معرفی
Pascal Kerschke is a Professor at the Chair of Big Data Analytics in Transportation at Technische Universität Dresden (TU Dresden). His research focuses on exploratory landscape analysis, multi-objective optimization, and automated algorithm selection for complex computational problems.
- Research Areas: Exploratory Landscape Analysis, Multi-Objective Optimization, Traveling Salesperson Problem (TSP), Machine Learning, Continuous Optimization
- Affiliation: Chair of Big Data Analytics in Transportation, TU Dresden
Kerschke has pioneered methodologies for characterizing optimization problem landscapes using machine learning and statistical features, bridging gaps between algorithm design and practical applications in transportation analytics. His work includes developing frameworks like FLACCO for fitness landscape analysis and advancing visualizations for multi-objective optimization.
Recent publications highlight his contributions to deep learning integration for landscape analysis (e.g., Deep-ELA), multiobjectivization techniques, and benchmarking challenges. He has also explored adversarial robustness in neural networks and parameter tuning methodologies.
Scientific Awards:
- PPSN 2016 Best Paper Award
Kerschke's collaborations with optimization heuristic developers and his role in creating benchmarking libraries (e.g., ASlib, OpenML) underscore his interdisciplinary impact in computational optimization and data-driven decision-making.
