Welcome! My name is Benjamin Erb and I am a computer scientist primarily working in the field of distributed systems and interdisciplinary projects, especially with researchers from psychology.
I am currently employed as a researcher at the Institute of Distributed Systems, Ulm University. I hold a Diploma degree in Computer Science in Media and a Bachelor degree in Psychology from Ulm University. In 2019, I received my doctoral degree for my work on a novel live graph computing approach that combines concepts of traditional graph computing with features from event-driven architectures.
Main Research Interests
- I have a strong interest in the design and implementation of data-intensive architectures, in particular distributed platforms for data processing. This includes processing models and programming abstractions for special data (e.g., evolving graph structures) as well as underlying platform architectures that aim for proper performance and scalability. I take special interest in data-intensive systems that consume stream-based input data and provide temporal capabilities such as retrospection. Here, I am using techniques such as event sourcing to enable history-aware processing.
- A second research interest addresses the interaction between data privacy and psychology. On the one hand, this includes the tension field between confidentiality, data protection, and empirical research in psychology. Here, I am exploring potential threats to privacy from public research data sets due to the open science movement, but also technical solutions and mitigations based on privacy-enhancing technologies. On the other hand, I am also interested in psychological aspects of privacy to better understand user behavior when it comes to privacy decisions.
|Apr 28, 2022||I have been awarded internal research start-up funding from Ulm University as part of the ProTrainU program for my work on privacy-enhanced empirical research platforms.|
|Jan 17, 2022||New personal website online.|
Article Frontiers in Big ...Are you willing to self-disclose for science? Effects of Privacy Awareness (PA) and Trust in Privacy (TIP) on self-disclosure of personal and health data in online scientific studies -an experimental studyFrontiers in Big Data 2021
Article PsyArXivEmerging Privacy Issues in Times of Open Science2021
Conference Paper SAC ’21Land of the Lost: Privacy Patterns’ Forgotten Properties: Enhancing Selection-Support for Privacy PatternsIn Proceedings of the 36th Annual ACM Symposium on Applied Computing 2021
Article Internet Interven...Feasibility of a Software agent providing a brief Intervention for Self-help to Uplift psychological wellbeing (“SISU”). A single-group pretest-posttest trial investigating the potential of SISU to act as therapeutic agentInternet Interventions 2021
Conference Paper SAC ’21PeQES: A Platform for Privacy-Enhanced Quantitative Empirical StudiesIn Proceedings of the 36th Annual ACM Symposium on Applied Computing 2021