Cafeteria menus

To overview

Location & approach

By car

The campus of TU Dortmund University is located close to interstate junction Dortmund West, where the Sauerlandlinie A 45 (Frankfurt-Dortmund) crosses the Ruhrschnellweg B 1 / A 40. The best interstate exits to take from A 45 is “Dortmund-Eichlinghofen” (closer to South Campus), and from B 1 / A 40 “Dortmund-Dorstfeld” or “Dortmund-Barop” (both closer to North Campus). Signs to the university are located at all the exits.

To get from North Campus to South Campus by car, there is the connection via Vogelpothsweg/Baroper Straße. We recommend you leave your car on one of the parking lots at North Campus and use the H-Bahn (suspended monorail system), which conveniently connects the two campuses.

By train

TU Dortmund University has its own train station (“Dortmund Universität”). From there, suburban trains (S-Bahn) leave for Dortmund main station (“Dortmund Hauptbahnhof”) and Düsseldorf main station via the “Düsseldorf Airport Train Station” (take S-Bahn number 1, which leaves every 15 or 30 minutes). The university is easily reached from Bochum, Essen, Mülheim an der Ruhr and Duisburg.

You can also take the bus or subway train from Dortmund city to the university: From Dortmund main station, you can take any train bound for the Station “Stadtgarten”, usually lines U41, U45, U 47 and U49. At “Stadtgarten” you switch trains and get on line U42 towards “Hombruch”. Look out for the Station “An der Palmweide”. From the bus stop just across the road, busses bound for TU Dortmund University leave every ten minutes (445, 447 and 462). Another option is to take the subway routes U41, U45, U47 and U49 from Dortmund main station to the stop “Dortmund Kampstraße”. From there, take U43 or U44 to the stop “Dortmund Wittener Straße”. Switch to bus line 447 and get off at “Dortmund Universität S”.

By plane

The AirportExpress is a fast and convenient means of transport from Dortmund Airport (DTM) to Dortmund Central Station, taking you there in little more than 20 minutes. From Dortmund Central Station, you can continue to the university campus by interurban railway (S-Bahn). A larger range of international flight connections is offered at Düsseldorf Airport (DUS), which is about 60 kilometres away and can be directly reached by S-Bahn from the university station.

H-Bahn

The H-Bahn (Suspended Monorail System) is one of the hallmarks of TU Dortmund University. There are two stations on North Campus. One (“Dortmund Universität S”) is directly located at the suburban train stop, which connects the university directly with the city of Dortmund and the rest of the Ruhr Area. Also from this station, there are connections to the “Technologiepark” and (via South Campus) Eichlinghofen. The other station is located at the dining hall at North Campus and offers a direct connection to South Campus every five minutes.

Plan of site & interactive map

The facilities of TU Dortmund University are located on two campuses, the larger North Campus and the smaller South Campus. In addition, some university facilities are located in the adjacent Dortmund Technology Park as well as in the city center and the wider urban area.

> Go to interactive map

ServicePortal UniMail

Contrast Deutsch

Cafeteria menus

To overview

Plan of site & interactive map

> Go to interactive map

ServicePortal UniMail

Alexander Marx

Professorship:

Causality, since 1 June 2024

To the Professorship

Department:

Statistics, Research Center for Trustworthy Data Science and Security

Studies and doctorate:

2021: Doctorate in Computer Science, Max Planck Institute for Informatics and CISPA Helmholtz Center for Information Security, Saarland University
2016: Master of Science in Bioinformatics, Saarland University

Stages:

2024: Postdoc, Department of Biosystems Science and Engineering, ETH Zurich
2021-2023: Postdoc-Fellow, Department of Computer Science and AI Center, ETH Zurich
2019: three-month research visit, University of Amsterdam

Focus areas:

Causality, causal discovery, causal representation learning
Information theory and Bayesian deep learning
Biomedical applications