Lior Limonad

Lior Limonad is a senior research scientist specializing in AI-empowered Business Automation at the IBM Research Lab (ISRL) in Haifa. In this role, he delves deep into Situation-Aware Explainability (SAX) and Agentic BPM, formulating methods and technologies that automate sound, context-enriched, and human-interpretable explanations for business process outcomes, with novel applications in Agentic BPM. With a tenure spanning over a decade at IBM, Lior has explored various research domains, from design science to human-centric advancements. Notably, he pioneered research in the IoT sphere aimed at bolstering worker safety through wearables. Moreover, Lior has made pivotal strides in developing cutting-edge architectural solutions for business automation, service interoperability, and data-driven decision-making. He has also served as a coordinator and active participant in several EU H2020 projects, including ACSI, SIMUSAFE, MINDTOOTH, and CONBOTS. Most recently, his focus on Situation-Aware Explainability and Agentic BPM has driven novel research results at the intersection of causal discovery and process mining—research that has been employed in IBM technologies and through participation in EU projects such as AutoTwin, FAME, and AI4Gov.

Educationally, Lior earned a B.Sc. in Industrial Engineering and Management with a specialization in Information Systems, and an M.Sc. in Information Systems Engineering, both from Ben-Gurion University of the Negev, Israel. He also holds a Ph.D. in Management Information Systems from the University of British Columbia, Canada. His research interests encompass systems analysis and design, conceptual modeling, knowledge representation and reasoning, ontological applications in information systems, causal discovery, and software engineering.