Stian-Anfinsen Stian Anfinsen. Stian’s research interests are in machine learning methodology development, where he has had a special focus on analysis of remote sensing images. His main research area has been development of image analysis algorithms based on advanced models for the statistical distribution of pixel values in radar images. Based on these models, he has developed estimators for model parameters and algorithms for target detection, change detection and image clustering. He takes a special interest in applications of the Mellin transform and its link to doubly stochastic product models used in coherent imaging, such as radar and ultrasound images. In a new line of research, he is turning his focus to methodology for analysis of multimodal or heterogeneous data, such as change detection in images with different modality or robust regression with heterogeneous data as input.

Robert Jenssen. [Brief CV]. Robert is the head of the UiT Machine Learning Group. He develops novel deep learning methodology and information theoretic and kernel-based machine learning algorithms, focusing on health analytics and on remote sensing applications. Robert is also a Prof II at the Norwegian Computing Center in Oslo. Robert is responsible for UiT’s Machine Learning and Statistics education within the Applied Physics and Mathematics study program. Please see Robert’s official UiT web page or Robert’s somewhat outdated semi-official web page.

Fred Fred Godtliebsen. Fred has long experience in statistics and has current research interests in machine learning methodology development and applications. He has contributed extensively e.g. to the development of scale-space methods. Fred leads the group’s big project on diabetes research, and a project on image analysis-based melanoma detection. He has furthermore contributed to research on inference in electronic health records, and in various aspects of medical image analysis. Fred is a Prof II at the Norwegian Centre for E-health Research.

 You? We are seeking a new faculty member in machine learning for health! [read more]

You? We are seeking a new faculty member in machine learning for renewable energy!


bianchi Filippo Bianchi. Filippo received the B.Sc. in Computer Engineering (2009), the M.Sc. in Artificial Intelligence and Robotics (2012) and the PhD in Machine Learning (2015) from “Sapienza” University, Rome. Filippo worked 2 years as research assistant at the Computer Science department at Ryerson University, Toronto. Filippo’s research interests in machine learning and pattern recognition include graph and sequence matching, clustering, classification, reservoir computing, deep learning and data mining. Filippo is funded by the Norwegian Research Council over FRIPRO project on “Next Generation Learning Machines”. Latest research activities can be found at Filippo’s home page.

jonas Jonas N. Myhre. Jonas works with efficient computations of kernel density derivatives, with density ridge frameworks for manifold unwrapping, and with ensemble-based clustering based on kNN mode seeking. Jonas has had a 6-month stay at the Northeastern University in Boston as a part of his PhD, working closely with Prof. Deniz Erdogmus.

 Phuong Ngo. Phuong is an expert on otimal and robust controllers for nonlinear dynamical systems using machine learning techniques. He has a PhD from Purdue University.

 Ilkka Launonen. Ilkka works on Bayesian methods for reinforcement learning.

PhD Students

WP_20150914_15_35_05_Pro Karl Øyvind Mikalsen. Karl Øyvind  works on health data analytics in a close collaboration with researchers at the University Hospital of North Norway (UNN), and the Norwegian Center for E-Health Research. The data source is the Department of Gastrointestinal Surgery at UNN with several years of big clinical data related to colon cancer and surgery including free text (nurses notes, surgeon’s report etc), semi-structured text, physiological data, blood tests, etc. The group works for example on prediction of post-operative anastomosis leakage and delirium, to name a few. Prof Fred Godtliebsen and Senior researcher Stein Olav Skrøvseth are co-supervisors.

WP_20150914 Michael Kampffmeyer. Michael works on applications and development of deep learning algorithms in a joint effort with researchers at the Norwegian Computing Center in Oslo, Norway. Michael studies issues related to transfer learning, the handling of different image resolutions and multi-modality. He is also interested in the combination of CNNs and unsupervised learning. Senior researcher Arnt-Børre Salberg at the Norwegian Computing Center is co-supervisor. Michael is funded by the Norwegian Research Council over FRIPRO project on “Next Generation Learning Machines”. Please visit Michael’s home page.

sigurd Sigurd Løkse. Sigurd works on robust kernel and information theoretic methods exploiting for example probabilistic cluster kernels as weak learners to build powerful similarity measures for ranking and spectral clustering. Sigurd works on aspects related to ensemble clustering, spectral clustering, Markov chains, and new approaches to missing data problems.

Rogelio Rogelio Andrade Mancisidor. Rogelio is an industrial PhD student financed by Santander Consumer Bank and the Research Council of Norway. The focus of Rogelio’s research is on applications of different Machine Learning techniques in the field of Credit Risk Modeling using Santander Bank’s data.  Credit Risk arises with the uncertainty of whether a client will pay back a granted loan. Machine Learning has shown to outperform traditional classification techniques in this field.

luigi Luigi Luppino. Luigi’s research is related to pattern recognition and machine learning applied to Earth observation and satellite remote sensing. In particular, he is focusing on change detection based on heterogeneous satellite images. A collaboration with Telecom Bretagne (France) and University of Genoa (Italy) is planned to be part of his PhD studies.

 Nhan Van Nguyen. Nhan is an industrial PhD student financed by the company eSmart Systems and the Research Council of Norway. He is working within eSmart System’s “connected drone” project, and will focus on developing image and video based automated analysis of power grids using deep learning techniques.              

  Sara Bjørk. Sara works on developing novel machine learning methodology for domain adaptation and change detection in remote sensing image analysis.

 Jørgen Agersborg. Jørgen works on the project “Methodological Advancement of Climate-ecological Observatory for Arctic Tundra (COAT Tools)”. The project seeks to further develop the use of remote sensing data for the Climate-ecological Observatory for Arctic Tundra (COAT), and provide tools for analyzing the data. From 2012 to 2017 he worked as a scientist in the Air and Space Systems Division at the Norwegian Defence Research Establishment (FFI).

 Thomas Johansen. Thomas works on multispectral imaging for melanoma detection and characterization.

 Brian Liu. Brian is a researcher at the Norwegian Computing Center (NR) and at the same time a PhD student in the UiT Machine Learning Group. His supervisor at NR is Arnt-Børre Salberg. Brian works on deep learning techniques applied to remote sensing data analysis. His PhD thesis will, among other topics, focus on multi-view objects detection, instance-aware segmentation, multi-resolution data fusion and domain adaption into remote sensing images.

 Samuel Kuttner. Samuel works on the project “advancing diagnosis and treatment for lung cancer patients using hybrid PET/MR imaging and novel visualization tools”. This is a collaboration between the PET-center in Tromsø, the Department of Clinical Medicine at UiT, and the Machine Learning Group.

 Miguel Hernandez. Miguel has experience in the use of machine learning algorithms in medical applications using hyperspectral images. His current research interests are focusing on reinforcement learning and simulating the Glucose Insulin model.

Master students

Several master students are affiliated with the group:

Tobias F. Olsen. Tobias is interested in Bayesian learning, including Dirichlet processes for clustering.

Past Visitors

Lorenzo Livi (visiting professor, University of Exeter, UK)

Eric Antonelo (visiting postdoc, Federal University of Santa Catarina, Brazil)

Raul Santos-Rodriguez (visiting professor, University of Bristol)

Inma Mora-Jimenez (visiting professor, U Rey Juan Carlos, Madrid)

Cristina Soguero Ruiz (PhD, U Rey Juan Carlos)

Emma Izquierdo Verdiguier (PhD, U Valencia)

Marius Kloft (PhD, TU Berlin)

Aleksey Tyulpin (MSc, Northern Federal U, Arkhangelsk)

Recent MSc Students

Listing 1st employment when known.

Tobias F. Olsen (Data Scientist at Skye Solutions)

Torgeir Brenn

Sara Bjørk (now PhD student in the group).

Thomas Johansen (now PhD student in the group).

Stian Sjøli (PhD student at UiO)

Morten Grønnesby (PhD student, Dept. Computer Science, UiT)

Michael Kampffmeyer (now PhD student in our group)

Sigurd Løkse (now PhD student in our group)

Sigurd Kulseng

Katalin Blix (PhD student, earth observation, UiT)

Ove Kåven

Vidar Vikjord (Microsoft Development Center, Norway)

Jørgen A. Agersborg (at Norwegian Research Defense Establishment, now PhD student in our group)

Jonas N. Myhre (PhD student in our group, now postdoc)

Ola Storås (Fugro Oceanor)






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