Lehrstuhl für Statistik und ihre Anwendungen in Wirtschafts- und Sozialwissenschaften




Partnership Program LMU - Tel Aviv University



Data Science – Combining Statistics and Computer Science


Munich, 8. November 2018


This workshop intends to promote Data Science building on the essential contributions of both, Statistics and Computer Science. Both universities, LMU and Tel Aviv University (TAU) have recently established a track record in the field of Data Science.

The LMU hosts the Elite Master program Data Science (www.datascience-munich.de) which is run jointly by the departments of statistics and computer science and is funded by the Bavarian state within the Elitenetzwerk Bayern.
At TAU, recently a Data Science Center has been established which aims to bundle the activities in this direction (https://datascience.tau.ac.il/).
Both groups emphasize the definition of Data Science as the intersection of statistics and computer science, which holds in research as well as in education.

The goal of the workshop is to explore the potential of collaboration between data scientists from TAU and LMU.
We envisage not only joint research activities but also a mutual exchange of students in the corresponding master programs. Potentially interdisciplinary collaborations between data scientists and researchers in the application field is a further goal of the workshop.

Conference Venue
The workshop takes place at Ludwig-Maximilians-Universität, Bibliothek der Wirtschaftswissenschaften und Statistik,
Freskensaal - R115 (1st floor), Ludwigstrasse 28. (google maps)

for this workshop ends on Friday, November 2, 2018. Please register with iris.burger@stat.uni-muenchen.de


Workshop Program

09:00 – 09:10  OPENING

09:10 - 09:20
LMU-TAU Research Cooperation Program

09:20 - 09:35
Goeran Kauermann, Munich
Data Science @ LMU/Germany

09:35 - 09:50
David M. Steinberg, Tel Aviv
Data Science @ TAU/Israel

09:50 - 10:00
All Participants
Discussion and First Thoughts

10:00 - 10:20  COFFEE BREAK

10:20 - 11:00
Amir Globerson, Tel Aviv
Deep Learning: Optimization, Generalization and Architectures

11:00 - 11:40
Moritz Grosse-Wentrup, Munich
Causal Representation Learning

11:40 - 12:30
Saharon Rosset, Tel Aviv
Quality Preserving Databases: Statistically Sound and Efficient Use of Public Databases for an Infinite Sequence of Tests

12:30 - 14:00  LUNCH BREAK

14:00 - 14:40
Volker Schmid, Munich
Efficient Bayesian approaches in Data Science

14:40 - 15:20
Daniel Nevo, Tel Aviv
On classical and modern variable selection in regression

15:20 - 15:40  COFFEE BREAK

15:40 - 16:20
David M. Steinberg, Tel Aviv
Experimental Design in the Online Economy

16:20 - 17:00
Goeran Kauermann, Munich
The Pipeline Revisited - Combining Machine Learning and Statistics

17:00 - 17:30
All Participants
Open Discussion

19:30 DINNER