- Dr Renuka Sindhgatta Rajan
- Lecturer Service Science
Science and Engineering Faculty,
School of Information Systems
- Discipline *
- Information Systems
- +61 7 3138 1725
- View location details (QUT staff and student access only)
- Identifiers and profiles
PhD (University of Wollongong)
I started my academic career at QUT, School of Information Systems, after working in the Industry research labs for over 15 years. Before joining QUT, I was at IBM Research as a Senior Technical Staff Member, leading research in areas of empirical software engineering, services research, and AI solutions for education technology that included conversational agents or chatbots.
I have worked extensively in the area of predictive analytics for service systems such as IT services. I have the experience of designing and building AI-enabled services for products and platforms. I have published over 40 refereed papers in leading computer science conferences. My current focus of research is the design of trustworthy machine learning techniques for service delivery systems. My interests lie in building interpretable machine learning and deep learning models for business processes and detecting bias in these systems. I am also interested in natural language understanding and dialogue management for domain-specific task-oriented dialogue systems. I have, in the past, worked on the dialogue management and short-response analysis for conversational tutoring systems
- Conducted research in the broad area of service science by applying machine learning and deep learning to automate or improve service delivery systems.
- Published over 40 research papers in highly ranked CORE A*/A conferences that include OOPSLA, ASE, ICSE, KDD, CIKM, BPM, ICSOC (Google h-index:13, 440 citations).
- Filed over 15 patent application with 5 granted patents.
- Operationalized an AI-enabled product by leading the development of natural language understanding and dialogue management of a product that was used by 2000+ users.
- Contributed to the area of resource modelling, optimal resource allocation, task dispatch in business processes.
- Recent research contributions are in emerging areas of designing dialogue-based systems for improving services delivery with a focus on dialogue-management and natural language understanding.
- Explainable predictive analytics for business processes and service delivery systems.
- Dialogue-based systems for industry domains like public services, fintech, IT services, and education.
I have over two decades of industry experience. I have worked in the area of software analytics by mining software development data and predicting defects or bugs.
I have analyzed the operational data of service teams and built a capacity planning solution that enabled the efficient allocation of work in a shared services delivery model. I was involved in developing simulation models for optimal staffing. Team staffing was validated based on data captured from over 500 teams across the organization. The implementation of these projects led to a cost saving of over 10 MUSD to the service delivery teams.