Scholar
Christian M. M. Frey
Google Scholar ID: hCNFekkAAAAJ
Machine Learning Lab @UTN
Citations & Impact
Citations
133
H-index
6
i10-index
4
Publications
20
Co-authors
7
list available
Publications
Resume (English only)
Academic Achievements
- - September 3, 2025: Runner-up Best Student Paper Award for the paper 'BEST: Bilaterally Expanding Subtrace Tree for Event Sequence Prediction' at International Conference on Business Process Management 2025
- - August 18, 2025: Paper 'SHAining on Process Mining: Explaining Event Log Characteristics Impact on Algorithms' accepted at ICPM 2025
- - May 8, 2025: Paper 'BEST: Bilaterally Expanding Subtrace Tree for Event Sequence Prediction' accepted at BPM 2025
- - February 14, 2025: New arXiv paper 'Is Deep Learning finally better than Decision Trees on Tabular Data?'
- - September 18, 2024: Paper 'iGEDI: interactive Generating Event Data with Intentional Features (Extended Abstract)' accepted at ICPM Demos Track 2024
Research Experience
- - From September 1, 2024 to present: Academic Advisor in the Machine Learning Lab at the University of Technology Nuremberg
- - Winter term 2023/2024: Lecturer at Otto-Friedrich University of Bamberg, teaching 'Data Science in Supply Chain Management'
- - Prior to 2023: Senior Scientist at Fraunhofer IIS, leading research projects and supervising a PhD student in collaboration with LMU
Education
- - Degree: Doctorate (Dr.rer.nat.)
- - University: Ludwig-Maximilian University
- - Advisor: Not explicitly mentioned
- - Time: June 2023
- - Major: Informatics
- - Dissertation Title: 'Learning from Complex Networks'
Background
- - Research Interests: Foundation Models, Large Language Models, Learning on Tabular Data, Neural Combinatorial Optimization, Data-efficient Learning
- - Professional Field: Machine Learning, Data Analysis, Supply Chain Management
- - Brief Introduction: Currently working as an academic advisor in the Machine Learning Lab at the University of Technology Nuremberg, focusing on foundation models, tabular data, reinforcement learning, and optimization techniques.
Miscellany
- - Personal Interests: Peer-reviewed for conferences including CIKM'15, SIGSPATIAL'15, SIGSPATIAL'16, KDD'16, SSDBM'16, ICDE'17, DASFAA'17, KDD'17, VLDB'17, ICDE'18, DASFAA'18, CIKM'18, VLDB'19, SDM'20, DAMI'20, ICDM'21, ECMLPKDD'21, SIGMOD'23, EJOR'23, ECML PKDD'24 [PC Member], EJOR'24, ECML PKDD'25 [PC Member], LOG'25
- - Supervised Theses:
- - MT - 'Attention-driven Learning of Temporal Abstractions in deep Reinforcement Learning'
- - MT - 'Relation Disambiguation in Knowledge Graphs'
- - MT - 'Application of Energy Consumption Forecasts using Deep Learning'
- - MT - 'Analysis Framework for spatio-temporal soccer data'
