جست‌وجوی استاد و پژوهشگر

• Algorithms
• Graph Theory
• Dynamic Algorithms
• +۴ مورد دیگر

Kathrin Hanauer is an Assistant Professor at the University of Vienna, where she is affiliated with the Research Group Theory and Applications of Algorithms and the Research Network Data Science. She conducts research in the design, analysis, and experimental evaluation of fast algorithms, with a focus on Algorithm Engineering connecting theoretical foundations with practical implementations. Her research interests include: Algorithm Engineering for practical algorithm implementation Dynamic algorithms for efficiently handling changing data Graph algorithms and network analysis Reachability problems on directed graphs Ranking problems, particularly the NP-hard Feedback Arc Set problem Network analysis, motif search, and subgraph counting Dr. Hanauer's recent publications demonstrate a strong focus on dynamic graph algorithms, with significant contributions to reachability queries, subgraph counting, and datacenter network optimization. Her work spans both theoretical algorithm design and practical implementation, often with C++ software projects. Notable contributions include the O'Reach algorithm for faster reachability queries in large graphs and several dynamic algorithms for subgraph counting and network analysis. Her scientific contributions: O'Reach: A novel approach to reachability queries in large graphs that outperforms previous methods Dynamic algorithms for four-vertex subgraph counting with efficient update operations Work on demand-aware link scheduling for reconfigurable datacenters Interdisciplinary research on normative reasoning with Aristotelian diagrams Dr. Hanauer actively supervises student research, with numerous completed theses focusing on dynamic graph algorithms, geometric algorithms, and reachability problems. Her lab maintains several software projects related to graph algorithms, including a modular algorithms library for dynamic graphs written in C++ and specialized implementations for reachability queries and subgraph counting.

• Bioinformatics
• Mass Spectrometry
• Machine Learning
• +۷ مورد دیگر

Viktoria Dorfer is a Professor at the University of Applied Sciences Hagenberg, affiliated with the Bioinformatics Center of Excellence and Medical Engineering/TIMed Center HEAL. She holds an ORCID iD (0000-0002-5332-5701) and has published 66 research outputs with an h-index of 9 and 676 citations. 2007–2012: Doctoral research on algorithmic approaches 2013–2016: FWF Translational Research on MS Amanda 2020–2022: PI for b-tastic project Research Interests: Spanning bioinformatics, mass spectrometry, and medical engineering, her work focuses on: Algorithm development for peptide identification Evolutionary algorithms in data analysis Mass spectrometry software platforms (AMANDA, Annika) Cross-linked peptide analysis Precision agriculture applications Medical device optimization 2024 Trends: Recent contributions include symbolic regression in livestock farming, enhanced rescoring platforms, and structural analysis of the C. elegans Box C/D complex. Awards: EuPA Bioinformatics Mass Spectrometry Award (2020) Leadership: Organized Austrian Proteomic Research Symposia (2017), served as reviewer/peer-reviewer for journals, and led interdisciplinary collaborations.

• Bioinformatics
• Machine Learning
• Spectral Library Search
• +۵ مورد دیگر

Sebastian Dorl is a researcher at the Fachhochschule Oberösterreich (University of Applied Sciences Upper Austria) , affiliated with the Research Center Hagenberg and the ASiC (Applied Systems and Cybernetics) group. His work spans bioinformatics, machine learning, and data-driven modeling, with a focus on proteomics data analysis, spectral library search algorithms, and industrial process optimization.