Arik Senderovich

Arik’s area of research lies in the intersection between Business Process Management, Data Analytics, and Artificial Intelligence. Currently, he focuses on developing methodologies for automatically learning models of complex environments (such as hospitals and public transportation systems) from data logs. His research has recently received an acknowledgement at the Fifteenth International Conference on Business Process Management in Barcelona (2017) where he was awarded with both the inaugural best dissertation award and the best paper award for that year.

• Data Science
• Information System Design

Journal Publications: 

• Arik Senderovich, Matthias Weidlich, Avigdor Gal: Context-aware temporal network representation of event logs: Model and methods for process performance analysis. Inf. Syst. 84: 240-254 (2019) 

• Arik Senderovich, Chiara Di Francescomarino, Fabrizio Maria Maggi: From knowledge-driven to data-driven inter-case feature encoding in predictive process monitoring. Inf. Syst. 84: 255-264 (2019)

• Avigdor Gal, Avishai Mandelbaum, François Schnitzler, Arik Senderovich, Matthias Weidlich: Traveling time prediction in scheduled transportation with journey segments. Inf. Syst. 64: 266-280 (2017)

Refereed Conferences: 

• Arik Senderovich, Kyle E. C. Booth, J. Christopher Beck: Learning Scheduling Models from Event Data. ICAPS 2019: 401-409

• Arik Senderovich, J. Christopher Beck, Avigdor Gal, Matthias Weidlich: Congestion Graphs for Automated Time Predictions. AAAI 2019: 4854-4861

• Arik Senderovich, Matthias Weidlich, Avigdor Gal: Temporal Network Representation of Event Logs for Improved Performance Modelling in Business Processes. BPM 2017: 3-21 (Best Paper Award). 

PhD Thesis: 

• Arik Senderovich. Queue Mining: Service Analysis and Simulation in Process Mining. (Technion, 2017; Best dissertation award at BPM 2017)

Master’s and doctoral levels and including dissertation/thesis titles

• Yossi Dahari. Fusion-Based Process Discovery. Sc. Thesis (Technion, 2018). Co-supervised with Prof. Avigdor Gal.

• Kunlong Li. Heuristic Search for Solving Petri Net Shortest Path Reachability Problems. Eng. Thesis (University of Toronto, 2019). Co-supervised with Prof. J. Christopher Beck.

• Linesh Sebastian Thanaslas. Learning Scheduling Models: A Declarative Approach Eng. Thesis (University of Toronto, 2019). Co-supervised with Prof. J. Christopher Beck.

• MIE 463: Integrated System Design
• MIE 1699: Business Process Management and Mining (as Special Topics in Operations Research)