Curriculum Vitae

General Information

Full Name Stéphane Guerrier
Contact Stephane.Guerrier [at] unige [dot] ch

Academic Positions

  • Since 2019
    SNSF professorship in Statistics and Data Science, Geneva School of Economics and Management & Faculty of Science (School of Pharmaceutical Sciences), University of Geneva, Switzerland
  • Education

    • , January 2019 - Present. Assistant Professor in Statistics and Data Science (tenure track), Pennsylvania State University, Department of Statistics & Institute for Computational and Data Sciences, PA, USA, July 2017 - December 2018. Assistant Professor in Statistics (tenure track), University of Illinois at Urbana- Champaign, Department of Statistics, IL, USA, July 2014 - June 2017. ́ Visiting Professor, Ecole Polytechnique F ́ed ́erale de Lausanne, Geodetic Engineering Laboratory, Switzerland, May 2016 - July 2016. Visiting Assistant Professor in Statistics, University of California, Santa Bar- bara, Department of Statistics & Applied Probability, CA, USA, September 2013 - June 2014.
    • 2003 - 2008
      École Polytechnique Fédérale de Lausanne – MSc & BSc in Environemental Engineering
      • MSc Thesis: Integration of Skew-Redundant MEMS-IMU with GPS for Improved Navigation Performance, Advisor: Dr. Jan Skaloud
      • Major in Geomatics Engineering and Navigation
      • Minor in Management of Technology and Entrepreneurship
  • Summer 2016
    Software Engineering Intern at Google X
  • Summer 2014
    Software Developer Intern at Microsoft

Research Experience

  • 2017 - now
    Machine Learning for understanding how the brain produces speech
    • Carnegie Mellon University, Pittsburgh, PA, USA
    • Advised by Prof. Tom M. Mitchell and Dr. Barnabàs Pòczos
    • Developing Machine Learning models that analyze neural activity signals (ECoG and Local Field Potentials) in order to understand how different properties of speech are represented in the brain, which can have major consequences for the treatment of many neurological disorders, such as Parkinson’s disease.
  • 2018
    Monte Carlo methods for question answering
    • Carnegie Mellon University, Pittsburgh, PA, USA
    • Advised by Dr. Barnabàs Pòczos
    • Using Monte Carlo Tree Search to answer natural language questions, using background knowledge represented as a graph.
  • 2016 - 2017
    Machine Learning for understanding meaning representation in the brain
    • Carnegie Mellon University, Pittsburgh, PA, USA
    • Advised by Dr. Barnabàs Pòczos and Prof. Tom M. Mitchell
    • Developed Machine Learning models that combine neural activity time series of different modalities. The goal was to use brain activity recordings, such as fMRI, EEG and MEG, to understand how the brain processes language. I focused on Deep Learning models, such as recurrent neural networks.
  • 2014 - 2015
    Computer Vision for unsupervised object discovery in video
    • Carnegie Mellon University, Pittsburgh, PA, USA
    • Advised by Dr. Marius Leordeanu
    • Unsupervised object discovery in video based on multiple frames matching. We also proposed a fast method for detecting the main object of interest in a video, titled VideoPCA.
  • Summer 2013
    Research Internship in Machine Learning at EPFL
    • École Polytechnique Fédérale de Lausanne, Laboratory for Probabilistic Machine Learning
    • Advised by Dr. Matthias Seeger
    • Used topic models to explore the correlation between social media messages from Twitter and the location of the users, with applications to user profiling, topic tracking and content recommendation. I was responsible with applying various machine learning models and parallelizing the code in order to scale well.
  • Summer 2013
    Research for Undergraduates Program
    • Politehnica University of Timisoara, Romania
    • Advised by Prof. Emilia Petrisor
    • Implemented algorithms for spectral clustering of nodes in a graph, based on minimum graph cut, with applications to data mining and statistics, such as clustering information from documents on the web and medical images segmentation.

Honors and Awards

  • Fellowships
  • Awards
    • Best poster award at the Eastern European Machine Learning Summer School in Bucharest, Romania (2019)
    • Machine Learning Department Teaching Assistant Award (2018)
    • Carnegie Mellon University Neurohackathon: 2nd place (2017)
    • KTH University Programming Challenge, Sweden: Top 10 contestants (2013)
    • ACM International Collegiate Programming Contest (ACM-ICPC): Honorable Mention in Southeastern European Regional (2013, 2012, 2011)
    • Microsoft Imagine Cup: Top 20 in the World Finals (2012), 1st team in the Romanian National Finals (2012)
    • Romanian National Olympiad in Informatics: Gold Medal (2008), Bronze Medal (2010), 1st Place (2004), 2nd Place (2005), Honorable Mention (2010, 2008, 2007, 2003)
    • Kangaroo International Mathematical Competition: 2nd prize in Romanian National Finals (2009, 2010)

Teaching Experience

  • Spring 2018
    Teaching Assistant for Graduate Machine Learning
  • Fall 2017
    Teaching Assistant for Topics in Deep Learning
  • 2013-14
    Teaching algorithms for competitive programming
    • Co-organized a competitive programming seminar at Politehnica University of Timisoara for university and high-school students interested to train for algorithmic competitions (e.g. ACM-ICPC, informatics olympiad).
    • Taught algorithms and data structures used in competitive programming, designed and solved practice problems and internal competitions.

Computer skills

  • ○ Programming languages: C, C++, Python, Matlab, Java.
  • ○ Data Structures and Algorithms: Familiarity with concepts used in algorithmic competitions and machine learning research.
  • ○ Frameworks: Tensorflow, NumPy, SciPy, Pandas.
  • ○ Database Systems: MySQL.

Technical Projects

  • LiveX Learning Platform
    • Tutoring system for kindergarten and school children based on a software platform that runs in the cloud, Windows Phone 7 devices and a set of electronic learning cubes called “IQubes” (our hardware invention).
    • Project proposed by our team, called IQube, that competed in the world finals of the Microsoft Imagine Cup competition.
  • Face and Hand Gesture Recognition for Human - Computer Interaction
    • Framework for C++ developers to extend their graphical user interfaces with more natural means of communication.
    • Works in real-time using a computer web camera.
  • Public Transport Route Recommendation
    • Python application for the Timisoara city public transport system using real-time information from GPS devices installed on public transport vehicles.
    • Overlays optimal routes suggestions on Google Maps (before they supported such a feature).
  • Handwritten digits recognition
    • C library implementing various linear algebra methods.

Leadership and Volunteering Activities

  • 2019
  • 2018 - now
    • Founding member of the AI+ Club at Carnegie Mellon University (CMU).
  • 2018 - now
    • Program Committees: ICML (2019), AISTATS (2019, 2020), ICLR (2018, 2020), ICLR-LLD (2019), PLOS ONE (2019).
  • 2018 - 2019
    • Treasurer of the Romanian Students Association at CMU.
  • 2016 - now
    • Member of the Doctoral Review Committee of the Machine Learning Department at CMU.
  • 2016 - now
    • Member of the Education Review Committee of the Machine Learning Department at CMU, which aims to improve the PhD program.
  • 2016 - 2018
    • President of the Romanian Students Association at CMU.
  • 2011 - 2012
    • Student representative in the faculty leadership board at Politehnica University of Timisoara.
  • 2010 - 2011
    • Volunteer for AIESEC, international youth organization.
  • 2010 - 2012
    • Volunteer for Liga AC, student organization at Politehnica University.

Other Interests

  • Sports: squash, volleyball, tennis, climbing, hiking
  • Hobbies: traveling, painting, movies