Trial lecture - time and place
The trial lecture starts at 10.15 in room A-1.025
The title of the trial lecture is “Generative AI Techniques and Tools for Logistics: Risks and Opportunities”
Live stream:
Trial lecture: 10:15 - 11:00: https://himolde.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=61b15e0e-657e-486a-b61c-b0ed00f71d2d
Defence: 12:15: https://himolde.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=10f06a06-c9f6-489b-a4b8-b0ed00f8a719
Adjudication committee
- Professor Ana Maria Dias Madureira Pereira, Polytechnic of Porto, Portugal
- Professor Alberto Manuel Rodrigues da Silva, Department of Computer Science
and Engineering, Universidade de Lisboa, Portugal - Professor Arild Hoff, Faculty of Logistics, Molde University College
Chair of defence
Professor Harald Martin Hjelle, Faculty of Logistics, Molde University College
Supervisors
- Main supervisor, Professor Berit Irene Helgheim, Faculty of Logistics, Molde University College
- Co-supervisors: Associate Professor Birgithe Eckermann Sandbæk from Molde University College and Associate Professor Nikhil Varma from Ramapo College of New Jersey, USA
Additional information
In a pioneering effort to reshape hospital production processes, the research explores the transformative potential of artificial intelligence (AI) in healthcare. Leveraging machine learning, deep learning, and process mining, the research focuses on turning raw data into practical decisions to enhance operational efficiency and elevate patient care.
Through the implementation of four distinct analytics approaches—descriptive, diagnostics, predictive, and prescriptive—the study delves into the existing system of operations, offering insights for resource planning and allocation. The result is a strategic blueprint for the integration of AI into hospital processes, promising not only improved efficiency but also ushering in a new era of data-driven decision-making.
Addressing the challenges faced by healthcare systems, this dissertation aligns with global sustainability goals, notably contributing to the UN's "good health and well-being" initiative and aligning with Norway's e-health strategy. More than an academic endeavor, this research provides practical insights poised to revolutionize hospital production processes.
Background for the thesis
To harness artificial intelligence, to optimize hospital production processes and address the challenges faced by the healthcare systems in Norway.
The impact of the thesis
The research holds the potential to reshape the landscape of hospital operations by integrating artificial intelligence, contributing not only to advancements in academic knowledge but also offering practical insights that can catalyze transformative changes in hospital production processes.
Agaraoli Aravazhi (33) comes from Chennai, India. He holds a Bachelor of Technology in Mechanical Engineering from Amrita Vishwa Vidyapeetham University, India (2011) and a Master of Science in Engineering Logistics from Molde University College (2016). While pursuing his PhD, Agaraoli worked as a PhD Research Fellow at Molde University College.