A5070529144- Business Process Modeling and Analysis
- Service-Oriented Architecture and Web Services
- Semantic Web and Ontologies
- Advanced Database Systems and Queries
- Data Quality and Management
- Privacy-Preserving Technologies in Data
- Data Management and Algorithms
- Data Stream Mining Techniques
- Petri Nets in System Modeling
- Software System Performance and Reliability
- Advanced Software Engineering Methodologies
- Scientific Computing and Data Management
- Flexible and Reconfigurable Manufacturing Systems
- Time Series Analysis and Forecasting
- Advanced Graph Neural Networks
- Complex Network Analysis Techniques
- Blockchain Technology Applications and Security
- Big Data and Business Intelligence
- Mobile Crowdsensing and Crowdsourcing
- Access Control and Trust
- Distributed and Parallel Computing Systems
- Topic Modeling
- Software Engineering Research
- Distributed systems and fault tolerance
- Traffic Prediction and Management Techniques
Humboldt-Universität zu Berlin
2016-2025
Charité - Universitätsmedizin Berlin
2016-2024
University of Mannheim
2021
Imperial College London
2014-2016
Technion – Israel Institute of Technology
2012-2014
Hasso Plattner Institute
2007-2012
University of Potsdam
2007-2012
Eindhoven University of Technology
2012
Vienna University of Economics and Business
2012
Blockchain technology offers a sizable promise to rethink the way interorganizational business processes are managed because of its potential realize execution without central party serving as single point trust (and failure). To stimulate research on this and limits thereof, in article, we outline challenges opportunities blockchain for process management (BPM). We first reflect how blockchains could be used context established BPM lifecycle second they might become relevant beyond....
Abstract The continued success of Large Language Models (LLMs) and other generative artificial intelligence approaches highlights the advantages that large information corpora can have over rigidly defined symbolic models, but also serves as a proof-point challenges purely statistics-based in terms safety trustworthiness. As framework for contextualizing potential, well limitations LLMs foundation model-based technologies, we propose concept Process Model (LPM) combines correlation power...
Engineering of process-driven business applications can be supported by process modeling efforts in order to bridge the gap between requirements and system specifications. However, diverging purposes initiatives have led significant problems aligning related models at different abstract levels perspectives. Checking consistency such corresponding is a major challenge for theory practice. In this paper, we take inappropriateness existing strict notions behavioral equivalence as starting...
Modern servers have become heterogeneous, often combining multi-core CPUs with many-core GPGPUs. Such heterogeneous architectures the potential to improve performance of data-intensive stream processing applications, but they are not supported by current relational engines. For an engine exploit a architecture, it must execute streaming SQL queries sufficient data-parallelism fully utilise all available processors, and decide how use each in most effective way. It do this while respecting...
Abstract Process mining provides a rich set of techniques to discover valuable knowledge business processes based on data that was recorded in different types information systems. It enables analysis end‐to‐end facilitate process re‐engineering and improvement. rely the availability form event logs. In order enable diverse environments, need be located transformed The journey from raw logs suitable for can addressed by variety methods techniques, which are focus this article. particular,...
In recent years, crowdsourcing has become essential in a wide range of Web applications. One the biggest challenges is quality crowd answers as workers have wide-ranging levels expertise and worker community may contain faulty workers. Although various techniques for control been proposed, post-processing phase which are validated still required. Validation typically conducted by experts, whose availability limited who incur high costs. Therefore, we develop probabilistic model that helps to...
Network alignment is the problem of pairing nodes between two graphs such that paired are structurally and semantically similar. A well-known application network to identify which accounts in different social networks belong same person. Existing techniques, however, lack scalability, cannot incorporate multi-dimensional information without training data, limited consistency constraints enforced by an alignment. In this paper, we propose a fully unsupervised framework based on multi-order...
Abstract Predictive process monitoring is a family of techniques to analyze events produced during the execution business in order predict future state or final outcome running instances. Existing this field are able predict, at each step instance, likelihood that it will lead an undesired outcome. These techniques, however, focus on generating predictions and do not prescribe when how workers should intervene decrease cost outcomes. This paper proposes framework for prescriptive monitoring,...
Advances in deep neural network (DNN) architectures have enabled new prediction techniques for stock market data. Unlike other multivariate time-series data, markets show two unique characteristics: (i) multi-order dynamics, as prices are affected by strong non-pairwise correlations (e.g., within the same industry); and (ii) internal each individual shows some particular behaviour. Recent DNN-based methods capture dynamics using hypergraphs, but rely on Fourier basis convolution, which is...