Data Science Lab

Bern Data Science Day 2022-05-06

The Bern Data Science Day brings together data scientists from the University of Bern, the Bern University Hospital, sitem-insel and the Psychiatric University Clinic (UPD) for a unique conference on applied Data Science (DS). It gathers scientists from different domains to network and exchange ideas on emerging trends and research results in data science. The stimulating program will focus on extended poster sessions in lobby mode for networking facilitation, the keynote talks framing the event. Everyone working with or on aspects of data processing is invited to submit abstracts related to the below topics. Abstracts are reviewed by the scientific committee for oral and poster presentation. Vote winning contributions will receive prizes from our sponsors. Posters are reviewed and invited for voluntary upload to the BORIS Publications University of Bern repository with DOI for reference.

Important dates and deadlines

Abstract submission: April 1
Registration: April 1
Notification to authors: April 15
Poster submission: May 1
Conference day: May 6
Repository submission: May 31


UniS, University of Bern, Schanzeneckstrasse 1, CH-3012 Bern, Switzerland

Agenda May 6

08:45 - 09:00 S 003 Opening session (J. Ziegel)
09:00 - 10:00 S 003 Keynote (Christian Althaus chaired by C. Tretter)
10:15 - 11:00 Foyer, A 017, A 019 Poster session 1
11:00 - 11:15 Foyer Coffee Break
11:15 - 12:00 Foyer, A 017, A 019 Poster session 2
12:00 - 13:00   Lunch (not provided)
13:30 - 14:30 S 003 Plenary with 4 selected oral presentations (chaired by C. Beisbart)
14:30 - 15:00 Foyer Coffee break
15:00 - 16:00 Foyer, A 017, A 019 Poster session 3
16:00 - 16:45 S 003 Poster reward and voting session (S. Haug, M. Reyes, A. Tzovara)
16:45 - 17:00 S 003 Closing session (J. Ziegel)
17:00 - 19:00 Foyer Apero with 10 highest ranked posters



Keynote at 09:00

Althaus Christian L., PD PhD

Description: Computational epidemiology has played an important role during the public health response against the COVID-19 pandemic. In my presentation, I will talk about the historical background of the research field from its early origins in the 18th century to the rapid development during the past two decades. I will then illustrate how Bayesian modeling, high-performance computing, genomic surveillance, and digital contact tracing have been used to understand the transmission dynamics of and the impact of public health interventions against COVID-19. Finally, I will give an outlook into how methods from statistical and machine learning can support the integration of multiple multidimensional data sources for monitoring the COVID-19 pandemic in the future.

Dr. Christian L. Althaus is a computational epidemiologist and head of the Interfaculty Platform for Data and Computational Science (INPUT) at the Institute of Social and Preventive Medicine (ISPM) at the University of Bern, Switzerland. After studying biology at ETH Zurich (Switzerland), he received his doctorate in theoretical biology at Utrecht University (The Netherlands). In 2017, he qualified as a university lecturer at the University of Bern medical faculty in the field of infectious disease epidemiology. He uses mathematical and computational modeling in combination with data analyses to investigate how the population biology of infectious diseases is affected by environmental changes, dynamic patterns of host immunity, or public health interventions. Dr. Althaus is an expert for emerging infectious diseases and made significant contributions to the better understanding of the transmission dynamics of Ebola, MERS, and COVID-19. He is a member of the Multidisciplinary Center for Infectious Diseases (MCID) at the University of Bern and served as a member of the Swiss National COVID-19 Science Task Force in 2020.

Organization Committee and Contact

Anna Broccard, Claire Dove, Sigve Haug (chair), Alexander Kashev, Petra Müller (conference email).

Scientific Committee

Prof. Dr. Dr. C. Beisbart, Prof. Dr. P. Favaro, Prof. Dr. D. Ginsbourger, PD Dr. S. Haug, Prof. Dr. M. Reyes, Prof. Dr. R Sznitman, Prof. Dr. C. Tretter, Prof. Dr. A. Tzovara, Prof. Dr. J. Ziegel.

Our sponsors (with real money)

The event participation is free of charge. Our sponsors cover the costs.

If you like to sponsor the event, please contact the organising committee (email above). External sponsors pay 500 CHF. Internal sponsors pay 300 CHF or more.  If desired, each sponsor can have a poster wall and a table for its material and discussions, in addition to the usual logo and link placements.

The Bern Data Science Day is an event from the Bern Data Science Initiative