• Stan Sclove

    Stan Sclove06/15/2021

    Stan was born in Charleston, West Virginia, and grew up in Huntington, West Virginia, and graduated from Huntington High School. He then attended Dartmouth College, graduating with a math major. He then went to Columbia University’s Department of Mathematical Statistics, getting a PhD. He served as a TA to T.W. Anderson in a statistics course for grad students in Sociology. During the summers, Stan worked as a Statistician in the Laboratory of Medical and Biological Sciences, Taft Center, U.S. Public Health Service, Cincinnati, Ohio. After finishing the PhD at Columbia, he was a Research Associate (postdoctoral fellow) for two years in Stanford’s Department of Statistics, working on a government research contract held by Herb Solomon and Herman Chernoff. Stan’s part of the contract related to Classification and Cluster Analysis. Stan then joined the newly formed Statistics Department at Carnegie-Mellon University in Pittsburgh. He was there for three years, then returned …

  • Paul McNicholas

    Paul McNicholas06/15/2021

    Paul McNicholas was born in Cork, Ireland, and raised in Dublin, Ireland. He was educated at Trinity College Dublin, where he studied mathematics, high-performance computing, and statistics. He is currently a Professor and Canada Research Chair in Computational Statistics at McMaster University, Hamilton, ON. His research focuses on statistical approaches to clustering, with a focus on clustering using mixture models. To date, he has written two monographs and over 100 research articles. Recent work includes approaches for higher order data as well as approaches for dealing with outliers. He has received some recognition for his work, including the Steacie Prize for the Natural Sciences. He is currently Editor-in-Chief of Journal of Classification and a member of the College of the Royal Society of Canada.

  • Abby Flynt

    Abby Flynt06/15/2021

    Abby Flynt is a statistician originally from Buffalo, NY. She received a Bachelor’s Degree in Mathematics Secondary Education from the State University of New York at Fredonia and a Master’s and PhD in Statistics from Carnegie Mellon University. Abby joined the Department of Mathematics at Bucknell University in 2012. She teaches introductory to advanced statistics courses to undergraduates, as well as a Foundation Seminar for first year students on sports analytics and an Integrated Perspectives course for sophomores on Data Science. Abby’s research is broadly focused in machine learning and data science. More specifically, she works on both theoretical and applied problems in clustering with applications in educational research, social justice, public health, and sports. Abby has been on the board of The Classification Society since 2014, currently serving as President and organizer of the 2021 annual meeting at Bucknell.

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Distinguished Dissertation Award


Each year, the Classification Society offers a Distinguished Dissertation Award for an outstanding PhD dissertation on the theme of clustering, classification, or related areas of data analysis, encompassing associated theory and/or applications. The Classification Society Distinguished Dissertation Award is supported by Springer.

2021 Classification Society Distinguished Dissertation Award


Michael Gallaugher, Analysis of Three-Way Data and Other Topics in Clustering and Classification, Baylor University.

Honorable Mention(s)

Salvatore Daniele Tomarchio, Advances in finite mixture models: new methodologies and application, University of Catania.

Nicolas Jouvin, High-dimensional data and graph clustering with discrete latent variable models, Institut Camille Jordan.

Board of Directors

The Classification Board of Directors is composed of four officers, six elected directors, two non-elected directors, the editor-in-chief of the Journal of Classification, and a representative to the International Federation of Classification Societies (IFCS) council.

Journal Publications

The Journal of Classification presents original work in the field of classification, broadly defined. Articles support advances in methodology, while demonstrating compelling substantive applications.

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