Dr. Saimir Bala

Dr. Saimir Bala

Postdoctoral Researcher

Business Process Technology (BPT) Group & Systems Cluster

Hasso Plattner Institute, University of Potsdam

289 citations · h-index 10 · 34 publications

Saimir Bala is a Postdoctoral Researcher at the Business Process Technology (BPT) Group and the Systems Cluster at the Hasso Plattner Institute (HPI), University of Potsdam, Germany. His research sits at the intersection of Software Engineering, Business Process Management, and Artificial Intelligence, with a particular focus on data-driven techniques for analyzing and improving complex processes.

Prior to joining HPI, he was a Research Associate at Humboldt-Universität zu Berlin (2021–2025). He holds a PhD in Economics and Social Sciences from the Institute for Data, Process and Knowledge Management at the Vienna University of Economics and Business (WU), Austria. His doctoral work investigated ways to bridge Process Mining and Software Engineering, developing analytical methods for understanding the software development process through data. He is also a Fellow of the Weizenbaum Institute for the Networked Society in Berlin.

Saimir holds a BSc and an MSc in Computer Science Engineering from Sapienza University of Rome.

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Core Research Areas

Business Process Management & Process Mining

My work in this area focuses on three specific problems: data quality in object-centric event data (how do we detect and classify issues that corrupt process analysis?); fairness and bias in process mining (which process perspectives are systematically distorted, and how can we intervene?); and AI-augmented process analytics (from exam process mining to lifecycle nudging). I am particularly interested in cases where process data reveals behavioral patterns that are hard to see with classical methods.

Software Engineering

I treat software development as a process that leaves traces — in version control history, issue trackers, and middleware logs. My specific contributions include process mining applied to git repositories (detecting side-tracking, co-evolution patterns, and developer behavior); file and project completion prediction using time-series models that embrace the lifecycle structure of software artifacts; and multi-dimensional process analysis of development projects.

Research code and datasets are shared on GitHub (github.com/s41m1r). Feel free to open issues or reach out if you want to build on this work.

Selected Publications

Full list available on Google Scholar

Conference — BPM, Springer, 2026

AI-Assisted Event Log Generation for Process Mining in Healthcare. Read paper Preprint Source code

S. Bala, Z. Soleimani, M. Weske. BPM, LNCS, Springer, 2026, pp. 259–276.

Conference — Process Technology Forum, BPM, Springer, 2026

Using Process Mining to Generate AI Agents from Software Engineering Process Records. Read paper Preprint Source code

S. Bala, F. Fournier, L. Limonad, A. Metzger. Process Technology Forum, BPM, LNBIP, Springer, 2026, pp. 146–162.

Journal — Process Science, 2026

Data quality in object-centric event data: issues classification and evaluation. Read paper Open Access

M. Kabierski, M. Basmer, A. Patecka, K. Sahling, S. Bala. Process Science, 3(1), 2026, p. 15.

Conference — BPM Forum, Springer, 2025

FairPM: A Taxonomy of Bias and Interventions in Process Mining. Read paper

K. Revoredo, S. Bala, F. M. Santoro. Business Process Management Forum, LNBIP 564, Springer, 2025, pp. 395–412.

Conference — MODELSWARD/MBSE, Springer, 2025

Analyzing Side-Tracking of Developers Using Object-Centric Process Mining. Read paper Preprint Source code

S. Bala, T. Nguyen, J. Mendling. Model-Based Software and Systems Engineering, CCIS 2547, Springer, 2025.

Journal — Business Process Management Journal, 2023

Enhancing decision-making of IT demand management with process mining. Read paper Open Access

C. Novak, L. Pfahlsberger, S. Bala, K. Revoredo, J. Mendling. Business Process Management Journal, 29(8), 2023, pp. 230–259.

View all 31 publications

Teaching

My approach to teaching combines theory with hands-on practice: students work with real datasets, process models, and software repositories to develop both analytical skills and research intuition. I have supervised Bachelor and Master theses, proseminars, and project-based courses across three universities, and I am happy to supervise motivated students at HPI.

Hasso Plattner Institute (HPI), University of Potsdam

Humboldt-Universität zu Berlin

Vienna University of Economics and Business (WU)

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