PhD Student Statistics Resume

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Andrew Watson

Phd Student in Statistics

Summary

An enthusiastic, adaptive and fast-learning person with a broad and acute interest in the discovery of new innovative methods, I particularly enjoy collaborating with scientists from different disciplines to develop new skills and solve new challenges.

Skills

  • Mastery of computers (Word, Excel, Access, Power Point).
  • Langage c, Fortran, Matlab.
  • Python, SPSS.

Work Experience

Supervision and support Students

University of California – Science

Jun 2014

Supervision and support of second semester students for up to thirty hours in the subject of Physics and Mathematics.

Tutored students

University of California – Science

Jan 2012

Tutored students during the fall 2011 session in the first semester of the physical sciences.

Education

Phd Student in Statistics

San Jose State University

Present

The subject is “Numerical modeling of co- publication between entities (countries, university, etc) by Gravity Model”.

BIG DATA and Machine Learning

Northeastern University

Aug 2019


Master’s Degree in energy research and materials technology

Arizona State University

Oct 2012


Bachelor in Physical Sciences

University of South Florida

Jul 2010


Software development technician

ECOSIAM

Apr 2010

Evening classes

Project

Oral communication

“A comparison of the most commonly used similarity measures in scientometric research”.

Present

For oral and technical presentation, recognition and appreciation of research contribution to ICSSA 2017: 19th International Confernce on Similarity Search and Applications.

Similarity indexes have been widely used and compared for scientometric research.The main objective of this paper is to provide scientometricians with a practical and informative literature review pertaining to these indexes with respect to scientometric analysis, namely: co-word, co-citation and co-author. 

Project”Cartographie de la coopération scientifique des pays du Maghreb”.

Jul 2016

My role in this project is to focus on understanding, mastering and numerical programming of the normalization indices essential for the construction and visualization of co-occurrence networks and clusters.

Languages

  • English
  • French
  • Arabic
  • German

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