Doctoral, master and intern supervision
Doctoral supervision
Below is a description of past and ongoing doctoral student supervision.
Dec 2025 - Dec 2029 (upcoming): Main supervisor for PhD candidate Isabelle Tingzon, who will also be affiliated with KTH Royal Institute of Technology. Academic supervisor: Prof. Yifang Ban (KTH). The doctoral project is titled ML-Earth: Robust and data-efficient machine learning for Earth observation and is funded by the Swedish Foundation for Strategic Research.
May 2023 - Feb 2025: Co-supervisor for PhD candidate Maria Bånkestad (RISE, Uppsala University). Academic supervisor: Prof. Thomas Schön (Uppsala University). Maria successfully defended her thesis in Feb 2025: Structured models for scientific machine learning: from graphs to kernels.
Master and intern supervision
Below is a description of past and ongoing master student and intern supervision.
Spring 2026 (upcoming): Internship main supervisor for doctoral student Jhonny Hueller within the project PRACTICAL WISION – Automatically identifying and mapping different weed species through the practical application of AI-based image analysis models.
Spring 2026 (upcoming): Co-main supervisor (jointly with Delia Fano Yela and Georg Andersson) of the master thesis students Isak Randahl and Linnea Sartorius, Lund University. Academic supervisor: TBD. Thesis title Machine learning and Earth observation data for monitoring nature restoration.
Spring 2026 (upcoming): Co-supervisor of the master thesis students Fatemeh Mofid, Stockholm University. Academic supervisor: TBD. Thesis title TBD.
Fall 2025 (4 months): Internship main supervisor for Rojina Shakya within the project AI-based remote sensing for monitoring nature restoration and landscape elements at farm level.
Fall 2025 (2 months): Internship co-supervisor for Lovisa Hambäck within the project PRACTICAL WISION – Automatically identifying and mapping different weed species through the practical application of AI-based image analysis models.
Spring 2024: Co-main supervisor (jointly with Martin Willbo) of the master thesis students Agnes Eriksson and Malte Åhman, Lund University. Academic supervisor: Assoc. Prof. Mikael Nilsson. Thesis: The Power of Privilege: Enhancing Land Cover Classification with Privileged Information.
Spring 2024: Co-main supervisor (jointly with Dr. Olof Mogren) of the master thesis students Emma Amnemyr and Daniel Björklund, Lund University. Academic supervisor: Prof. Kalle Åström. Thesis: Active Learning Techniques for Annotation Efficiency in Detecting Coffee Berry Disease.
Fall 2023 (2 months): Internship main supervisor for Dr. Martin Trimmel on the topic of deep neural network activation functions for Earth observation data.
Summer-Fall 2023: Co-main supervisor (jointly with Dr. Olof Mogren) of the master thesis students Axel Eiman and Nils Eickhoff, Chalmers University of Technology. Thesis: Weakly semi-supervised object detection for annotation efficiency: Leveraging a mix of strong bounding box labels and weak point labels for detecting coffee berry disease. The thesis topic is within the area of climate adaptation and was conducted with collaborators in Tanzania (Mpendakazi Agribusiness), who provided data and use-cases. A popular summary can be found here.
Spring 2023: Main supervisor of the master thesis student Ennio Rampello, KTH Royal Institute of Technology. Academic supervisors: Prof. Yifang Ban and Dr. Puzhao Zhang. Thesis: High-altitude navigation to improve the performance of AiRLoc: An RL model for drone navigation. The thesis is related to the area of UAV-based disaster response and management.
Spring 2023: Main supervisor of the master thesis student Vishal Nedungadi, KTH Royal Institute of Technology. Academic supervisors: Prof. Yifang Ban and Ritu Yadav (PhD candidate). Thesis: Active street to aerial view geo-localization. The thesis is related to the area of UAV-based disaster response and management.
Spring 2022: Main supervisor of the master thesis students Anton Samuelsson and John Backsund, Lund University. Academic supervisor: Prof. Kalle Åström. Thesis: Aerial View Goal Localization with Reinforcement Learning. The thesis was subsequently condensed and accepted to a remote sensing workshop at ICLR 2023 (see Publications and preprints above). The thesis is related to the area of UAV-based disaster response and management.