, Statistics, College of Engineering and Computing

    David Holmes has taught statistics for more than 20 years at The University of the West of England, Bristol, before joining The College of New Jersey where he spent 19 years heading their statistics program. On retiring from The College of New Jersey he was awarded the title of Professor Emeritus. His research field is Stylometry - the statistical analysis of literary style - specializing in authorship attribution.
  • Assistant Professor and Associate Chair for Education, Statistics, College of Engineering and Computing

    Brett Hunter earned his PhD in Statistics from Colorado State University.  As a graduate student, he won multiple teaching awards and mentored junior graduate teaching assistants.  His research interests include statistical computing, extreme value theory, and biometric human recognition.  For his dissertation, he worked with computer scientists that had developed a facial recognition algorithm to determine what characteristics in pairs of photographs of different people might commonly lead to false matches.
  • Assistant Professor, Statistics, College of Engineering and Computing

    Ilhan Izmirli grew up surrounded by books and a profound sense of deference for education, a practice, which, according to Oscar Wilde (1854 – 1900), “makes one rogue cleverer than another.” To Izmirli, the pursuit of knowledge is at once esoteric and abstract for the sole purpose of attaining intellectual maturity, cultural sensitivity, and social consciousness. As he continued academic study, he was equally attracted to literature, mathematics, music, and physics and was having a hard time deciding which one of these disciplines to study in college.
  • Assistant Professor, Statistics, College of Engineering and Computing

    David is an Assistant Professor of Statistics. He received his PhD in Statistics from the University of British Columbia and a Master of Science in Statistics from the Vienna University of Technology (Austria). His research primarily revolves around robust estimation in high-dimensional settings and applications in the life sciences. David is particularly interested in the robustness of feature selection in the presence of arbitrary contamination as well as countering the effects of contamination on predictive models.