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Vorträge

Prof. Dr. Andreas Groll

  • A hybrid machine learning approach for the modeling and prediction of the UEFA EURO 2020, CMStatistics 2021, 18 December 2021, London, Great Britain.
  • Ein internationaler Studiengang ist akkreditiert – wie geht es weiter? Ein Erfahrungsbericht über den erfolgreichen Betrieb des neuen Masterstudiengangs "Data Science", Vortragsreihe Internationalisierung TU Dortmund, 01 December 2021, Dortmund, Germany.

  • Modeling and Predicting the UEFA EURO 2020 with Hybrid Machine Learning, Research Seminar – University of Naples, 30 September 2021, Naples, Italy.

  • Modeling and Predicting the UEFA EURO 2020 with Hybrid Machine Learning, 11th S-TRAINING (digital) Meeting, 10 September 2021, Naples, Italy.

  • Wie man mit Statistik den Fußball-Europameister vorhersagen kann, SchnupperUni, 10 August 2021, Dortmund, Germany.

  • A Modern Hybrid Machine Learning Approach for the Prediction of International Football Matches, Virtual ISI World Statistics Congress, 11-16 July 2021, Den Haag, Netherlands.

  • Mit Statistik die Fußball-EM vorhersagen, Virtueller Tag der Statistik, 25 June 2021, Dortmund, Germany.

  • Wer wird Fußball-Europameister? - Wie man Spaß berechnen kann, Zwischen Brötchen und Borussia, 12 June 2021, Dortmund, Germany.

  • An Overview of Modeling and Prediction Approaches for Football Data, 2nd S-TRAINING (digital) Meeting, 30 October, 2020, Dortmund, Germany.

  • Prediction methods for football data (and more) - an overview (Invited Speaker), Round Table on “Statistics in Sports”, 18 September, 2020, Brescia, Italy.

  • Interpretable Machine & Statistical Learning in (Sports) Medicine, EORS2020 Congress 2020, 17-18 September 2020, Izmir, Turkey.

  • New Methods for Statistical Learning, Dortmund Data Science Center, 16. June, 2020, Dortmund, Germany.

  • An adaptive lasso Cox frailty model for time-varying covariates based on the full likelihood, CMStatistics 2019, 14.-16. December 2019, London, Great Britain.

  • An adaptive lasso Cox frailty model for time-varying covariates based on the full likelihood, IWSM 2019, 7.-12. July 2019, Guimaraes, Portugal.

  • Prediction of the 2019 IHF World Men’s Handball Championship – A sparse Gaussian approximation model, ASMDA 2019, 11.-14. June 2019, Florence, Italy.

  • A hybrid random forest approach for modeling and prediction of international soccer matches (Invited Keynote Speaker), 51es Journées de Statistique, 3.-7. June 2019, Nancy, France.

  • Effect Selection in Cox Frailty Models by Regularization Methods, Research Seminar, 6th February 2019, Helmut-Schmidt-University Hamburg, Germany.

  • Modellierung und Vorhersage von internationalen Fußballturnieren, Dortmunder Tag der Statistik, 5th February 2019, TU Dortmund University, Germany.

  • Boosting methods for effects selection in Cox frailty models, CMStatistics 2018, 14.-16. December 2018, Pisa, Italy.

  • A hybrid random forest approach for modeling and prediction of international soccer matches, Workshop: Sports Analytics on Soccer, 12th November 2018, TU Dortmund University, Germany.

  • Statistische Modellierung von Fußballspielen, Tag der offenen Tür, 10th November 2018, TU Dortmund University, Germany.

  • A Comparison of Covariate-based Prediction Methods for FIFA World Cups, Sports, Data & Journalism Conference, 25th October 2018, Zurich, Switzerland.

  • A Comparison of Covariate-based Prediction Methods for FIFA World Cups, Zurich R User Group Meetup, 25th October 2018, Zurich, Switzerland.

  • Wenn Bäume die WM vorhersagen …, EinsteinSlam -Physik in 10 Minuten! Domicil, 20th September 2018, Dortmund, Germany.

  • Effect Selection in Cox Frailty Models by Regularization Methods (Invited Speaker), Statistische Woche 2018, 11.-14. September 2018, Linz, Austria.

  • Boosting Methods for Effects Selection in Cox Frailty Models, IWSM 2018, 16.-20. July 2018, Bristol, Great Britain.

  • Führt Andrés Iniesta Spanien zum Titel? Science Slam, TU Dortmund University, 5th July 2018, Dortmund, Germany.

  • Modelling and Predicting Matches in International Football Tournaments with Random Forests, 7th German-Japanese Symposium, 3rd July 2018, Dortmund, Germany.

  • Machine Learning Methods for the Prediction of International Football Tournaments, Tech Lunch, 22nd June 2018, Scalable Capital, Munich, Germany.

  • A Comparison of Covariate-based Prediction Methods for FIFA World Cups, SMTDA 2018, 12.-15. June 2018, Chania, Greece.

  • Predicting Matches in International Football Tournaments with Random Forests, SEPS Research / Quantitative Methods Seminar, University of St. Gallen, 19th April 2018, Switzerland.

  • Modeling and Prediction of International Soccer Matches, Mathematical Colloquium, 20th December 2017, TU Clausthal, Germany.

  • Selection of Effects in Cox Frailty Models by Regularization Methods, CMStatistics 2017, 16.-18. December 2017, London, Great Britain.

  • Modeling and Prediction of International Soccer Matches, Workshop on Big Data Analytics in Sports, 16th November 2017, Brescia, Italy.

  • Selection of Effects in Cox Frailty Models by Regularization Methods, Statistische Woche 2017, 19.-22. September 2017, Rostock, Germany.

  • LASSO-Type Penalization in the Framework of Generalized Additive Models for Location, Scale and Shape, IWSM 2017, 03.-07. July 2017, Groningen, Netherlands.

  • On the Dependency of Soccer Scores - A Sparse Bivariate Poisson Model for the UEFA European Football Championship 2016, MathSport International 2017 Conference, 26.-28. July 2017, Padua, Italy.

  • The Statistical View on Randomness - An Excursion, Beta Kontext Series on General Phenomena, 6th May, 2017, Berlin, Germany.

  • Selection of Effects in Cox Frailty Models by Regularization Methods, Institutskolloquium, Department of Statistics, LMU Munich, 1st February 2017, Germany.

  • Modeling Football Results Using Match-specific Covariates, Empirical Economics and Econometrics Seminar, University of Innsbruck, 24th November 2016, Austria.

  • Modeling Football Results Using Match-specific Covariates, Munich Datageeks Data Day, 8th October 2016, Munich, Germany.

  • Who's the Favorite? – A Bivariate Poisson Model for the UEFA European Football Championship 2016, Institutskolloquium, Department of Statistics, LMU Munich, 15th June 2016, Germany.

  • Modeling Football Results in Penalized Ordinal Bradley-Terry Models Including Match-specific Covariates, DAGStat, 14.-18. March 2016, Göttingen, Germany.

  • Regularization in Cox Frailty Models, IWSM 2015, 06.-10. July 2015, Linz, Austria.

  • Prediction of major international soccer tournaments based on team-specific regularized Poisson regression: An application to the FIFA World Cup 2014, A Symposium on World Football Cup, 11.-12. May 2015, Athens, Greece.

  • Employment and Fertility – A Comparison of the German Family Survey 2000 and the PAIRFAM Panel, SMTDA 2014, 11.-14. June 2014, Lisbon, Portugal.

  • Prediction of the FIFA World Cup 2014 by a regularized random effects model, 4th June 2014, Institutskolloquium, Department of Statistics, LMU Munich, Germany.
  • A Consistent 2-Factor Model for Pricing Temperature Derivatives, 2014 International Conference on Commodity Markets, 16.-17. January 2014, Paris, France.

  • Variable Selection for Generalized Linear Mixed Models by L1-Penalized Estimation, Economic Risk Seminar, 02.12.2013, Humboldt University of Berlin, Germany.

  • Employment and Fertility – A Comparison of the German Family Survey 2000 and the PAIRFAM Panel, y-BIS 2013, 19.-21. September 2013, Istanbul, Turkey.

  • A Study on European Football Championships in the GLMM Framework with an Emphasis on UEFA Champions League Experience, AMSDA, 25.-28. June 2013, Barcelona, Spain.

  • Estimation of Stochastic Employment and Unemployment Intensities, DAGStat, 18.-23. March 2013, Freiburg, Germany.

  • Variable Selection for Generalized Linear Mixed Models by L1-Penalized Estimation, CEN, 12.-15. September 2011, Zurich, Switzerland.

  • Variable Selection for Generalized Additive Mixed Models by Likelihood-based Boosting, AMSDA, 07.-10. June 2011, Rome, Italy.

  • Ordinal Random Effects Models Including Variable Selection, BioMed-S Retreat, 22.-23. July 2010, Höhenried, Germany.

  • Variable Selection in Generalized Mixed Models, DAGStat, 23.-26. March 2010, Dortmund, Germany.

  • Generalized Additive Mixed Models Based on Boosting, DStatG Nachwuchsworkshop, 3.-5. June 2009, Merseburg, Germany.

Anfahrt & Lageplan

Der Campus der Technischen Universität Dortmund liegt in der Nähe des Autobahnkreuzes Dortmund West, wo die Sauerlandlinie A45 den Ruhrschnellweg B1/A40 kreuzt. Die Abfahrt Dortmund-Eichlinghofen auf der A45 führt zum Campus Süd, die Abfahrt Dortmund-Dorstfeld auf der A40 zum Campus-Nord. An beiden Ausfahrten ist die Universität ausgeschildert.

Direkt auf dem Campus Nord befindet sich die S-Bahn-Station „Dortmund Universität“. Von dort fährt die S-Bahn-Linie S1 im 15- oder 30-Minuten-Takt zum Hauptbahnhof Dortmund und in der Gegenrichtung zum Hauptbahnhof Düsseldorf über Bochum, Essen und Duisburg. Außerdem ist die Universität mit den Buslinien 445, 447 und 462 zu erreichen. Eine Fahrplanauskunft findet sich auf der Homepage des Verkehrsverbundes Rhein-Ruhr, außerdem bieten die DSW21 einen interaktiven Liniennetzplan an.
 

Zu den Wahrzeichen der TU Dortmund gehört die H-Bahn. Linie 1 verkehrt im 10-Minuten-Takt zwischen Dortmund Eichlinghofen und dem Technologiezentrum über Campus Süd und Dortmund Universität S, Linie 2 pendelt im 5-Minuten-Takt zwischen Campus Nord und Campus Süd. Diese Strecke legt sie in zwei Minuten zurück.

Vom Flughafen Dortmund aus gelangt man mit dem AirportExpress innerhalb von gut 20 Minuten zum Dortmunder Hauptbahnhof und von dort mit der S-Bahn zur Universität. Ein größeres Angebot an internationalen Flugverbindungen bietet der etwa 60 Kilometer entfernte Flughafen Düsseldorf, der direkt mit der S-Bahn vom Bahnhof der Universität zu erreichen ist.