Sven Weinzierl

About Sven Weinzierl

Sven Weinzierl, With an exceptional h-index of 13 and a recent h-index of 13 (since 2020), a distinguished researcher at Friedrich-Alexander-Universität Erlangen-Nürnberg, specializes in the field of Business Process Management, Deep Learning, Machine Learning, Business Analytics.

His recent articles reflect a diverse array of research interests and contributions to the field:

TOWARDS AUTOMATED BUSINESS PROCESS REDESIGN IN RUNTIME USING GENERATIVE MACHINE LEARNING

TRANSFER LEARNING FOR PREDICTIVE PROCESS MONITORING

Predicting Customer Satisfaction in Service Processes Using Multilingual Large Language Models

Context-aware Explanations of Accurate Predictions in Service Processes

Interpretable generalized additive neural networks

Predictive Recommining: Learning Relations Between Event Log Characteristics and Machine Learning Approaches for Supporting Predictive Process Monitoring

Guiding text-to-text privatization by syntax

Driving context into text-to-text privatization

Sven Weinzierl Information

University

Position

Researcher

Citations(all)

393

Citations(since 2020)

392

Cited By

45

hIndex(all)

13

hIndex(since 2020)

13

i10Index(all)

14

i10Index(since 2020)

14

Email

University Profile Page

Google Scholar

Sven Weinzierl Skills & Research Interests

Business Process Management

Deep Learning

Machine Learning

Business Analytics

Top articles of Sven Weinzierl

TOWARDS AUTOMATED BUSINESS PROCESS REDESIGN IN RUNTIME USING GENERATIVE MACHINE LEARNING

2024

TRANSFER LEARNING FOR PREDICTIVE PROCESS MONITORING

2024

Predicting Customer Satisfaction in Service Processes Using Multilingual Large Language Models

2024/1/3

Context-aware Explanations of Accurate Predictions in Service Processes

2024/1/3

Interpretable generalized additive neural networks

European Journal of Operational Research

2023/6/22

Predictive Recommining: Learning Relations Between Event Log Characteristics and Machine Learning Approaches for Supporting Predictive Process Monitoring

2023/6/8

Guiding text-to-text privatization by syntax

arXiv preprint arXiv:2306.01471

2023/6/2

Sven Weinzierl
Sven Weinzierl

H-Index: 5

Driving context into text-to-text privatization

arXiv preprint arXiv:2306.01457

2023/6/2

Sven Weinzierl
Sven Weinzierl

H-Index: 5

Predictive end-to-end enterprise process network monitoring

Business & Information Systems Engineering

2023/2

Best of Both Worlds: Combining Predictive Power with Interpretable and Explainable Results for Patient Pathway Prediction

2023

Text-aware predictive process monitoring with contextualized word embeddings

2022/9/11

GAM (e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints

2022/4/19

Detecting temporal workarounds in business processes–A deep-learning-based method for analysing event log data

Journal of Business Analytics

2022/1/2

A Method for Predicting Workarounds in Business Processes

Pacific Asia Conference on Information Systems (PACIS)

2022

The Recomminder: A Decision Support Tool for Predictive Business Process Monitoring

2021/9/6

A technique for determining relevance scores of process activities using graph-based neural networks

Decision Support Systems

2021/5/1

Exploring Gated Graph Sequence Neural Networks for Predicting Next Process Activities

5th International Workshop on Artificial Intelligence for Business Process Management (AI4BPM2021)

2021

Sven Weinzierl
Sven Weinzierl

H-Index: 5

Bringing Light Into the Darkness-A Systematic Literature Review on Explainable Predictive Business Process Monitoring Techniques

2021

Predictive Business Process Deviation Monitoring

2021

Time Matters: Time-Aware LSTMs for Predictive Business Process Monitoring

2021

See List of Professors in Sven Weinzierl University(Friedrich-Alexander-Universität Erlangen-Nürnberg)

Co-Authors

academic-engine