My academic life

I'm currently working as a Staff Machine Learning Engineer at Celonis. Before, I was a postdoctoral researcher at the Telecooperation Lab in the department of computer science at Technische Universität Darmstadt, Germany. I'm interested in process mining, an area that investigates recorded event logs by information systems to obtain valuable knowledge about how (business) processes are executed in reality. Specific topics include: process discovery, trace clustering, machine learning, and computer-assisted guidance for visual exploration.

Links to visit: My ORCID website  |  My Google scholar profile

 

Publications

2024

Inferring Missing Event Log Data from IoT Sensor Data – A Case Study in Manufacturing.
Alexander Seeliger, Markus Schreiber, Florian Giger, Joachim Metternich and Max Mühlhäuser.
International Conference on Business Process Management (BPM 2024), Krakow, Poland

2023

Discovering Process-Based Drivers for Case-Level Outcome Explanation.
Peng Li, Hantian Zhang, Xu Chu, Alexander Seeliger and Cong Yu
International Workshop on Leveraging Machine Learning (ML4PM 2023) at International Conference on Process Mining (ICPM 2023), Rome, Italy
PDF

2022

Inferring A Multi-Perspective Likelihood Graph from Black-Box Next Event Predictors.
Yannik Gerlach, Alexander Seeliger, Timo Nolle, Max Mühlhäuser
International Conference on Advanced Information Systems Engineering (CAiSE 2022), Leuven, Belgium
DOI: 10.1007/978-3-031-07472-1_2

2021

A Method for Debugging Process Discovery Pipelines to Analyze the Consistency of Model Properties.
Christopher Klinkmüller, Alexander Seeliger, Richard Müller, Luise Pufahl, Ingo Weber
International Conference on Business Process Management (BPM 2021), Rome, Italy
DOI: 10.1007/978-3-030-85469-0_7

Learning of Process Representations Using Recurrent Neural Networks.
Alexander Seeliger, Stefan Luettgen, Timo Nolle, Max Mühlhäuser
International Conference on Advanced Information Systems Engineering (CAiSE 2021), Melbourne, Australia
DOI: 10.1007/978-3-030-79382-1_7

Case2vec: Advances in Representation Learning for Business Processes.
Stefan Luettgen, Alexander Seeliger, Timo Nolle, Max Mühlhäuser
Process Mining Workshops, S. 162-174, 1st International Workshop on Leveraging Machine Learning in Process Mining (ML4PM)
DOI: 10.1007/978-3-030-72693-5_13

2020

Intelligent Computer-assisted Process Mining
Alexander Seeliger
Dissertation. Technische Universität Darmstadt
PDF | DOI: 10.25534/tuprints-00011915


DeepAlign: Alignment-Based Process Anomaly Correction Using Recurrent Neural Networks

Timo Nolle, Alexander Seeliger, Nils Thoma, Max Mühlhäuser
International Conference on Advanced Information Systems Engineering (CAiSE2020)
DOI: 10.1007/978-3-030-49435-3_20

2019

BINet: Multi-perspective business process anomaly classification
Timo Nolle, Stefan Luettgen, Alexander Seeliger, Max Mühlhäuser
Information Systems
DOI: 10.1016/j.is.2019.101458


UPA'19: 4th International Workshop on Ubiquitous Personal Assistance
Alejandro Sanchez Guinea, Alexander Seeliger, Veljko Pejović, Usman Naeem, Philipp Marcel Scholl, Cristina Mihale-Wilson, Elena Di Lascio, Muhammad Awais Azam, Pei-Yi (Patricia) Kuo, Max Mühlhäuser, Christian Meurisch
ACM International Joint Conference on Pervasive and Ubiquitous Computing and International Symposium on Wearable Computers
DOI: 10.1145/3341162.3347755


ProcessExplorer: Intelligent Process Mining Guidance
Alexander Seeliger, Alejandro Sánchez Guinea, Timo Nolle, Max Mühlhäuser
International Conference on Business Process Management, Wien, Austria
DOI: 10.1007/978-3-030-26619-6_15


ProcessExplorer: Interactive Visual Exploration of Event Logs with Analysis Guidance
Alexander Seeliger, Maximilian Ratzke, Timo Nolle, Max Mühlhäuser
International Conference on Process Mining - Demo Track, Aachen, Germany
PDF

2018

Finding Structure in the Unstructured: Hybrid Feature Set Clustering for Process Discovery
Alexander Seeliger, Timo Nolle, Max Mühlhäuser
Business Process Management, Sydney, Australia
DOI: 10.1007/978-3-319-98648-7_17


ProcessExplorer: An Interactive Visual Recommendation System for Process Mining
Alexander Seeliger, Timo Nolle, Max Mühlhäuser
KDD 2018 Workshop on Interactive Data Exploration and Analytics, London, UK
PDF


BINet: Multivariate Business Process Anomaly Detection Using Deep Learning
Timo Nolle, Alexander Seeliger, Max Mühlhäuser
Business Process Management, Sydney, Australia
DOI: 10.1007/978-3-319-98648-7_16


Analyzing business process anomalies using autoencoders
Timo Nolle, Stefan Luettgen, Alexander Seeliger, Max Mühlhäuser
Machine Learning, ISSN 0885-6125
DOI: 10.1007/s10994-018-5702-8

2017

Can We Find Better Process Models? Process Model Improvement using Motif-based Graph Adaptation
Alexander Seeliger, Michael Stein, Max Mühlhäuser
Business Process Management Workshops, Barcelona, Spain
DOI: 10.1007/978-3-319-74030-0_17


Detecting Concept Drift in Processes using Graph Metrics on Process Graphs
Alexander Seeliger, Timo Nolle, Max Mühlhäuser
International Conference on Subject-oriented Business Process Management (S-BPM-ONE), Darmstadt, Germany
DOI: 10.1145/3040565.3040566

2016

Process Compliance Checking using Taint Flow Analysis
Alexander Seeliger, Timo Nolle, Benedikt Schmidt, Max Mühlhäuser
International Conference on Information Systems (ICIS), AIS, Dublin, Ireland
PDF | AIS eLibrary


Unsupervised Anomaly Detection in Noisy Business Process Event Logs Using Denoising Autoencoders
Timo Nolle, Alexander Seeliger, Max Mühlhäuser
International Conference, DS 2016, Bari, Italy
DOI: 10.1007/978-3-319-46307-0_28


What Belongs Together Comes Together. Activity-centric Document Clustering for Information Work
Alexander Seeliger, Benedikt Schmidt, Immanuel Schweizer, Max Mühlhäuser
International Conference on Intelligent User Interfaces, ACM, Sonoma, CA, USA
DOI: 10.1145/2856767.2856777

2015

Upgrading Wireless Home Routers for Enabling Large-scale Deployment of Cloudlets
Christian Meurisch, Alexander Seeliger, Benedikt Schmidt, Immanuel Schweizer, Fabian Kaup, Max Mühlhäuser
International Conference, MobiCASE 2015, Berlin, Springer, Berlin, Germany
ISBN 978-3-319-29002-7

2012

A Semantic Browser for Linked Open Data
Alexander Seeliger, Heiko Paulheim
Semantic Web Challenge