Nijat Mehdiyev

38 papers Journal 19Unranked 19

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Assessing the Business Process Modeling Competences of Large Language Models. CoRR Chantale Lauer, Peter Pfeiffer, Alexander Rombach, Nijat Mehdiyev
2026	J	`jnl`	Human-Centered Evaluation of an LLM-Based Process Modeling Copilot: A Mixed-Methods Study with Domain Experts. CoRR Chantale Lauer, Peter Pfeiffer, Nijat Mehdiyev
2025	J	`jnl`	Augmenting post-hoc explanations for predictive process monitoring with uncertainty quantification via conformalized Monte Carlo dropout. Data Knowl. Eng. Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2025	—	`conf`	Conversational Business Process Modeling using LLMs: Initial Results and Challenges. EMISA Chantale Lauer, Peter Pfeiffer, Alexander Rombach, Nijat Mehdiyev
2025	J	`jnl`	From Theory to Practice: Real-World Use Cases on Trustworthy LLM-Driven Process Modeling, Prediction and Automation. CoRR Peter Pfeiffer, Alexander Rombach, Maxim Majlatow, Nijat Mehdiyev
2025	J	`jnl`	Integrating permutation feature importance with conformal prediction for robust Explainable Artificial Intelligence in predictive process monitoring. Eng. Appl. Artif. Intell. Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2025	J	`jnl`	Interpretable and explainable machine learning methods for predictive process monitoring: a systematic literature review. Artif. Intell. Rev. Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2025	J	`jnl`	Quantifying and explaining machine learning uncertainty in predictive process monitoring: an operations research perspective. Ann. Oper. Res. Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2024	—	`conf`	Communicating Uncertainty in Machine Learning Explanations: A Visualization Analytics Approach for Predictive Process Monitoring. xAI (3) Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2024	J	`jnl`	Counterfactual Explanations in the Big Picture: An Approach for Process Prediction-Driven Job-Shop Scheduling Optimization. Cogn. Comput. Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2024	J	`jnl`	Deep learning-based clustering of processes and their visual exploration: An industry 4.0 use case for small, medium-sized enterprises. Expert Syst. J. Knowl. Eng. Nijat Mehdiyev, Lea Mayer, Johannes Lahann, Peter Fettke
2024	—	`conf`	Generative AI For Code Comment Classification: A Comparative Analysis. MCIS Busra Sebin, Nazim Taskin, Nijat Mehdiyev
2024	J	`jnl`	Uncertainty-aware multi-criteria decision analysis for evaluation of explainable artificial intelligence methods: A use case from the healthcare domain. Inf. Sci. Kamala Aliyeva, Nijat Mehdiyev
2023	J	`jnl`	Communicating Uncertainty in Machine Learning Explanations: A Visualization Analytics Approach for Predictive Process Monitoring. CoRR Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2023	—	`conf`	Explainable Artificial Intelligence Meets Uncertainty Quantification for Predictive Process Monitoring. PMAI@IJCAI Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2023	J	`jnl`	Interpretable and Explainable Machine Learning Methods for Predictive Process Monitoring: A Systematic Literature Review. CoRR Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2023	J	`jnl`	Quantifying and Explaining Machine Learning Uncertainty in Predictive Process Monitoring: An Operations Research Perspective. CoRR Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2021	—	`conf`	Explainable Artificial Intelligence (XAI) Supporting Public Administration Processes - On the Potential of XAI in Tax Audit Processes. Wirtschaftsinformatik Nijat Mehdiyev, Constantin Houy, Oliver Gutermuth, Lea Mayer, Peter Fettke
2021	—	`conf`	Local Post-Hoc Explanations for predictive Process Monitoring in manufacturing. ECIS Nijat Mehdiyev, Peter Fettke
2020	J	`jnl`	A Novel Business Process Prediction Model Using a Deep Learning Method. Bus. Inf. Syst. Eng. Nijat Mehdiyev, Joerg Evermann, Peter Fettke
2020	J	`jnl`	Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring. CoRR Nijat Mehdiyev, Peter Fettke
2020	—	`conf`	Explainable Process Predictions (xPP): A Holistic Framework and Applications (Extended Abstract). ICPM Doctoral Consortium / Tools Nijat Mehdiyev
2020	J	`jnl`	Local Post-Hoc Explanations for Predictive Process Monitoring in Manufacturing. CoRR Nijat Mehdiyev, Peter Fettke
2020	—	`conf`	Prescriptive Process Analytics with Deep Learning and Explainable Artificial Intelligence. ECIS Nijat Mehdiyev, Peter Fettke
2019	—	`conf`	Substitution of hazardous chemical substances using Deep Learning and t-SNE. Wirtschaftsinformatik Patrick Lübbecke, Nijat Mehdiyev, Peter Fettke
2019	J	`jnl`	Towards Explainable Process Predictions for Industry 4.0 in the DFKI-Smart-Lego-Factory. Künstliche Intell. Jana-Rebecca Rehse, Nijat Mehdiyev, Peter Fettke
2017	—	`conf`	A Multi-stage Deep Learning Approach for Business Process Event Prediction. CBI (1) Nijat Mehdiyev, Joerg Evermann, Peter Fettke
2017	—	`conf`	iPRODICT - Intelligent Process Prediction based on Big Data Analytics. BPM (Industry Track) Nijat Mehdiyev, Andreas Emrich, Björn P. Stahmer, Peter Fettke, Peter Loos
2016	—	`conf`	Determination of Event Patterns for Complex Event Processing Using Fuzzy Unordered Rule Induction Algorithm with Multi-objective Evolutionary Feature Subset Selection. HICSS Nijat Mehdiyev, Julian Krumeich, Dirk Werth, Peter Loos
2015	—	`conf`	Determination of Rule Patterns in Complex Event Processing Using Machine Learning Techniques. Complex Adaptive Systems Nijat Mehdiyev, Julian Krumeich, David Enke, Dirk Werth, Peter Loos
2015	—	`conf`	Sensor event mining with hybrid ensemble learning and evolutionary feature subset selection model. IEEE BigData Nijat Mehdiyev, Julian Krumeich, Dirk Werth, Peter Loos
2015	—	`conf`	Towards an Extended Metamodel of Event-Driven Process Chains to Model Complex Event Patterns. ER Workshops Julian Krumeich, Nijat Mehdiyev, Dirk Werth, Peter Loos
2014	—	`conf`	A Hybrid Neuro-fuzzy Model to Forecast Inflation. Complex Adaptive Systems David Enke, Nijat Mehdiyev
2014	J	`jnl`	Interest rate prediction: a neuro-hybrid approach with data preprocessing. Int. J. Gen. Syst. Nijat Mehdiyev, David Enke
2013	J	`jnl`	Stock Market Prediction Using a Combination of Stepwise Regression Analysis, Differential Evolution-based Fuzzy Clustering, and a Fuzzy Inference Neural Network. Intell. Autom. Soft Comput. David Enke, Nijat Mehdiyev
2013	—	`conf`	Type-2 Fuzzy Clustering and a Type-2 Fuzzy Inference Neural Network for the Prediction of Short-term Interest Rates. Complex Adaptive Systems David Enke, Nijat Mehdiyev
2012	—	`conf`	A New Hybrid Approach For Forecasting Interest Rates. Complex Adaptive Systems David Enke, Nijat Mehdiyev
2011	—	`conf`	Stock Market Prediction with Multiple Regression, Fuzzy Type-2 Clustering and Neural Networks. Complex Adaptive Systems David Enke, Manfred Grauer, Nijat Mehdiyev