Disputas - Master of Engineering Miguel Ángel Tejedor Hernandez

Master of Engineering Miguel Ángel Tejedor Hernandez will May 7th at 12.15 publically defence his thesis for the PhD degree in Science.

Title of the thesis:

«Glucose Regulation for In-Silico Type 1 Diabetes Patients Using Reinforcement Learning»

Popular scientific abstract:

Type 1 diabetes is a metabolic disorder characterized by high blood glucose levels as a consequence of insulin deficiency, requiring lifelong treatment by external insulin administration.

New technologies have impacted currect research for type 1 diabetes, changing how the disease is treated and leading to vast improvements in patient's quality of life. Among others, the artificial pancreas for automatically regulating blood glucose levels has gaines importance in recent years, becoming the holy grail of the diabetes research.

Reinforcement learning methods have emerged as a promising and personalized solution for the blood glucose regulation problem in type 1 diabetes. These algorithms are based on the interaction between a decision making agent and an unknown environment, with the goal of training the agent to take actions that maximize its long term benefit. This thesis explores the use of reinforcement learning methods as a control algorithm in the artificial pancreas system.

 

The thesis is published in Munin and is available at:

https://munin.uit.no/handle/10037/20861.

 

Supervisors:

  • Researcher Jonas Nordhaug Myrhe, Department of Physics and Technology, UiT (main supervisor)
  • Professor Fred Godtliebsen, Department of Mathematics and Statistics, UiT
  • Professor Gunnar Hartvigsen, Department of Computer Science, UiT
  • Professor Robert Jenssen, Department of Physics and Technology, UiT
  • Lecturer Susan Wei, University of Melbourne

Evaluation Committee:

  • Associate Professor Kezhi Li, Institute of Health Informatics, University College London, Storbritannia (1. opponent)
  • Professor Kjersti Engan, Department of Electrical Engineering and Computer Science, Faculty of Science and Technology, UiS (2. opponent)
  • Associate Professor Chiara Bordin, Department of Computer Sciences, UiT The Arctic University of Norway (internal member and leader of the committee)

 

Leader of the public defence:

The leader of the publicc defence is Professor Alfred Hanssen, Vice-Dean for Innovation, Faculty of Science and Technology.

 

Opposition ex auditorio:

If you have any qiestions for the candidate during the public defence, please send an e-mail to alfred.hanssen@uit.no. He will announce the questions during the defence.

 

Trial lecture:

The trial lecture is held on Friday May 7th at 10.15 in the same auditorium. The title of the trial lecture is: «Opportunities and challenges of deep reinforcement learning in healthcare»

 

Streaming:

The defence and trial lecture will be streamed via Mediasite:

https://mediasite.uit.no/Mediasite/Catalog/Full/c6790ebc9c184cdfb889ec28ce06039f21

 

Audience:

UiT follows the national guidelines regarding infection control. A maximum of 20 people are allowed in the auditorium during the defence, as long as everybody keeps a distance of 1 meter at all times.

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Informasjon
Når: 07. mai 2021 kl. 12.15–15.00
Hvor: Auditorium 1.022, Teknologibygget
Studiested: Digitalt, Tromsø
Målgruppe: Ansatte, Studenter
Kontakt: Maren L. Andresen