Severin Gsponer

PhD, Computer Science
University College Dublin
Insight Centre for Data Analytics

Contact

svgsponer@gmail.com
Goolge Scholar
ResearchGate Github

Short Bio

I currently work at IT-Logix in Bern, Switzerland, where I am involved in developing and consulting in the area of Datawarehousing, with a particular focus on datawarehouse automation. Prior to this, I was a member of the contact tracing team for the Health Services of Basel-City, where I was responsible for creating data analytics apps and maintaining a knowledge management system to support the team in their efforts to combat COVID-19. In addition, I contributed to the analysis of data for scientific publications, including co-authoring papers. I also worked at BDO AG in Switzerland, where I helped to develop various data products, specifically, by developing a suitable data architecture and clearly defining the company's needs.

In addition, I teach at the University of Applied Science and Arts Northwestern Switzerland (FHNW), where I manage a machine learning challenge for students to apply their skills to real-world datasets. Before my current role, I was a postdoctoral researcher at the School of Computer Science at University College Dublin, where I focused on using Evolutionary Algorithms, particularly Gene Expression Programming with Covariance Matrix Adaption, for multivariate time series classification, and the potential of Random Kernel Classification. I received my PhD in Computer Science from the School of Computer Science at University College Dublin in 2019. My thesis focused on developing effective and interpretable machine learning algorithms for solving sequence learning problems by learning linear models in all-substring feature spaces. These algorithms are applicable in many domains, such as DNA and amino-acid classification, malware classification, and time series classification. I completed my MSc in 2014 and BSc in 2012 in Computer Science from the University of Basel.

Main Research Interests

  • Sequence Classification and Regression
  • Time Series Classification
  • Interpretable Machine Learning
  • Evolutionary Algorithms
  • Digital Health
  • Bioinformatics
  • Reproducibility in Research

Publications

  • SARS-CoV-2 Vaccine Alpha and Delta Variant Breakthrough Infections Are Rare and Mild but Can Happen Relatively Early after Vaccination Microorganisms 2022, 10(5), 857, Peter J.K., Wegner F., Gsponer S., Helfenstein F., Roloff T., Tarnutzer R., Grosheintz K., Back M., Schaubhut C., Wagner S., Seth-Smith H.M.B., Scotton P., Redondo M., Beckmann C., Stadler T., Salzmann A., Kurth H., Leuzinger K., Bassetti S., Bingisser R., Siegemund M., Weisser M., Battegay M., Sutter S.T., Lebrand A., Hirsch H.H., Fuchs S., Egli A, <pdf>
  • SARS-CoV-2 in schools: genome analysis shows that concurrent cases in the second and third wave were often unconnected Preprint medRxiv 2022, Stange M., Wuerfel E., Peter J.K., Seth-Smith H., Roloff T., Gsponer S., Mari A., Gil B.C. , Lebrand A., Wegner F., Heininger U., Bielicki J., Tschudin Sutter S.,Stadler T., Leuzinger K., Hirsch Hans H., Ledergerber M., Fuchs S., Egli A.; <pdf>
  • An Examination of the State-of-the-Art Multivariate time Series Classification, LISTA 2020, Sorrento, Italy Bhaskar Dhariyal, Thach Le Nguyen, Severin Gsponer, Georgiana Ifrim <pdf>
  • Background Knowledge Injection for Interpretable Sequence Classification, NFMCP 2019, Würzburg, Germany Severin Gsponer, Luca Costabello, Chan Le Van, Sumit Pai, Christophe Gueret, Georgiana Ifrim, Freddy Lecue <pdf>
  • Interpretable Time Series Classification using All-Subsequence Learning and Symbolic Representations in Time and Frequency Domains, DMKD/DAMI, May 2019, Data Mining and Knowledge Discovery, Springer, Thach Le Nguyen, Severin Gsponer, Iulia Ilie, Martin O'Reilly, Georgiana Ifrim (Insight Centre for Data Analytics - University College Dublin). <pdf> <code>
  • Efficient Sequence Regression by Learning Linear Models in All-Subsequence Space, ECML-PKDD 2017, Skopje, Macedonia, Severin Gsponer, Barry Smyth, Georgiana Ifrim (Insight Centre for Data Analytics - University College Dublin). <pdf> <code>
  • Time Series Classification by Sequence Learning in All-Subsequence Space, ICDE 2017 IEEE International Conference on Data Engineering, San Diego, Thach Le Nguyen, Severin Gsponer, Georgiana Ifrim (Insight Centre for Data Analytics - University College Dublin). <pdf> <code>
  • Reproducible Experiments in High-Performance Computing: Techniques and Stencil Compiler Benchmark Study, Presentation at Platform for Advanced Scientific Computing 2014 , ETH Zürich, Helmar Burkhart, Severin Gsponer, Danilo Guerrera, and Antonio Maffia (University of Basel).
  • Reproducible Experiments in High-Performance Computing: Techniques and Stencil Compiler Benchmark Study, Workshop at 1st International Workshop on Reproducibility in Parallel Computing, Porto, Portugal, Danilo Guerrera, Helmar Burkhart, Severin Gsponer, and Antonio Maffia (University of Basel).

Talks

  • Background Knowledge Injection for Interpretable Sequence Classification. September 2019 <slides>
  • Efficient Sequence Regression by Learning Linear Models in All-Subsequence Space. September 2017 <slides>
  • Introduction to Git for Master Students. October 2016 <slides>
  • Machine Learning for Sequence Learning. January 2016 <slides>

Teaching

Lecturer @ FHNW

  • Data Science Challenges-X SS 2022
  • Machine Learning Challenge WS 2021

Teaching assistant / Tutor @ UCD Dublin

  • Data Analytics (COMP47350) SS 2017 / SS 2018 / SS 2020
  • Object Oriented Programming in Python WS 2018
  • Intro to Text Analytics (COMP30810) WS 2018
  • Recommender Systems & Collective Intelligence (COMP475800) SS 2018
  • Object-Oriented Programming (COMP30070) WS 2016/ WS 2017
  • Software Engineering (COMP30670) SS 2016
  • Computer Programming I (COMP10110) WS 2015
  • Introduction to Java (COMP20250) WS 2015
  • Programming I (Python) (COMP10280) WS 2015

Community Services

Program Commitee Member:

  • AAAI Conference on Artificial Intelligence (AAAI 2021)
  • Irish Conference on Artifical Intelligence and Cognitive Science (AICS 2020)
  • International Joint Conference On Artificial Intelligence - Pacific Rim International Conference on Artificatial Intelligenece (IJCA-PRICAI 2020)
  • European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Applied Data Science Track (ECMLPKDD 2020)

Reviewer

  • ACM International Conference on Information and Knowledge Management (CIKM 2020)
  • SIAM International Conference on Data Mining (SDM 2020)
  • IEEE/CAA Journal of Automatica Sinica
  • Machine Learning Journal (Springer)
  • International Conference on Data Mining and Knowledge Discovery (DMKD 2018)
  • European Conference on Machine Learning and Principles and Practice of Knowledge Discover in Databases (ECMLPKDD 2018)
  • International Conference on Knowledge Engineering and Knowledge Management (EKAW 2018)
  • European Conference on Machine Learning and Principles and Practice of Knowledge Discover in Databases (ECMLPKDD 2017)

Smart Pointers

Podcasts

English podcasts

  • Linear Digressions - Regular podcast by Ben Jaffe and Katie Malone about various topics in Machine learning.
  • Data Sceptic - Podcast with Kyle and Linh Da feature longer interviews with active data scientists as well as episodes that introduces basic principles of Data Science.
  • Talking Machines - Katherine Gorman and Neil Lawrence talk about topics in Machine learning and present interesting interviews with researchers and experts in the field.
  • CppCast - Rob Irving and Jason Turner discuss C++ news and have interesting conversations with C++ conference speakers, library authors, writers, ISO committee members and more.

German podcasts

  • Methodisch inkorrekt - Nicolas Wöhrl and Reinhard Remfort present fortnightly four papers from fields of science in a entertaining and informative way.
  • CRE: Technik, Kultur, Geselschaft - Tim Pritlove features in depth interviews with experts from various fields.

Newsletters

These newsletters provide a good overview over the mass of article and news in the field of ML and AI:

  • AI Weekly - Newsletter similar to ML Weekly but for the field of AI.
  • Data Elixir - Curated news and resources about data science.
  • Import AI - A newsletter about artificial intelligence.

These mailing lists contain recent announcements and CfP and are probably more interesting for researchers and people working in academia.

  • Connectionists - Mailing list about neural networks and cognitive or computational neuroscience.
  • ML-News - Google group for announcements and CfP for the machine learning community.
  • UAI - Mailing list for uncertainty in artificial intelligence.