Enterprise AI Analytics
We have developed a number of techniques for
designing optimal
Robotic Process Automation
(RPA) architectures,
mining process variants, mining post-conditions
of process tasks, using data analytics to recommend
task allocations, using data analytics for optimal
business process provisioning, managing variability in
business process instances, mining causal links between
business processes and task post-conditions, and mining
enterprise architectures. Our
industry partners for this research theme include IBM
Research, Infosys and Bosch.
- Geeta Mahala, Renuka Sindhgatta, Hoa Khanh Dam
and Aditya Ghose, Designing Optimal Robotic
Process Automation Architectures, Lecture Notes
in Computer Science, Proceedings of the 18th
International Conference on Service-Oriented
Computing (ICSOC 2020).
- Yingzhi Gou, Aditya Ghose and Hoa Khanh Dam,
GameOfFlows: Process Instance Adaptation in Complex,
Dynamic and Potentially Adversarial Domains,
Proceedings of the 31st International Conference on
Advanced Information Systems Engineering (CAISE),
Lecture Notes in Computer Science, To Appear
(acceptance rate: 20%).
- Metta Santiputri, Aditya Ghose, Hoa Khanh Dam,
Mining task post-conditions: Automating the
acquisition of process semantics,
Data and
Knowledge Engineering journal, Volume 109,
May 2017, Elsevier,
dx.doi.org/10.1016/j.datak.2017.03.007
- Metta Santiputri, Aditya Ghose, Hoa Khanh Dam
and Suman Roy, Goal Orchestrations: Modelling
and Mining Flexible Business Processes,
Proceedings of the 36th International Conference on
Conceptual Modeling (ER), Lecture
Notes in Computer Science, Volume 10650 (2017),
pages 373-387,
Springer (acceptance rate: 18,3% for full
papers). Best
Paper Award
- Metta Santiputri, Novarun Deb, Aditya Ghose, Hoa
Khanh Dam, Nabendu Chaki and Muhammad Asjad Khan,
Mining goal refinement patterns: Distilling
know-how from data, Proceedings of the 36th
International Conference on Conceptual Modeling (ER),
Lecture Notes in Computer Science, Volume 10650
(2017), pages 69-76,
Springer (acceptance rate: 25% for both short
and full papers)
- Renuka Sindhgatta, Aditya Ghose, and Hoa Khanh
Dam, Context-Aware Recommendation of Task
Allocations in Service Systems, Proceedings of
the 14th International Conference on
Service-Oriented Computing (ICSOC),
Lecture Notes in Computer Science, Volume 9936
(2016), Springer (acceptance rate: 21%).
- Renuka Sindhgatta, Aditya Ghose, and Hoa Khanh
Dam, Context-Aware Analysis of Process
Executions to Aid Resource Allocation Decision,
Proceedings of the 28th International Conference on
Advanced Information Systems Engineering (CAISE),
Lecture Notes in Computer Science, Volume 9694
(2016), pages 575-589, Springer
- Karthikeyan Ponnalagu, Aditya Ghose, Nanjangud
C. Narendra, Hoa Khanh Dam, Goal-aligned
categorization of instance variants in
knowledge-intensive processes, Proceedings of
the 13th International Conference on Business
Process Management (BPM), Lecture
Notes in Computer Science, Volume 9253 (2015), pages
350-364, Springer