Humboldt-Universität zu Berlin - Berlin School of Library and Information Science

Information Processing and Analytics

The focus of the Information Processing and Analytics research group are methods and systems for processing and analysing information. Central research areas are computer-supported information processing and the analysis of big data as well as their influence on information and knowledge processes. This includes the application and improvement of approaches for data mining, machine learning, information extraction, and natural language processing.

One of our research goals is to improve access to the ever-increasing amount of research outputs for researchers and the general public and to make the World Wide Web accessible as a research object. Typical application areas are recommender systems, collaborative tagging systems (such as our own system BibSonomy), research data management, web archiving, digital humanities and the social web.

Professor

Robert Jäschke, Prof. Dr.

Since 2017 Robert Jäschke is head of the Information Processing and
Analytics group at the Berlin School for Library and Information
Science. His research area is Web Science, an emerging branch of data
science that is dedicated to the study of the World Wide Web. His
research areas are computer-based information processing, the analysis
of big data and their influence on information and knowledge processes.
Robert Jäschke studied mathematics at Technische Universität Dresden and
earned his PhD in computer science at the University of Kassel.
Afterwards, he worked as a research fellow at the University of Kassel,
as assistant professor at Leibniz Universität Hannover and as senior
lecturer at the University of Sheffield. He is co-founder of the social
bookmarking system BibSonomy and member of of the L3S Research Center Hannover.
His interests include information infrastructures, recommender systems,
open science and digital humanities. He is co-operator of the blog
weltliteratur.net, a “black market for digital humanities”. profile page

Robert Jäschke

PhD Students

Frederik Arnold, M.Sc.

Frederik Arnold has been an academic assistant at the Chair of Information Processing and Analytics at the Institute for Library and Information Science since 2020 and holds a Master's degree in Computational Linguistics from Saarland University. In the DFG-funded project What matters? Key passages in literary works he is developing methods for identification and characterisation of key passages. profile page

Simon Hachmeier, M.Sc.

Simon Hachmeier is research assistant at L3S Research Center and PhD student at the Information Processing and Analytics group. In the L3S research project Uncovr he is working on the identification, linking and characterisation of music videos on large web-based video platforms. He has a master's degree in information systems from the University of Innsbruck.

Simon Hachmeier

Michel Schwab, M.Sc.

Michel Schwab is research assistant at the chair of Information Processing and Analytics at the Berlin School of Library and Information Science. He earned his master’s degree in mathematics at Technische Universität Berlin. profile page

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Hadi Sadaatdoorabi, M.Sc.

Hadi Sadaatdoorabi is research assistant at L3S Research Center and PhD student at the Information Processing and Analytics group. In the L3S research project Uncovr he is working on the identification, linking and characterisation of music videos on large web-based video platforms.

Student Assistants

Miriam Brauer

Miriam Brauer is a student assistant and has been studying at Humboldt University since 2015. Since 2017 she has been studying library and information science and American studies. profile page

Laura Perello

Laura Perello is a student assistant and has been studying Library and Information Science in the core subject at Humboldt University since 2020. In 2019 she obtained a Bachelor of Arts in East Asian Studies/Korea Studies. profile page

Alumni

Christoph Hube

Christoph Hube worked in the DESIR project from 2017 to 2019 and did research on Methods for Detecting and Mitigating Linguistic Bias in Text Corpora.