Object-Centric Process Mining (OCPM)

Prof.dr.ir. Wil van der Aalst is a full professor at RWTH Aachen University, leading the Process and Data Science (PADS) group. He is also the Chief Scientist at Celonis, part-time affiliated with the Fraunhofer FIT, and a member of the Board of Governors of Tilburg University. Currently, he is also deputy CEO of the Internet of Production (IoP) Cluster of Excellence and co-director of the RWTH Center for Artificial Intelligence. 

His research interests include process mining, Petri nets, business process management, workflow automation, simulation, process modeling, and model-based analysis. He is often called the Godfather of Process Mining and the research he started in the late 1990-ties led to a wave of process mining tools, including commercial tools Many of his papers are highly cited (he is one of the most-cited computer scientists in the world and has an H-index of 179 according to Google Scholar with over 146,000 citations), and his ideas have influenced researchers, software developers, and standardization committees working on process support. According to Research.com, he is the highest-ranked computer scientist in Germany and ranked 9th worldwide. 

He previously served on the advisory boards of several organizations, including Fluxicon, Celonis, ProcessGold/UiPath, and aiConomix/Automaited. Van der Aalst received honorary degrees from the Moscow Higher School of Economics (Prof. h.c.), Tsinghua University, and Hasselt University (Dr. h.c.). He is also an IFIP Fellow, IEEE Fellow, ACM Fellow, and an elected member of the Royal Netherlands Academy of Arts and Sciences, the Royal Holland Society of Sciences and Humanities, the Academy of Europe, the North Rhine-Westphalian Academy of Sciences, Humanities and the Arts, and the German Academy of Science and Engineering. In 2018, he was awarded an Alexander-von-Humboldt Professorship.

Enabling Process Mining Capabilities for Managing and Improving Intertwined Construction Business Processes: A Change Order Management Process Use Case

Araham is a PhD student in Building Engineering at Concordia University. He is a passionate professional about driving digital transformation in the construction industry through innovation and state-of-the-art technologies and methodologies for managing and executing construction operations in a more efficient and automated manner throughout the entire life cycle of construction projects. Araham’s current efforts focus on data-driven process engineering in construction with a symbiotic combination of research and industry applications aiming at helping to overcome construction productivity stagnation.

Araham holds a Bachelor’s degree in Civil Engineering and a Master’s in Construction Management. He has 10+ years of experience in the construction industry working on residential, industrial, institutional and infrastructure construction projects.

Demo: Queue mining with SiMLQ

Arik Senderovich is an Assistant Professor at the School of Information Technologies (ITEC) at York University and a Status-Only Assistant Professor at Rotman School of Management (University of Toronto). His research intersects Operations Management, Data Science, and Artificial Intelligence, focusing on developing methodologies for modeling complex, congested environments like hospitals and public transportation systems. He is also the co-founder of a U of T based start-up company, SiMLQ, that provides simulation- and ML-driven solutions to business analytics in congested queueing systems. 

Jacques is a digital leader obsessed with delivering solutions that provide clear ROI, and transformational impact. He is experienced in managing traditional IT projects, software development teams, and more recently, Intelligent Automation - including low-code, Robotic Process Automation (RPA), Process Mining and Workflow Automation. Jacques has over 20 years of experience in IT, and is a recent graduate of the Master’s of Digital Transformation and Innovation program at the University of Ottawa (2023). He is always seeking opportunities to grow and generate organizational impact by leveraging data, intelligent automation, and modern digital toolsets.

Kavya Mallur is a seasoned professional with a strong background in business process management and a Master’s degree in Computer Science from the University of Ottawa. After gaining valuable experience at several private companies, Ms. Mallur transitioned to the public sector, bringing with her a wealth of industry knowledge and expertise. Currently serving as a Technical Advisor at Transport Canada, Ms. Mallur plays a pivotal role in leading process-based application development on low code platform- Appian. With a deep understanding of both technical intricacies and business processes, she is instrumental in driving innovation and efficiency within the organization. Having successfully led process mining projects at Transport Canada last year, Ms. Mallur has demonstrated her ability to analyze, optimize, and streamline workflows effectively. 

On the use of semantic knowledge graphs for querying event logs and process models

William received his PhD in Applied Computer Science at the Vrije Universiteit Brussel in Belgium. He was a Research Associate at Dalhousie University, and a Visiting Researcher at the Universidad Politécnica de Valencia, Spain. Themes of particular interest are Knowledge Representation and Reasoning, Process Mining, and, to a lesser extent, Mobile Computing. William is the co-chair of the W3C Community Group on Notation3, a declarative semantic language to implement decision making in open web environments. In the field of Process Mining, it is his ambition to integrate Knowledge Graph technology to more effectively cope with incomplete logs and models, answer process-related questions, and check conformance with normative models.