Alise Danielle Midtfjord

Doctoral Research Fellow - Risk and Stochastics
Image of Alise Danielle Midtfjord
Norwegian version of this page
Mobile phone +47 93427423
Room 1005
Username
Visiting address Moltke Moes vei 35 Niels Henrik Abels hus 0851 Oslo
Postal address Postboks 1053 Blindern 0316 Oslo

Academic interests

  • Machine learning and Data Science
  • Explainable Artificial Intelligence
  • Applications within risk and safety

Background

Alise did her Master of Science at the Norwegian University of Life Sciences (NMBU) in Environmental Physics. In her thesis, she combined machine learning with image analysis of PET/CT-images of cancer tumors, to predict the treatment outcome. After that, Alise worked with technology consulting for Accenture, working with new technologies like machine learning and extended reality. Since August 2019, she has been a PhD Student at the Department of Mathematics at the University of Oslo. Here she is working on modelling and analysis of multidimensional high-resolution environmental data within safety-critical systems such as airport runway condition management.

Preprint

A Machine Learning Approach to Safer Airplane Landings: Predicting Runway Conditions using Weather and Flight Data

Talks

13 October 2021 - A Machine Learning Approach to Safer Airplane Landings: Predicting Runway Conditions using Weather and Flight Data. Big Insight Lunch.

21 September 2021 - A Machine Learning Approach to Assess Runway Conditions Using Weather Data. 31st European Safety and Reliability Conference.

23 May 2021 - The Fundamentals of AI. Demystify AI - The Fundamentals & Implications

2 November 2020 - Estimating Runway Friction Using Flight Data. 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference

17 June 2020 - Explainable Artificial Intelligence: How to make AI responsible. Global AI on Tour. 

8 February 2020 - Explainable Artificial Intelligence (XAI). Women in Tech Summit 2020. 

Other websites

Tags: Risk, Statistics, Machine Learning, data science
Published Nov. 20, 2019 1:48 PM - Last modified Oct. 18, 2021 9:29 AM