Ewch i’r prif gynnwys
Dr Andreas Artemiou

Dr Andreas Artemiou

Lecturer

Yr Ysgol Mathemateg

Email:
artemioua@cardiff.ac.uk
Telephone:
+44 (0)29 2087 0616
Location:
Adeilad Mathemateg ac Addysg, Ffordd Senghennydd, Caerdydd, CF24 4AG
Sylwebydd y cyfryngau
Ar gael fel goruchwyliwr ôl-raddedig

Education

  • PhD – Statistics, Pennsylvania State University, USA, 08/2010.
  • M.Sc. – Statistics, Pennsylvania State University, USA, 05/2008.
  • BSc – Mathematics and Statistics (minor Computer Science), University of Cyprus, Cyprus, 06/2005.

Previous positions

  • 09/2012-05/2013 New Researcher Fellow at the Statistics and Applied Mathematics Instittute
  • 08/2010 – 08/2013 Assistant Professor, Department of Mathematical Sciences, Michigan Technological University, USA

Anrhydeddau a Dyfarniadau

  • Eleneio Dissertation Award, Greek Statistical Institute (2011)
  • Teaching Award, Department of Statistics, Pennsylvania State University, (2008)

Aelodaethau proffesiynol

  • Royal Statistical Society
  • British Classification Society
  • International Association of Statistical Computing
  • Institute of Mathematical Statistics
  • American Statistical Association
  • Greek Statistical Institute

Ymrwymiadau siarad cyhoeddus

Invited talks

International Symposium on Business and Industrial Statistics. Invited Talk: "Dimension Reduction through LqSVM", Durham, NC, June 2014.

1st International Symposium on Nonparametric Statistics. "Using machine learning for sufficient dimension reduction.&ldquo Halkidiki, Greece, June 2012

Greek Statistical Institute meeting 2011. "Hyperplane Alignment for sufficient dimension reduction: Implementation, Application and afdvantages", Patra, Greece, April 2011

Contributed talks

European Meeting of Statisticians 2015: "A machine learning approach for robust sufficient dimension reduction", Amsterdam, July 2015

2014 RSS Annual meeting. Contributed Talk: _Sufficient dimension reduction through Support Vector Machine variantsŒ, September 2014, Sheffield, UK.

Joint Statistical Meeting 2013: "Using large margin classifies for sufficient dimension reduction", Montreal, Canada, August 2013

Joint Statistical Meeting 2012: "Slice inverse mean difference for sufficient dimension reduction", San Diego, CA, July 2012

14th meeting of New Researchers in Statistics and Probability: "Using machine algorithm in sufficient dimension reduction", San Diego, CA, July 2012

Workshop on Statistical Inference Complex/High Dimensional Problems: "On the use of machine learning techniques in the sufficient dimension reduction framework" Vienna, Austria, July 2012

Joint Statistical Meeting 2011: "Hyperplane Alignment for sufficient dimension reduction: Implementation, Application and afdvantages", Miami, FL, August 2011

Joint Statistical Meeting 2010: "Predictive potential of Kernel Principal Support Vector Machine", Vancouver, Canada August 2010

Joint Statistical Meeting 2008: "Principal Components and regression: A statistical explanation of a natural phenomenos", Denver, CO, August 2008

2019

2018

2017

2016

2015

2014

2013

2011

2009

2007

I teach the following modules:

  • MA2002 Matrix Algebra
  • MA0263 Introduction to Computational Statistics

Postgraduate students

Students graduated (since 2000)

  • Master of Science: Lipu Tian at Michigan Technological University (2012)
  • Former Research Assistants: Min Shu at Michigan Technological University

Current students

  • Timothy Vivian-Griffiths, Ph.D., School of Medicine, Cardiff University
  • PhD student: Luke Smallman, School of Mathematics, Cardiff University (start: 10/2015)

Research interests

  • Unsupervised dimension reduction methodology like PCA and its effectiveness when it is applied in a regression setting.
  • Supervised dimension reduction like sufficient dimension reduction.  Using machine learning ideas in the sufficient dimension reduction framework.   
  • Machine learning algorithms.
  • Kernel methods.                                    
  • Applications of dimension reduction and machine learning ideas to massive/high dimensional real datasets.

External funding

Expired: US National Science Foundation, Division of Mathematical Sciences, 09/2012 $110000