PRESENTATIONS (invited unless otherwise indicated)

  • January, 2024. Institute for Mathematical Statistics - Asia-Pacific Rim Meeting (IMS-APRM), Melbourne, Australia. The Detection of Differentially Expressed Genes via Cluster-Specific Contrasts of Mixed Effects.

  • December, 2023. The Banff International Research Station (BIRS)-IASM Workshop: Harnessing the Power of Latent Structure Models and Modern Big Data Learning Hangzhou, China. An Apparent Paradox in Semi-Supervised Learning.

  • December, 2023. The 16th International Conference of the ERCIM WG (European Research Consortium for Informatics and Mathematics Working Group) on Computational and Methodological Statistics (CMStatistics 2023), Berlin Learning of Classifiers from Partially Classified Training Data.

  • December, 2023. The 67th Annual Meeting of the Australian Mathematical Society (AustMS 2023), Brisbane, Australia. A Surprising Result in Semi-Supervised Learning.

  • July, 2023. The IMECS 2023 Conference of the International Association of Engineers, Hong Kong. An Apparent Paradox in Machine Learning: Semi-Supervised Learning Can Typically Produce More Accurate Classifiers than Full Supervision (keynote).

  • August, 2022. CSDA & EcoSta Workshop on Statistical Data Science, Bologna. A Most Surprising But Useful Result in Semi-Supervised Learning (keynote).

  • August, 2022. 24th International Conference on Computational Statistics (COMPSTAT 2022), Bologna. Some Skew Distributions Useful in Model-Based Clustering.

  • July, 2021. Seminar Series, Department of Statistics, University of New South Wales, Sydney. Semi-Supervised Learning of a Classifier from a Statistical Perspective .

  • December, 2019. The 12th International Conference of the ERCIM WG (European Research Consortium for Informatics and Mathematics Working Group) on Computational and Methodological Statistics (CMStatistics 2019), London. On the Role of Latent Variables in Characterizing Some Skew Distributions.

  • September, 2019. Conference of the CLAssification and Data Analysis Group (CLADAG) of the Italian Statistical Society, Cassino, Italy. Mixture Modelling with Skew-Symmetric Component Distributons.

  • August, 2019. The 2019 Conference of the International Federation of Classification Societies (IFCS) , Thessaloniki, Greece. Estimation of Classification Rules from Partially Classified Data.

  • July, 2019. Research School on Statistics and Data Science 2019 Institute for Advanced Study, La Trobe University, Melbourne. Flexible Modelling via Multivariate Skew Distributions.

  • July, 2019. Statistical Society of Australia (Queensland Branch) Statistics Career Seminar: Lead with Statistics, University of Queensland. Teaching and Researching in Statistics at UQ.

  • June, 2019. The 3rd International Conference on Econometrics and Statistics (EcoSta 2019) at the National Chung Hsing University (NCHU), Taiwan. The NCHU 2019 Keynote Lecture. Recent Advances on Mixtures of Skew Distributions for Modelling Heterogeneous and Asymmetric Data.

  • January, 2019. Big Data 2019. 5th International Winter School on Big Data at the University of Cambridge. Co-organized by the Cambridge Big Data Initiative of the University of Cambridge and the Institute for Research Development, Training and Advice (IRDTA), Brussels/London. Applying Finite Mixture Models to Big Data.

  • December, 2018. The 11th International Conference of the ERCIM WG (European Research Consortium for Informatics and Mathematics Working Group) on Computational and Methodological Statistics (CMStatistics 2018), Pisa. On the use of latent variables to extend Gaussian mixture models.

  • August, 2018. Advances in Finite Mixture and Other Non-Regular Models, Guangxi Normal University, Guilin, China. Some Extensions of Gaussian Mixture Models via Hidden Variables (Opening Plenary).

  • July, 2018. 2018 Winter School in Mathematical & Computational Biology, St. Lucia, Brisbane. A Need for Caution in Clustering and Classifying High-Dimensional Data.

  • June, 2018. The 2nd International Conference on Econometrics and Statistics (EcoSta 2018), Hong Kong. Mixture Modelling of High-Dimensional Data.

  • December, 2017. The 10th International Conference of the ERCIM WG (European Research Consortium for Informatics and Mathematics Working Group) on Computational and Methodological Statistics (CMStatistics 2017), London. A Multithreaded Implementation of the EM Algorithm for Finite Mixture Models.

  • November, 2017. School of Mathematics and Physical Sciences, Nanyang Technological University, Singapore.

  • August, 2017. The 2017 Conference of the International Federation of Classification Societies (IFCS) , Tokai University, Tokyo. Acceptance presentation for the IFCS Research Medal (plenary).

  • July-August, 2017. Joint Statistical Meetings 2017, Baltimore. A Parallel EM Algorithm for Statistical Learning via Mixture Models.

  • July, 2017. The Annual Summer Session of the Working Group on Model-Based Clustering, University of Perugia Perugia. Multithreaded Implementation of the EM algorithm: Applications to Skew Mixture Models.

  • June, 2017. The 1st International Conference on Econometrics and Statistics (EcoSta 2017), Hong Kong. Testing for Group Structure.

  • December, 2016. The 9th International Conference of the ERCIM WG (European Research Consortium for Informatics and Mathematics Working Group) on Computational and Methodological Statistics (CMStatistics 2016), Sevilla. Adoption of Skew Distributions in Mixtures of Factor Models.

  • December, 2016. 2016 AUT Mathematical Sciences Symposium, Auckland. Modelling and Clustering via Multivariate Skew Distributions. (keynote)

  • November, 2016. Advances in Statistics and Econometrics Workshop organized by the National Centre for Econometric Research (NCER), Brisbane. On the Use of Some Non-Normal Distributions for the Modelliing and Clustering of Data in the Presence of Skewness and Outliers (plenary).

  • September, 2016. MBC^2 - Workshop on Model Based Clustering and Classification, organized with the support of the Italian Statistical Society and the Classification and Data Analysis Group (CLADAG), the Università di Catania, Catania. Hidden Components of Skew Distributions - A Cautionary Warning (contributed talk).

  • August, 2016. COMPSTAT 2016, Oviedo, Spain. On Mixture Modelling with Multivariate Skew Distributions.

  • August, 2016. Joint Statistical Meetings 2016, Chicago. Bruce Lindsay and Mixture Models in Memorial Session for Bruce Lindsay.

  • February, 2016. Seminar. Universitat Pompeu Fabra, Barcelona. Modelling and Clustering via Mixtures of Multivariate Skew t-Distributions.

  • February, 2016. Big Data 2016. 2nd International Winter School on Big Data at DeustoTech, School of Engineering, University of Deusto in Bilbao, Spain. Big Data Extensions of Some Methods of Classification and Clustering.

  • December, 2015. The 8th International Conference of the ERCIM WG (European Research Consortium for Informatics and Mathematics Working Group) on Computational and Methodological Statistics (CMStatistics 2015), London. On the Adoption of a Mixed Effects Model to Classify Multiple Samples Represented by Mixture Distributions.

  • October, 2015. Colloquium. Queensland Chapter of the IEEE Computational Intelligence Society (CIS). Griffith University, Gold Coast Campus. On Modelling and Clustering via Mixture Distributions.

  • August, 2015. Joint Statistical Meetings 2015, Seattle. On Finite Mixtures of Some Skew Distributions.

  • July, 2015. 60th World Statistics Congress -ISI 2015, Rio de Janeiro. Model-Based Clustering of Single and Multiple Samples.

  • July, 2015. The Annual Summer Session of the Working Group on Model-Based Clustering, University of Washington, Seattle. Clustering via Mixtures of Skew Symmetric Component Distributions.

  • July, 2015. International Society for NonParametric Statistics (ISNPS) 2015 Meeting "Biosciences, Medicine, and novel Non-Parametric Methods," Graz, Austria. Correcting for Selection Bias via Cross-Validation in the Classification of High-Dimensional Data (keynote).

  • July, 2015. The 2015 Conference of the International Federation of Classification Societies (IFCS), the University of Bologna, Bologna. Clustering via Mixture Models with Flexible Components.

  • May, 2015. Science at the Shine Dome 2015, Canberra. Finite Mixture Distributions: Statistical Modelling and Inference.

  • April, 2015. Seminar. University of Toulon, France. On Some Mixture Distributions for Modelling Complex Datasets.

  • February, 2015. Seminar. Discipline of Business Analytics, The University of Sydney Business School. Some Recent Results on Skew Versions of the Normal Distribution for Modelling Asymmetric Data with Applications to Financial Data.

  • December, 2014. The 7th International Conference of the ERCIM Working Group on Computational and Methodological Statistics (ERCIM 2014), Pisa. A Latent Variable Model for Clustering Data with Structure.

  • November, 2014. The Twelfth Australasian Data Mining Conference (AusDM 2014), Brisbane. Making Sense of a Random World through Statistics (keynote).

  • November, 2014. 2014 Joint NZSA+ORSNZ Conference, Victoria University of Wellington, New Zealand. Modelling, Clustering, and Cluster Matching of Multiple Samples via Skew Distributions (opening plenary).

  • November, 2014. 2014 Shayle Searle Visiting Fellow in Statistics at Victoria University of Wellington, Wellington, New Zealand. Mixture Models with High-Dimensional Data.

  • September, 2014. Seminar. Department of Statistics, University of Padua, Padua. On Finite Mixtures of Skew t-Distributions.

  • September, 2014. Seminar. Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno, Salerno. Mixture Models with High-Dimensional Data.

  • September, 2014. Seminar. Department of Statistics, University of Bologna, Bologna. Joint Clustering and Matching of Multivariate Samples Across Objects.

  • September, 2014. Seminar. Department of Quantitative Methods for Economics, University of Milano-Bicocca, Milan. On Extensions of Normal Mixtures for Modelling Complex Datasets.

  • September, 2014. MBC^2 - Workshop on Model Based Clustering and Classification, organized by the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, the Università di Catania, Catania. On Finite Mixtures of Canonical Fundamental Skew t-Distributions (contributed talk).

  • August, 2014. COMPSTAT 2014, Geneva. Mixture of regression models with latent variables and sparse coefficient parameters. (contributed paper presented by coauthor Angus Ng).

  • July, 2014. Joint Australian Statistical Conference 2014/IMS Annual Meeting, Sydney. Applying Mixture Models to High-Throughput Data.

  • June, 2014. The 31st International Conference on Machine Learning (ICML 2014), Beijing. Mixture Models for Cluster Analysis.

  • May, 2014. Statistical Society of Canada 2014 Annual Meeting, Toronto. On Finite Mixtures of Skew Distributions.

  • May, 2014. Biometry Workshop of the Department of Agriculture, Fisheries and Forestry, Marburg, Queensland. High-Dimensional Data (keynote).

  • December, 2013. 2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2013), Shanghai. Conference Co-Chair. Using Cluster Analysis to Improve Gene Selection in the Formation of Discriminant Rules for the Prediction of Disease Outcomes (contributed talk).

  • December, 2013. 6th International Conference of the ERCIM Working Group on Computational and Methodological Statistics (ERCIM 2013), London. On Mixtures of Skew Factor Models.

  • November, 2013. Seminar. INRIA Grenoble Rhone-Alpes, France. Modelling via Mixtures of Skew Distributions.

  • August, 2013. ISI (International Statistical Institute) 2013 Satellite Meeting on Statistics in Business, Industry, and Risk Management, sponsored by the ISI Committee on Risk Analysis and ISBIS (International Society for Business and Industrial Statistics), City University of Hong Kong, Hong Kong. Non-Normal Mixture Models with Applications to Financial Data. (opening plenary).

  • August, 2013. ISI Young Statisticians' Meeting (2013 YSI), Department of Statistics and Actuarial Science of the University of Hong Kong, Hong Kong. On the Fitting of Mixture Models to High-Dimensional Data.

  • July, 2013. The 20th Annual Summer Session of the Working Group on Model-Based Clustering, the University of Bologna, Bologna. On Mixtures of Skew Distributions.

  • July, 2013. 12th Conference of the International Federation of the Classification Societies (IFCS 2013), the University of Tilburg, Tilburg, Netherlands. Tutorial on Some Recent Advances in Mixture Modelling and talk titled On Finite Mixtures of Skew Distributions.

  • July, 2013. The 28th Edition of the International Workshop on Statistical Modelling (IWSM), the Dipartimento di Scienze Statistiche e Matematiche, Universita di Palermo, Palermo, Italy. On Finite Mixtures of Skew Distributions (plenary).

  • May, 2013. The IL-SONG Lecture at the 2013 The Korean Statistical Society Spring Annual Meeting, State University of New York (SUNY) Korea, Sandgo, Icheon, South Korea. Extending the Role of Finite Mixtures of Distributions in Modelling and Clustering (keynote).

  • May, 2013. Seminar, Chonnam National University, Gwangju, South Korea. Extending the Role of Finite Mixtures of Distributions in Modelling and Clustering.

  • December, 2012. 5th International Conference of the ERCIM Working Group on Computing & Statistics, Oviedo, Spain. On Some Recent Results for Mixtures of Skew Normal and Skew t-Distributions.

  • October, 2012. Program on Meeting the Challenges of High Dimension: Statistical Methodology, Theory and Applications, Institute for Mathematical Sciences, National University of Singapore. Talk on Clustering High-Dimensional Data via Finite Mixture Models and four tutorial lectures on On Modelling High-Dimensional Data via Finite Mixture Distributions.

  • October, 2012. Seminar, School of Mathematical & Physical Sciences, Nanyang Technological University, Singapore. Fitting Mixtures of Skew Normal and Skew t-Distributions with Applications in Flow Cytometry.

  • September, 2012. The Centre for Mathematics and its Applications (CMA) Special Year on Inverse Problems: The One-Day Seminar (S4) on Statistical Aspects of Inverse Problem, the Australian National University (ANU), Canberra. On Mixtures of Factor Models in High-Dimensional Problems.

  • September, 2012. MBC^2 - Workshop on Model Based Clustering and Classification, organized by the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, the Università di Catania, Catania. On Mixtures of Skew Normal and Skew t-Distributions (keynote).

  • August, 2012. COMPSTAT 2012, Limassol, Cyprus. Mixture Models for High-Dimensional Data. Tutorial on Mixture Models for High-Dimensional Data.

  • August, 2012. XXVIth International Biometric Conference, Kobe, Japan. Mixtures of Skew Distributions for an Automated Approach to the Analysis of Flow Cytometric Data.

  • July, 2012. Distinguished Lecture in Bioinformatics, University of Guelph, Canada. On Some Microarray Gene Expression-Based Approaches to Disease Discovery, Diagnosis, and Prognosis.

  • June, 2012. International Symposium on Business and Industrial Statistics 2012 (ISBIS 2012), Bangkok, Thailand. Some Extensions of Normal Mixtures Models with Examples.

  • February, 2012. Fifth Annual ASEARC Research Conference, University of Wollongong. On Some Applications of Mixture Models in Bioinformatics.

  • January, 2012. Bioinformatics Workshop, University of Technology Sydney, Sydney. On Improving the Power of Tests for the Detection of Differential Expression via Mixture Models.

  • December, 2011. 7th IASC-ARS (Joint Meeting of the 2011 Taipei International Statistical Symposium and the 7th Conference of the Asian Regional Section of the IASC, Institute of Statistical Science, Academia Sinica, Taipei. On Automated Flow Cytometric Data Analysis.

  • December, 2011. ICDM 2011 (The 11th IEEE International Conference on Data Mining), Vancouver. Acceptance presentation for the IEEE ICDM Research Contributions Award (plenary).

  • October, 2011. Colloquium, School of Mathematical Sciences, University of Adelaide, Adelaide. On the Ever Increasing Role of Mixture Distributions in the Modelling of Heterogeneous Data. Statistics Seminar, Statistical Modelling for Some Problems in Bioinformatics.

  • August-September, 2011. Joint Conference of the International Federation of Classification Societies with the German Classification Society (GfKl) and the German Association for Pattern Recognition (DAGM) , Frankfurt. Presidential Address: The Ever-Increasing Role of Mixture Models in Classification (plenary).

  • August, 2011. Joint Statistical Meetings, Miami Beach, Florida. Clustering of High-Dimensional Data via Factor Models.

  • June, 2011. 39th Annual Meeting of the Statistical Society of Canada, Acadia University, Wolfville, Nova Scotia, Canada. Clustering via Mixtures of Skew Normal or Skew t-Distributions.

  • May, 2011. HDS2011 (High Dimensional Statistics: Advances and Challenges), Nanyang Technological University, Singapore. Modelling High-Dimensional Data via Factor Models.

  • December, 2010. ICDM 2010 (The 10th IEEE International Conference on Data Mining), Sydney. Assessing the Significance of Groups in High-Dimensional Data (keynote).

  • December, 2010. Colloquium on Data Sciences, Knowledge Discovery and Business Intelligence, Sydney. On Applications of the EM Algorithm.

  • December, 2010. The 3rd International Conference of the ERCIM (European Research Consortium for Informatics and Mathematics) Working Group on Statistics & Computing, University of London, London. Modelling of Multivariate Data via Mixtures of Skew Normal and Skew-t Distributions.

  • December, 2010. Seminar, Laboratoire Statistique et Genome, Universite d'Evry, Evry, Paris. Modelling High-Dimensional Data via Factor Models.

  • November, 2010. BioInfoSummer 2010, AMSI Summer Symposium in Bioinformatics, WEHI (The Walter and Eliza Hall Institute for Medical Research), Melbourne. The EM Algorithm and Applications.

  • October, 2010. Workshop: GWAS Mega-Analysis for Complex Diseases - part of ISMB 2010 (The 11th International Conference on Systems Biology), Edinburgh. Few Samples with Many Features - Lessons Already Learned from Microarray Analyses.

  • September, 2010. The 54th Annual Meeting of the Australian Mathematical Society, University of Queensland, St. Lucia, Brisbane. The Clustering of High-Dimensional Data.

  • September, 2010. Seminar, School of Mathematics and Statistics Seminar Series, University of South Australia, Adelaide. On the Development of Microarray Gene Expression-Based Signatures in Disease Prognosis.

  • August, 2010. RECOMB 2010 (Fourteenth International Conference on Research in Computational Molecular Biology), Lisbon. Automated High-Dimensional Flow Cytometric Data Analysis.

  • August, 2010. Joint Statistical Meetings, Vancouver. Multiple Hypothesis Testing by Clustering of Gene (Variable) Profiles (contributed paper presented by coauthor Leesa Wockner).

  • July, 2010. WCCI (World Congress in Computational Intelligence) 2010, Barcelona. Identifying Fibre Bundles with Regularised k-Means Clustering Applied to Grid-Based Data (contributed paper presented by coauthor Dr. Vladimir Nikulin).

  • July, 2010. The 17th Annual Summer Session of the Working Group on Model-Based Clustering, INRIA-Grenoble Rhone-Alpes. Fitting Mixtures of Multivariate Normal Distributions to High-Dimensional Data via Factor Models (keynote).

  • July, 2010. ICME 2010 (International Conference on Complex Medical Engineering), Gold Coast. On the Development of Microarray Gene Expression-Based Signatures in Cancer Prognosis (keynote).

  • July, 2010. LASR (Leeds Annual Statistical Research Workshop) 2010, Leeds, U.K. Clustering of High-Dimensional Data with Application to Gene-Expression Data.

  • May, 2010. Workshop in Bioinformatics and Genetics Epidemiology organzied by the University of Puerto Rico and the University of Texas MD Anderson Cancer Centre, San Juan, Puerto Rico. Estimating the Local False Discovery Rate in the Detection of Differential Expression between Two Classes.

  • May, 2010. Statistical Seminar, University of Padua, Padua. Fitting Mixtures of Multivariate Normal Distributions to High-Dimensional Data Using Factor Models.

  • March, 2010. Conference on Resampling Methods and High Dimensional Data, Texas A&M University. Assessing the Statistical Significance of Clusters in High-Dimensional Data.

  • March, 2010. Mixture Estimation and Applications, International Centre for Mathematical Sciences, Edinburgh. The Modelling of High-Dimensional Data via Normal Mixture Models.

  • Feburary, 2010. Statistical Modelling and Inference Conference to celebrate Murray Aitkin's 70th birthday, Queensland University of Technology Gardens Point, Brisbane. The EM Algorithm with Applications to Finite Mixture Modelling.

  • January, 2010. Bioinformatics 2010, Valencia, Spain. On a Gradient-Based Algorithm for Matrix Factorization Applied to Dimensionality Reduction.

  • December, 2009. DICTA (Digital Image Computing: Techniques and Applications) 2009, Melbourne. Multivariate Skew t-Mixture Models: Application to Fluorescence-Activated Cell-Sorting Data (contributed talk).

  • November, 2009. IEEE BIBM 2009 - IEEE International Conference on Bioinformatics & Biomedicine, Washington, D.C. On a General Method for Matrix Factorization Applied to Supervised Classification.

  • November, 2009. Statistical Methods in Genetics and Bioinformatics, Queensland University of Technology, Brisbane. Statistical Analysis of Gene-Expression Data.

  • October, 2009. BA2009 - Bioinformatics Australia Conference, Melbourne. The Combination of Clinical Factors and Genetic Markers Can Improve Cancer Prognosis (contributed paper presented by coauthor Dr Kim-Anh Le Cao).

  • October, 2009. The Australasian Conference on Statistical Methods for Genomic Data Analysis, Queensland University of Technology, Brisbane. Large-Scale Simultaneous Inference with Applications to the Detection of Differential Expression.

  • October, 2009. CIBB 2009 - Sixth International Meeting On Computational Intelligence for Bioinformatics and Biostatistics, Genoa, Italy. Regularised k-Means Clustering for Dimension Reduction Applied to Supervised Clustering (contributed paper presented by coauthor Dr Vladimir Nikulin).

  • September-October, 2009. 53rd Annual Meeting of the Australian Mathematical Society, University of South Australia, Adelaide. Large-Scale Simultaneous Inference via Mixture Models.

  • September, 2009. Royal Statistical Society Conference 2009, Edinburgh. The Influence of the EM Paper by Dempster et al.

  • September, 2009. Workshop of the Young Statisticians Section (YSS) of the Royal Statistical Society, Edinburgh. Some Applications of the EM Algorithm.

  • July, 2009. The 4th International Conference on Rough Sets and Knowledge Technology (RSKT 2009), Gold Coast, Queensland. Statistical Methodology and Applications in Bioinformatics (keynote).

  • June, 2009. The Classification Society and Interface Society Annual Meetings, Washington University, St. Louis. Mixture Models in Multiple Hypothesis Testing (contributed talk).

  • March, 2009. 11th Conference of the International Federation of the Classification Societies (IFCS 2009) - jointly with the 33rd Conference of the German Classification Society (GfKl), Dresden, Germany. Use of Mixture Models in Multiple Hypothesis Testing with Applications in Bioinformatics (contributed talk).

  • December, 2008. Celebrating Sue Wilson's 34 Years at ANU, Australian National University, Canberra. On Mixture Models in Multiple Hypothesis Testing.

  • November, 2008. Second Annual Workshop on Statistical Methods for Genetic Analysis, Queensland University of Technology, Brisbane. On Selection Biases in Classification Based on Gene Expression Signatures.

  • October, 2008. Third IAPR Conference in Pattern Recognition in Bioinformatics, Melbourne. On Some Problems in the Statistical Analysis of Microarray Gene-Expression Data.

  • August, 2008. Compstat 2008, Portico, Portugal. Latent Class Modelling via Mixture Models with Random Effects.

  • July, 2008. GfKl 2008 German Classification Society 32nd Annual Conference, Hamburg. Clustering of High-Dimensional Data via Finite Mixture Models.

  • July, 2008. XXIV International Biometric Conference, Dublin. Invited discussant in Invited Session on Critical Evaluation of Statistical Methods Proposed for Microarray Analysis.

  • July, 2008. The Australian Statistical Conference, Melbourne. Clustering of Gene Expression Profiles via Mixture Regression Models with Random Effects.

  • June, 2008. Inference and Estimation in Probabilistic Time-Series Models, Isaac Newton Institute for Mathematical Sciences, Cambridge, UK. Clustering of Time Course Gene-Expression Data via Mixture Regression Models.

  • June, 2008. Quantitative Biology and Applied Statistics Seminar, The University of Reading, Reading. The Statistical Analysis of Microarray Gene-Expression Data.

  • May, 2008. CRiSM (Centre for Research in Statistical Methodology) Seminar, The University of Warwick, Coventry. On Simple Mixture Models in High-Dimensional Testing for the Detection of Differentially Expressed Genes.

  • March-April, 2008. High Dimensional Statistics in Biology, Isaac Newton Institute for Mathematical Sciences, Cambridge, UK. On Mixture Models in High-Dimensional Testing for the Detection of Differential Gene Expression.

  • Jan-June, 2008. Program on Statistical Theory and Methods for Complex, High-Dimensional Data, Isaac Newton Institute for Mathematical Sciences, Cambridge (invited participant).

  • December 2007. CMLS 2007- International Symposium on Computational Models for Life Sciences, Gold Coast, Queensland, Australia. Detection of Differential Expression with Microarray Data (keynote).

  • November, 2007. Symposium on Mixture Modelling with Special Interest to Applications in Educational Measurement and Bioinformatics, Katholieke Universiteit Leuven, Belgium. Mixture Modelling of High-Dimensional Data (plenary).

  • September 2007. Annual meeting of the Spanish Society of Statistics and Operational Research (SEIO), Valladolid, Spain. Statistical Analysis of Microarray Data.

  • September 2007. Opening statistics seminar of the academic year (with discussion), Department of Statistics, University of Bologna. Large-Scale Simultaneous Inference with Applications to the Detection of Differential Expression with Microarray Data.

  • September, 2007. CLADAG2007. Sixth Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, Macerata. Clustering of High-Dimensional and Correlated Data (Plenary Talk).

  • August, 2007. 56th Meeting of the International Statistical Institute, Lisbon. Invited discussant in Specialized Topic Session on Latent Class Analysis and Classification Issues.

  • June, 2007. 2007 Winter School in Mathematical and Computational Biology, ARC Centre in Bioinformatics and Institute for Molecular Bioscience, University of Queensland. Large-Scale Simultaneous Inference for the Detection of Differential Expression with Microarray Data.

  • December, 2006. BioInfoSummer 2006 - ICE-EM Summer Symposium in Bioinformatics, Centre for Bioinformation Science ANU, Canberra. Testing for Differential Gene Expression.

  • December, 2006. Workshop on Intelligent Systems for Bioinformatics (WISB-2006), Hobart. Clustering Replicated Microarray Data via Mixtures of Random Effects Models for Various Covariance Structures (contributed talk).

  • November, 2006. Bioinformatics Australia 2006, Sydney. Finding Differentially Expressed Genes in Multiclass Microarrays Using a Mixture Model Approach (contributed talk).

  • September, 2006. Macquarie University, Sydney. Microarray Data Classification.

  • September, 2006. Computational Statistics International School, Universita di Naples Federico II. Clustering by Normal Mixture Models (plenary).

  • September, 2006. Knowledge Extraction and Modelling IASC-INTERFACE-IFCS Workshop, Isle of Capri. Clustering of Gene-Expression Profiles.

  • August, 2006. One-Day Workshop at the Joint Statistical Meetings 2006. Methods and Computational Tools for the Screening and Classification of Microarray Gene Expression Data (joint with Kim-Anh Do and Keith Baggerly), Seattle.

  • July, 2006. XXIIIrd Meeting of the International Biometric Society, Montreal. Some Issues Associated with Testing for Gene Differential Expression.

  • July, 2006. Australian Statistical Conference/New Zealand Statistical Association Conference 2006, Auckland. Clustering of High-Dimensional Data.

  • June, 2006. 2006 Winter School in Mathematical and Computational Biology, ARC Centre in Bioinformatics and Institute for Molecular Bioscience, University of Queensland. Classification of Microarray Data.

  • April, 2006. One-Day Workshop at The University of Waikato, Hamilton, New Zealand. Statistical Methods for the Screening and Classification of Microarray Gene Expression Data.

  • February, 2006. Meeting of the Canberra Branch of the Statistical Society of Australia, Canberra. Some Applications of Statistics in Bioinformatics.

  • December, 2005. International Conference in Statistics, Kuala Lumpur, Malaysia. Some Applications of Mixture Models to Microarray Data in Bioinformatics (plenary).

  • September, 2005. Association for the Advancement of Animal Breeding and Genetics(AAABG) 16th Conference, Noosa. Using Mixture Models to Detect Differentially Expressed Genes.

  • July, 2005. Bioinformatics Symposium 2005, HELP University College, Kuala Lumpur, Malaysia. An Introduction to the Statistical Analysis of Microarray Gene-Expression Data (keynote).

  • July, 2005. Perspectives in Modern Statistical Inference III, Mikulov, Czech Republic. Robust Cluster Analysis via Mixture Models.

  • July, 2005. Sixth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL2005),Brisbane. Selection Bias and Other Issues in Applications of Machine Learning in Bioinformatics (keynote).

  • June, 2005. Joint Annual Meeting of the Interface and Classification Society of North America, St. Louis, Missouri. Model-Based Clustering of High-Dimensional Data in session on Model-Based Clustering/Classification in High-Dimensional Data and A Model-Based Approach to Multiple Hypothesis Testing via Mixture Models in session on Model Building with Applications to Mixtures and Bioinformatics.

  • May, 2005. Workshop on Oncogenetics, Florence. Invited discussion of paper by Professor Lucio Luzzatto (Tuscany Cancer Institute), titled The Molecular Basis of Cancer.

  • May, 2005. Statistics for Functional Genomicists and Functional Genomics for Statisticians, Florence. Sponsored by the Nutrigenomics Organization (a European Union VI Framework Network of Excellence) and the Tuscany Cancer Institute. Class Discovery and Class Prediction: Unsupervised and Supervised Clustering Probabilistic Models (joint with C. Romualdi et al.).

  • May, 2005. Meeting of the Statistical Society of Australia (Queensland Branch), Brisbane. The Role of Statistics in Bioinformatics.

  • February, 2005. ANU Mathematical Sciences Institute Workshop on High-Dimensional Approximation, Canberra. On High-Dimensional Statistical Learning.

  • January, 2005. The 3rd Asia-Pacific Bioinformatics Conference, Singapore. Classification of Microarray Data: Recent Statistical Approaches. Tutorial (with Liat Ben-Tovim Jones).

  • December, 2004. BioInfoSummer 2004, Canberra. The Classification of Microarray Data (keynote).

  • November, 2004. Statistical and Applied Mathematical Sciences Institute (SAMSI), Research Triangle Park, North Carolina. Model-Based Clustering of Microarray Gene-Expression Data .

  • November, 2004. Department of Statistics and Operations Research, University of North Carolina, Chapel Hill. Discriminant Analysis of Microarray Gene-Expression Data.

  • September, 2004. International Conference on Bioinformatics 2004, Auckland. Classification of Microarray Gene Expression Data (keynote).

  • September, 2004. Bioinformatics Group, Walter & Eliza Hall Institute (WEHI) of Medical Research, Melbourne. Model-Based Clustering of Microarray Gene-Expression Data.

  • September, 2004. School of Mathematics and Statistics, University of West Australia. Analyzing Microarray Gene-Expression Data.

  • August, 2004. Joint Statistical Meetings, Toronto. Robust Mixture Modelling.

  • June, 2004. International Meeting of the Psychometric Society, Pacific Grove, California. Mixture Model-Based Clustering of High-Dimensional Data (keynote).

  • May, 2004. Interface 2004: Computational Biology and Bioinformatics, Baltimore. Supervised and Unsupervised Learning Methods for Gene-Expression Data.

  • February, 2004. Sydney Summer Statistics Workshop - 2004, University of Sydney. Model-Based Classification with High-Dimensional Data.

  • February, 2004. New Zealand Summer School of Bioinformatics, Auckland. Multivariate Techniques in the Statistical Analysis of Gene-Expression Data.

  • November-December, 2003. Invited lecturer at the winter school jointly sponsored by the universities in the French-speaking part of Switzerland, Villars-Sur-Ollon, Switzerland. Lectures on Finite Mixture Models and The EM Algortihm.

  • November, 2003. The fourth international conference for the Critical Assessment of Microarray Data Analysis (CAMDA 2003), Durham, North Carolina. Use of Microarray Data via Model-Based Classification in the Study and Prediction of Survival from Lung Cancer (presentation of finalist paper in the CAMDA 2003 Challenge).

  • September-October, 2003. Workshop of the Institute for Mathematics and its Applications on Statistical Methods for Gene Expression: Microarrays and Proteomics, University of Minnesota. Classification of Microarray Gene-Expression Data.

  • September, 2003. Opening plenary at the 5th Congresso Nazionale of the Italian Region of the International Biometric Society, Marina di Massa. Some Applications of Mixture Models

  • July, 2003. Royal Statistical Society Workshop on The Statistical Analysis of Gene Expression Data, Wye College Conference Centre, Kent, England. Classification of Tissue Samples on the Basis of Microarray Gene-Expression Data.

  • August, 2002. Workshop: Perspectives in Modern Statistical Inference II, Brno, Czech Republic. On Variants of the EM Algorithm for the Fitting of Finite Mixture Models.

  • December, 2001. International Conference on Statistics, Combinatorics and Related Areas on the 25th anniversary of the Forum for Interdisciplinary Mathematics, University of Wollongong. Clustering of Directional Data.

  • August, 2001. Workshop, Joint Statistical Meetings, Atlanta. Applying Finite Mixture Models.

  • July, 2001. Mixtures 2001 - Recent Developments in Mixture Modelling, Hamburg. Modelling High-Dimensional Data by Mixtures of Factor Analyzers.

  • March, 2001. 25th Annual Conference of the German Classification Conference - GfKl (2001), Munich. On Clustering by Mixture Models.

  • March, 2001. Workshop in Statistical Mixtures and Latent-Structure Modelling, Edinburgh. On the Incremental EM Algorithm for Speeding Up the Fitting of Finite Mixture Models.

  • November, 2000. Seminar at University of California Irvine. Applying Mixture Models to Data.

  • November, 2000. Seminar at the MD Anderson Cancer Centre, Houston. Role of Mixture Models in Survival Analysis.

  • November, 2000. Seminar at Rice University, Houston. On Some Computational Aspects of the Fitting of Normal Mixtue Models.

  • November, 2000. Seminar at the SAS Institute, Cary, North Caroilina. Finite Mixture Models.

  • August, 2000. ASA Invited Session on Bayesian Statistics, Joint Statistical Meetings, Indianapolis. On Computational Aspects of Clustering via Mixtures of Normal and t Components.

  • August, 2000. Biometrics Invited Workshop, Joint Statistical Meetings, Indianapolis. Applying Finite Mixture Models.

  • September, 1999. Symposium on Chaos and Non-Linear Time Series, Kyushu University, Fukuoka, Japan. Modelling Nonlinearity by Mixtures of Factor Analyzers via Extensions of the EM Algorithm.

  • June, 1999. 31st Symposium on the Interface, Chicago. Computing Issues for the EM Algortihm in Mixture Models.

  • February, 1999. Information, Decision and Control - 99, Adelaide. Vector Quantization, Clustering, and Data Compression via Finite Mixture Models.