Curriculum
Computer Science for Societal Challenges and Innovation, XXXIX series
Grant sponsor
Università degli Studi di Padova
Supervisor

Massimiliano De Leoni
Co-supervisor
s
TBD
Contact
faizanahmed.khan@studenti.unipd.it

Project description
This project aimed at enhancing Robotic Process Automation (RPA) lifecycle management by integrating Task Mining techniques. RPA has gained prominence for automating routine processes, but challenges remain in identifying, automating, and managing these routines effectively. Task Mining offers insights into user interactions and process patterns, presenting opportunities to address these challenges.
The project's primary goal is to optimize RPA processes, expand routine identification capabilities, and contribute to automation literature by understanding process variations, identifying candidates for automation, managing errors, and recommending automation solutions.
The research spans three years, involving a comprehensive literature review, the development of innovative techniques for routine identification, reasoning about complex automatable routines, and defining routine equivalence for efficient automation. The project also investigates handling partially deterministic routines and broadening the scope of RPA lifecycle management to include performance mining.
This interdisciplinary approach combines Task Mining, Human-Computer Interaction, RPA, Process Optimization, and Data Mining to advance automation systems. The expected outcomes include novel strategies for routine identification, advanced automatable routine discovery methods, and an extended RPA lifecycle management scope. Ultimately, this research aims to enhance RPA systems' efficiency and productivity, contributing to the evolution of automation in organizations.