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Stefan Neumann

Profile picture of Stefan Neumann

About me

News

  • Two papers accepted at KDD 2023 (more details soon).
  • One paper accepted at ECML PKDD 2023 (more details soon).
  • I was named among the best reviewers of the Web Conference 2023 (formerly WWW). Great honor!
  • New paper at the Web Conference 2023 (formerly WWW). We show that biclustering can be used to detect patterns in datacenter traffic.
  • New paper at STACS 2023. We provide a novel condition showing that existing dynamic programs can be fully dynamic.

Biography

I am a tenure-track assistant professor. I am broadly interested in the foundations of data science and social network analysis. Currently I have two main research goals:

  • In the foundations of data science, I develop practical data science algorithms with provable guarantees.I am particularly interested in theoretically sound methods for finding and exploiting patterns in data.
  • In social network analysis, I study how interventions like Facebook's timeline algorithm influence the polarization and the disagreement in the network.

Previously, I was a postdoctoral researcher at KTH in the group of Aris Gionis and before that I received my Ph.D. from University Vienna under the supervision of Monika Henzinger. During that time, I visited Eli Upfal at Brown University for six months. My Ph.D. thesis won the Heinz Zemanek Award from the Austrian Computer Society and an Award of Excellence from the Austrian federal government. I received my Master's from Saarland University and Max Planck Institute for Informatics, where I worked with Pauli Miettinen and Jilles Vreeken.

You can find more detailed information in my CV.

My research is funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP).

If you have any questions, please feel free to send me a mail. You can contact me in English and in German.


Courses

Advanced Algorithms (DD2440), assistant | Course web

Applied Computer Science (DD1320), assistant | Course web

Applied Programming and Computer Science (DD2325), teacher, course responsible | Course web