The Classification Society

The Classification Society 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 Chapman and Hall/CRC.

The 2019 Classification Society Distinguished Dissertation Award

The 2019 Award winner will be invited to make a presentation in a special session at the 2019 Classification Society Annual Meeting (location and date to be determined). The Classification Society will cover travel expenses to the 2019 Annual Meeting of at most 1,000 USD for a North American-based Award winner or at most 1,500 USD for an Award winner based elsewhere. 

Criteria for nomination for the Award include: 

  • the main topic of the dissertation is in classification, clustering or a closely related area; 
  • the dissertation contains innovative work in theory/methodology and/or or innovative or well developed application(s); and 
  • the literature review is thorough. 


To be eligible for nomination, a Ph.D. dissertation must have been successfully completed – including successful defense – within the calendar year 2018. Nominations may be made by the dissertation author, supervisor, or related person, and must be sent by email. A nomination must include contact information for the nominator and nominee (if different), a URL where an online copy of the dissertation can be accessed by the members of the Award Committee, and an electronic (e.g., scanned) cover letter, written and signed by the nominator, stating the date of final completion of the Ph.D. dissertation and outlining why the dissertation merits the award. The nominator must also arrange for two external referee reports to be sent directly to the chair of the Award committee. If possible, the referees should be arms-length from the dissertation author and their supervisor. Cover letters should include full bibliographic details for any published papers, proceedings, book chapters, or similar scholarly material that have arisen from the dissertation. For non-English language dissertations, nominators are requested to provide an extended abstract in English and, where relevant, to highlight any papers, proceedings, book chapters, or similar scholarly material associated with the dissertation that have been published in English. 


The award committee consists of:

  • Prof. Volodymyr Melnykov (chair), 
  • Prof. Katrijn Van Deun, and 
  • Prof. Hans Friedrich Kohn. 

Nominations and external referee reports must be submitted to the chair of the Award Committee, Prof. Volodymyr Melnykov at 
< vmelnykov at culverhouse dot ua dot edu > on or before 11:59pm (EST) on February 1, 2019. Results will be announced approximately two months after this submission deadline.

2018 Classification Society Distinguished Dissertation Award Winners

  • Yang Tang, Dimensionality Reduction with Non-Gaussian Mixtures, McMaster University, 2017.
  • Michael Fop, Advances in Model-Based Clustering and Classification, University College Dublin, 2017.

Previous Award Winners and Nominees

2017 Classification Society Distinguished Dissertation Award

  • Winner:
    Paula Murray, Detecting Non-Elliptical Clusters, McMaster University, 2016.

2016 Classification Society Distinguished Dissertation Award

  • Winner:
    Zsuzsa Bakk, Contributions to Bias Adjusted Stepwise Latent Class Modeling, Universiteit Leiden, 2015.
  • Honorable Mention:
    Samuel Ventura, Large-Scale Classification and Clustering Methods with Application in Record Linkage, Carnegie Mellon University, 2015.

2015 Classification Society Distinguished Dissertation Award

  • Winner:
    Irene Vrbik, Non-Elliptical and Fractionally Supervised Classification, University of Guelph, March 2014.
  • Honorable Mention:
    Hsin-Hsiung Huang, Information Extraction For Virus Classification And Robust Dimension Reduction, University of Illinois at Chicago, 2014.
  • Shortlist:
    Brian Franczak, Mixtures of Shifted Asymmetric Laplace Distributions, University of Guelph, March 2014.
    Utkarsh Dang, Mixtures of Power Exponential Distributions and Topics in Regression-based Mixture Models, University of Guelph, March 2014.
2014 Classification Society Distinguished Dissertation Award
  • Winner: 
    Kim de Roover, Clusterwise & Switching Component Models For Modeling Between-& Within-Block Structural Differences In Multivariate Multiblock Data, KU Leuven, 2013.
  • Honorable Mention:
    Kate MorrisDimension Reduction and Clustering using Non-Elliptical Mixtures, University of Guelph, December 2013.
2013 Classification Society Distinguished Dissertation Award
  • Winner: 
    Jeffrey L. Andrews, Model-Based Learning: t-Families and Variable Selection, University of Guelph, June 2012.
  • Honorable Mention:
    Carel PeetersBayesian Exploratory and Confirmatory Factor Analysis, VU University Amsterdam, June 2012.
    Sanjeena Dang Subedi, Model Based Clustering Using Eigen-decomposed Covariance Structure in a Variational Bayes Framework, University of Guelph, June 2012.

2012 Classification Society Distinguished Dissertation Award

  • Winner: 
    Theodore Damoulas, Probabilistic Multiple Kernel Learning, Cornell University, 2011
  • Honorable Mention: 
    Ondrej Vencalek, Depth-based Classification, Palacky University, Olomouc, 2011

2011 Classification Society Distinguished Dissertation Award

  • Winner:
    Frank Busing, Advances in MultiDimensional Unfolding, Leiden University, The Netherlands, April 2010.
  • Travel Award Winners:
    David Casado de Lucas, Classification Techniques for Time Series and Functional Data, Universidad Carlos III de Madrid, Spain, July 2010.
    Pedro Contreras, Search and Retrieval in Massive Data Collections, University of London, May 2010.
    Jorge Tendeiro, Some Mathematical Results on Three-Way Component Analysis, University of Groningen, The Netherlands, October 2010.
    Hongxia Yang, Nonparametric Bayes Models for High-Dimensional and Sparse Data, Duke University, December 2010
  • Shortlist:
    Silvia Liverani, Bayesian Clustering of Curves and the Search of the Partition Space, The University of Warwick,
    January 2010.
    Sara Garza Villarreal, A Process for Extracting Groups of Thematically Related Documents in Encyclopedic Knowledge Web Collections by Means of a Pure Hyperlink-based Clustering Approach, Tec de Monterrey (ITESM), Mexico, May 2010.

2010 Classification Society Distinguished Dissertation Award

  • Winner:
    Daniel Aloise, Exact Algorithms for Minimum Sum-of-Squares Clustering, University of Montreal, June 2009.
  • Honorable mention:
    Petri Kontkanen, Computationally Efficient Methods for MDL-Optimal Density Estimation and Data Clustering, University of Helsinki, Finland, November 2009.
  • Shortlist:
    Clintin P. Davis-Stober, Luce’s Challenge: Quantitative Models and Statistical Methodology, University of Illionois at Urbana-Champaign, 2009.
    T. Siva Tian, Dimensionality Reduction for Classification with High-Dimensional Data, University of Southern California, August 2009.
    Joost van Rosmalen, Segmentation and Dimension Reduction: Exploratory and Model-Based Approaches, Erasmus Universiteit Rotterdam, April 2009.
2009 Classification Society Distinguished Dissertation Award
  • Winner:
    Innar Liiv, Pattern Discovery Using Seriation and Matrix Reordering: A Unified View, Extensions and an Application to Inventory Management, Tallinn University of Technology, August 2008.
  • Honorable mention:
    Georgi Nalbantov, Essays on Some Recent Penalization Methods with Applications in Finance and Marketing, Erasmus University Rotterdam, September 2008.
  • Shortlist:
    Matthijs Warrens, Similarity Coefficients for Binary Data, Leiden University, June 2008.
    Carolin Strobl, Statistical Issues in Machine Learning – Towards Reliable Split Selection and Variable Importance Measures, Institut für Statistik der Fakultät für Mathematik, Informatik und Statistik der Ludwig-Maximilians-Universität München, May 2008.
    Walid Sharabati, Multi-Mode and Evolutionary Networks, George Mason University, October 2008.
    Chia-Yi Chiu, Cluster Analysis for Cognitive Diagnosis: Theory and Applications, University of Illinois at Urbana-Champaign, August 2008.
    Pietro Coretto, The Noise Component in Model-Based Clustering, University College London, September 2008.
2008 Classification Society Distinguished Dissertation Award
  • Winner:
    Anita Van der Kooij, Prediction Accuracy and Stability of Regression with Optimal Scaling Transformations, Leiden University, June 2007. Link to homepage.
  • Runner-up:
    Jonathan Schler, Authorship Analysis in the Absence of a closed Candidate Set, Bar-Ilan University, Ramat-Gan, Israel, January 2007.
  • Honorable mention: 
    Balazs Feil, Fuzzy Clustering in Process Data Mining, (University of Veszprem, Pannonia), Hungary, Sept. 2006, published as monograph Cluster Analysis for Data Mining and System Identification, by Birkhaeuser, 2007 
    Jorge Santos, Data Classification with Neural Networks and Entropic Criteria, (ISEP – Instituto Superior de Engenharia do Porto, Porto, Jan. 2007).
  • Shorlist:
    Jorge Caiado, Distance-based methods for classification and clustering of time series, ESCE / Polytechnic Institute of Setubal, Portugal, 2006.
    Hans-Friedrich Koehn, The Structural Representation of Three-Way Proximity Data, University of Illinois, Urbana-Champaign, 2007.
    Cem Iyigun, Probabilistic Distance Clustering, Rutgers University, November 2007.
    Teemu Roos, Statistical and Information-Theoretric Methods for Data Analysis, University of Helsinki, June 2007. 
    Link to homepage.
    Nema Dean, Variable Selection and Other Extensions of the Mixture Model Clustering Framework, University of Washington, Seattle, 2006.
    Marielle Linting, Nonparametric Inference in Nonlinear Principal Components Analysis: Exploration and Beyond, Leiden University, October 2007.
    Anita Van der Kooij, Prediction Accuracy and Stability of Regression with Optimal Scaling Transformations, Leiden University, June 2007. Link to homepage.

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