Service-centric Networking

Tobias Eichinger

Office TEL 19
Building TEL

Scientific Career

Tobias Eichinger received his Bacherlor’s degree in mathematics at KIT (Karlsruhe Institute of Technology) in 2014. Consecutively commencing his Master’s studies, he applied his thoroughly acquired mathematical knowledge in the field of business administration and economics at KAIST (South Korea). In 2016, he graduated his Master’s degree in mathematics at KIT.

In early 2017, he joined the Service-centric Networking group at Telekom Innovation Laboratories/Technische Universität Berlin as a research fellow in the field of Data Science led by Prof. Axel Küpper. His research focuses on decentralized recommender systems in the broader context of distributed systems. In particular, his focus is the applicatibility of techniques from the area of Natural Language Processing also in view of privacy preservation.

Research Interests

  • Recommender Systems
  • Distributed Systems
  • Natural Language Processing
  • Machine Learning

Publication

2023

T. Eichinger and A. Küpper, "Distributed Data Minimization for Decentralized Collaborative Filtering Systems" in Proceedings of the 24th International Conference On Distributed Computing And Networking (ICDCN), ACM, 2023. pp. 140-149.

2022

T. Kao, L. Dahm and T. Eichinger, "Are User-Generated Item Reviews Actually Beneficial for Recommendation?" in Workshop Proceedings of the 4th Edition of Knowledge-aware and Conversational Recommender Systems (KaRS 2022), CEUR-WS, 2022. pp. 1-6.
T. Eichinger and M. Ebermann, "Can We Effectively Use Smart Contracts to Stipulate Time Constraints?" in IEEE International Conference on Decentralized Applications and Infrastructures (DAPPS 2022), IEEE, 2022. pp. 11-18.

2021

T. Eichinger, "Reviews Are Gold!? On the Link between Item Reviews and Item Preferences" in 2021 Joint Workshop on Knowledge-aware and Conversational Recommender Systems & Recommendation in Complex Environments (KaRS & ComplexRec), CEUR-WS, 2021.

2019

T. Eichinger, F. Beierle, S. U. Khan and R. Middelanis, "Affinity: A System for Latent User Similarity Comparison on Texting Data" in 2019 53rd Conference on Communications (ICC), IEEE, 2019.
F. Beierle and T. Eichinger, "Collaborating with Users in Proximity for Decentralized Mobile Recommender Systems" in 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), IEEE, 2019. pp. 1192-1197.
T. Eichinger, F. Beierle, R. Papke, L. Rebscher, H. Chinh Tran and M. Trzeciak, "On Gossip-based Information Dissemination in Pervasive Recommender Systems" in 2019 13th Conference on Recommender Systems (RecSys), ACM, 2019.

2017

T. Eichinger and S. Winter, "Regularly Varying Functions, Generalized Contents, and the Spectrum of Fractal Strings" in 2017 Horizons of Fractal Geometry and Complex Dimensions, AMS, 2017.
T. Eichinger, "The Corpus Replication Task" in 2017 4th Conference on Computational Science and Computational Intelligence (CSCI), IEEE Computer Society, 2017.