Research Associate at Fraunhofer FIT, Germany
Mr. Humam Kourani is a dedicated and highly skilled researcher with a strong background in Data Science and Computer Science. He holds both a Master’s and Bachelor’s degree from RWTH Aachen University, specializing in process mining, artificial intelligence, and data-driven decision-making. He has gained valuable experience working in research institutions and industry settings, most notably at the Fraunhofer Institute for Applied Information Technology and Fondazione Bruno Kessler in Italy. His research focuses on improving data science methodologies, particularly in process mining and workflow language models. With a solid academic foundation, practical experience, and significant contributions to his field, Humam has proven himself to be a promising and impactful researcher.
Professional Profile
Education
Humam Kourani completed his Master of Science in Data Science from RWTH Aachen University in 2022, with a focus on Computer Science. His master’s thesis explored the improvement of the Hybrid Miner by utilizing causal graph metrics, an area critical for process mining. Prior to that, he earned his Bachelor of Science degree in Computer Science from the same institution in 2019. His Bachelor’s thesis involved the development of a scalable interactive event data visualization tool in Python, further showcasing his technical skills. Humam’s academic journey reflects his dedication to mastering complex data science concepts and his drive to contribute to the field’s advancement through academic research and innovation.
Professional Experience
Mr. Kourani’s professional experience spans key positions in research and data science. Since May 2022, he has been working as a Research Associate at the Fraunhofer Institute for Applied Information Technology, specializing in Data Science and Artificial Intelligence. In this role, he contributes to research on process mining, artificial intelligence, and data-driven decision-making. Earlier, he held student assistant roles at RWTH Aachen University, including positions at the Chair of Process and Data Science and the Chair of Process and Data Science in 2021. Humam also completed an Erasmus+ internship at Fondazione Bruno Kessler in Italy, where he gained hands-on experience in process and data intelligence. His professional experience reflects a consistent focus on leveraging data science and AI for practical problem-solving and research innovation.
Research Interests
Humam Kourani’s research interests lie primarily in data science, artificial intelligence, and process mining. He is particularly focused on enhancing data-driven methods for analyzing and improving business processes, with an emphasis on process modeling and workflow languages. His recent work has explored innovative approaches, such as large language models for process modeling, and improving existing hybrid mining techniques using causal graph metrics. Through his work, Humam aims to bridge the gap between advanced computational techniques and practical business process applications, enabling more efficient decision-making. His research also delves into the intersection of data science and AI, with a strong interest in developing scalable models that address real-world challenges across various industries.
Awards and Honors
Humam Kourani has received several prestigious awards in recognition of his outstanding research contributions. He won the Best Paper Award at the EMMSAD 2024 conference for his paper on “Process Modeling with Large Language Models”. Additionally, he received the Best Paper Award at the BPM 2023 conference for his work on the “POWL: Partially Ordered Workflow Language”. These awards highlight the significance of his research in the fields of process mining and business process management. Humam was also honored with membership in the PADS Excellence Honors Class at RWTH Aachen University in 2022, further underscoring his academic excellence. These honors attest to his innovative contributions to the research community and his growing influence in the fields of data science and AI.
Conclusion
Humam Kourani is undoubtedly a highly talented researcher with a solid foundation in data science and process mining. His research achievements, international experience, and awards demonstrate that he is already making significant contributions to his field. His multidisciplinary skills, coupled with his passion for continuous learning, make him a standout candidate for the Best Researcher Award. While there are opportunities for growth in areas like expanding his publication base and increasing leadership roles in research initiatives, his strengths far outweigh these minor areas of improvement. Humam Kourani is a promising researcher with the potential for continued excellence and impact in the field of data science and artificial intelligence.
Publications Top Noted
- Title: Process Modeling With Large Language Models
Authors: H. Kourani, A. Berti, D. Schuster, W.M.P. van der Aalst
Year: 2024
Citations: 21
- Title: Evaluating Large Language Models in Process Mining: Capabilities, Benchmarks, Evaluation Strategies, and Future Challenges
Authors: A. Berti, H. Kourani, H. Hafke, C.Y. Li, D. Schuster
Year: 2024
Citations: 8
- Title: POWL: Partially Ordered Workflow Language
Authors: H. Kourani, S.J. van Zelst
Year: 2023
Citations: 7
- Title: ProMoAI: Process Modeling with Generative AI
Authors: H. Kourani, A. Berti, D. Schuster, W.M.P. van der Aalst
Year: 2024
Citations: 5
- Title: PM4KNIME: Process Mining Meets the KNIME Analytics Platform
Authors: H. Kourani, S.J. van Zelst, B.D. Lehmann, G. Einsdorf, S. Helfrich, F. Liße
Year: 2022
Citations: 5
- Title: Scalable Discovery of Partially Ordered Workflow Models with Formal Guarantees
Authors: H. Kourani, D. Schuster, W. Van Der Aalst
Year: 2023
Citations: 4
- Title: PM-LLM-Benchmark: Evaluating Large Language Models on Process Mining Tasks
Authors: A. Berti, H. Kourani, W.M.P. van der Aalst
Year: 2024
Citations: 3
- Title: Discovering Hybrid Process Models with Bounds on Time and Complexity: When to be Formal and When Not?
Authors: W.M.P. van der Aalst, R. De Masellis, C. Di Francescomarino, C. Ghidini, H. Kourani
Year: 2023
Citations: 3
- Title: Evaluating Large Language Models in Process Mining: Capabilities, Benchmarks, and Evaluation Strategies
Authors: A. Berti, H. Kourani, H. Häfke, C.Y. Li, D. Schuster
Year: 2024
Citations: 2
- Title: Mining for Long-Term Dependencies in Causal Graphs
Authors: H. Kourani, C. Di Francescomarino, C. Ghidini, W. van der Aalst, S. van Zelst
Year: 2022
Citations: 2
- Title: Bridging Domain Knowledge and Process Discovery Using Large Language Models
Authors: A. Norouzifar, H. Kourani, M. Dees, W. van der Aalst
Year: 2024
Citations: 0 (preprint)
- Title: Leveraging Large Language Models for Enhanced Process Model Comprehension
Authors: H. Kourani, A. Berti, J. Hennrich, W. Kratsch, R. Weidlich, C.Y. Li, A. Arslan, et al.
Year: 2024
Citations: 0 (preprint)
- Title: Discovering Hybrid Process Models with Bounds on Time and Complexity: When to be Formal and When Not?
Authors: W. van der Aalst, R. De Masellis, C. Di Francescomarino, C. Ghidini, H. Kourani
Year: 2023
Citations: 0
