Scholar
Phillip Kingston
Google Scholar ID: jMYmIFkAAAAJ
AppliedAI
Citations & Impact
Citations
2
H-index
1
i10-index
0
Publications
5
Co-authors
1
list available
Publications
Resume (English only)
Academic Achievements
- 1. Published key papers on AI-driven workflow generation and optimization.
- 2. Introduced formal concepts to capture the goal of a process, such as Workflow Signal and Intention.
- 3. Provided a mathematical framework, representing a Workflow Signal as a vector and a Workflow Intention as a tensor.
Research Experience
- 1. Develops frameworks for automatically generating workflows in complex Business Process Outsourcing (BPO) scenarios.
- 2. Represents workflows as Directed Acyclic Graphs (DAGs), providing a structured blueprint of complex processes through task decomposition.
- 3. Uses a two-phase methodology for workflow creation: the generation phase produces candidate workflows from a high-level intention using a Large Work Model (LWM); the optimization phase selects an optimal workflow via path optimization techniques.
Background
- Visiting Professor at State University Kyiv Aviation Institute, Kyiv, Ukraine and a Member of Technical Staff at AppliedAI in Abu Dhabi, United Arab Emirates. His recent research is focused on advancing AI-driven workflow automation in complex business environments.
