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Massimiliano Pontil

Senior Researcher Tenure Track - Principal Investigator

Research Line

Computational Statistics and Machine Learning

Center

IIT Central Research Labs Genova

Contacts

+39 010 2897 409
Contact Me

About

Massimiliano Pontil received an MSc degree in Physics from the University of Genova in 1994 (summa cum laude) and a PhD in Physics from the same University in 1999. His main research interests are in machine learning, function representation and approximation, numerical optimization, regularization methods, and statistical learning theory. He has made contributions in the areas including kernel methods, multitask and transfer learning, online learning, sparsity regularization, and statistical learning theory. He also studied machine learning applications arising in affective computing, bioinformatics, computer vision, and user modelling, among others. He has published over 30 international journals papers, 10 book chapters and 60 peer reviewed conference proceedings. His research papers have been cited approximately 12,000 times and his h-index is 47 (Google Scholar, March 2016). He was a full time member of academic staff at University College London (UCL) between 2003 and 2015, a Research Associate in the Department of Information Engineering at University of Siena (2001--2002) and a Post-doctoral Fellow at the Massachusetts Institute of Technology (1998--2000). He has been on the programme committee of the main machine learning conferences, including the Annual Conference on Learning Theory (COLT), the International Conference on Machine Learning (ICML), and the Annual Conference on Neural Information Processing Systems (NIPS). He is on the editorial board of the Machine Learning Journal, Statistics and Computing, the Journal of Machine Learning Research, and he is on the Scientific Advisory Board of the Max Planck Institute for Intelligent Systems.

Projects

Research Grants

2010–2014 EPSRC grant EP/H027203/1 entitled “Structured Sparsity Methods in Machine Learning and Convex Optimisation”, Lead PI.

2011–2013 Royal Society International Joint Project 2010/R2, Sole PI.

2009–2011 Consultant for US Air Force grant FA9550-09-1-0511, entitled “Estimation, Approximation and Computation in Learning Theory” (PIs: Profs. C.A. Micchelli and Y. Xu)

2007–2010 BBSRC grant BB/E017452/1 entitled “Prediction of Protein-Protein Interaction Hot Spots using a Combination of Physics and Machine Learning”, £368,821, co-PI (PI: Prof. David Jones, UCL).

2006–2011 EPSRC grant EP/D071542/1 entitled “A New Generation of Trainable Machines for Multi-task Learning”, Sole PI.

2006 EPSRC grant EP/D052807/1 entitled “Study of Regularization Methods in Machine Learning”, Sole PI.

2004–2006 EPSRC grant GR/T18707/017 entitled “Novel Machine Learning Methods Based on Techniques from Approximation, Estimation and Computation”, Sole PI.

2005–2007 IST Programme IST-2002-506778 of the European Community, entitled “Multi-task Learning: Optimization Methods and Applications”, Lead PI.

2003–2005 Senior Participant of US National Science Foundation Grant ITR-0312113, entitled “Adaptive Kernel Based Machine Learning Methods” (PIs: Profs. Y. Xu and C.A. Micchelli).

2002 Italian Ministry of Education, University and Research (MIUR) Project “Giovani Ricercatori” entitled “Feature Selection with Kernel Machines Techniques”.

 

Advisory Boards

2013 Evaluation Committee, Ecole Normale Superieure de Cachan, France.

2012–2017 Scientific Advisory Board, Max Planck Institute for Biological Cybernetics, Germany.

 

Editorial Board

2013– Journal of Machine Learning Research, Action Editor.

2013– Statistics and Computing.

2009– Machine Learning Journal.

2004–2006 Pattern Recognition Letters.

 

Invited talks

Over 40 Invited conference presentations and 50 invited seminars/lectures/colloquia at Universities and Research Institutes.

 

Program Committees

2016 International Conference on Machine Learning (ICML), Area Chair.

2016 International Conference on Pattern Recognition Applications and Methods (ICPRAM).

2015 Neural Information Processing Systems (NIPS), Area Chair.

2015 International Conference on Machine Learning (ICML), Area Chair.

2015 Annual Conference on Learning Theory (COLT).

2014 International Conference on Machine Learning (ICML), Area Chair.

2013 Neural Information Processing Systems (NIPS), Area Chair.

2013 International Workshop on Similarity-Based Pattern Analysis and Recognition (SIMBAD).

2012 International Conference on Artificial Intelligence and Statistics (AISTATS), Area Chair.

2011 Annual Conference on Learning Theory (COLT).

2011 International Workshop on Similarity-Based Pattern Analysis and Recognition (SIMBAD).

2010 Annual Conference on Learning Theory (COLT).

2010 Eighth International Workshop on Mining and Learning with Graphs (MLG-2010).

2009 NIPS Workshop on Transfer Learning for Structured Data.

2009 International Conference on Algorithmic Learning Theory Conference (ALT).

2009 International Conference on Machine Learning (ICML), Area Chair.

2008 Annual Conference on Learning Theory (COLT).

2007 European Conference on Machine Learning (ECML).

2006 Annual Conference on Learning Theory (COLT).

2006 Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition and Statistical Techniques in Pattern Recognition.

2005 Annual Conference on Learning Theory (COLT).

2004 International Conference on Machine Learning (ICML).

 

Organization

2015 Co-organizer, Dagstuhl Seminar 15152, entitled ”Machine Learning with Interdependent and Non-identically Distributed Data, Dagstuhl, Germany.

2012 Co-organizer, ICML Workshop entitled “Object, Functional and Structured Data: Towards Next Generation Kernel-Based Methods”, Edinburgh, Scotland.

2010 Co-organizer, Conference entitled “Information Representation and Estimation”, UCL, UK.

2009 Co-organizer, Workshop entitled “Sparsity in Machine Learning and Statistics”, Cumberland Lodge, UK.

2006 Co-organizer, Open House on “Multi-Task and Complex Outputs Learning”, UCL, UK.

2005 Co-chair, NIPS Workshop entitled “Inductive Transfer: 10 Year Later”, British Columbia, Canada.

2005 Co-chair, NIPS Workshop entitled “Accuracy-Regularization Frontier”, British Columbia, Canada.

2003 Session Co-organizer, European Symposium of Artificial Neural Networks (ESANN), Bruges, Belgium.

1999 Co-organizer, Workshop entitled “Support Vector Machines: Theory and Applications”, Crete, Greece.

 

Teaching Activity

Dept of Computer Science, UCL:

Graduate and 3rd year course entitled “Supervised Learning”, Fall 2010–2014.

Graduate and 3rd year course entitled “Mathematical Methods for Machine Learning”, Fall 2009–2014.

Graduate and 4th year course entitled “Advanced Topics in Machine Learning”, Spring 2010 and 2011.

Graduate and 4th year course entitled “Advanced Topics in Machine Learning”, Spring 2005 and 2006.

Graduate and 3rd year course entitled “Supervised Learning”, Fall 2005.

MScCS course entitled “Fundamentals of Mathematics”, Fall 2005 (10 lectures).

Graduate and 3rd year course entitled “Information Theory”, Fall 2003 and 2004.

Elsewhere:

Master Course entitled “Advanced Machine Learning”, Ecole Polytechnique, University Paris-Saclay, March 2015 (12 lectures).

PhD course entitled “Kernel-based Methods” University Carlos III of Madrid, September 2002 (12 lectures).

PhD course entitled “Elements of Statistical Learning”, University of Florence, Spring 2002 (20 lectures).

3rd year course entitled “Introduction to Machine Learning”, University of Siena, Spring 2002 (24 lectures).

PhD course entitled “Statistical Learning Theory”, City University of Hong Kong, February 2002 (10 lectures).

1st year course entitled “Fundamentals of Computer Science”, Univ. of Florence, Fall 2001 (40 lectures).

Awards

Best Paper Runner Up, 2013 International Conference on Machine Learning, Atlanta, USA.

Scientific Advisory Board, Max Planck Institute for Intelligent Systems, Germany, 2012-2017.

EPSRC Advanced Research Fellowship, UK, 2006–2011.

Edoardo R. Caianiello Award for the Best Italian PhD Thesis on Connectionism, Italy, 2002.

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