Geir Kjetil Sandve
I studied computer science at NTNU (Norway), focusing on algorithms and machine learning. During my PhD, I surveyed, benchmarked and developed machine learning methodology for motif discovery in biosequences. For my postdoctoral studies (UiO, Norway), I set out to broaden my understanding of statistics, collaborating with biologists and statisticians to pioneer statistical analysis of genomic co-localization. I have through my career tried to combine deep theoretical considerations with applied relevance, aiming to understand both machine learning and application domains at a depth that allows to creatively generate and intuitively judge the promise of research ideas. Currently, my main focus is on doing my part to help make our research environment fun but productive, brutally honest but supportive, and visionary while delivering on our promise.
Ivar achieved both his masters degree and PhD degree in the Sandve lab. In his PhD, titled “Graph-based reference genomes – Approaches and Applications”, he studied how graph-based reference genomes can be used to improve common bioinformatics procedures, such as read mapping and ChIP-seq peak calling. He is currently doing his postdoc in similar topics, studying how graph-based reference genomes can be used to analyse the genetic variation in the Cod species. He is also interested in more general bioinformatics topics, such as genotyping, variant-calling and read-mapping. In his free time he likes to fly his drone, play ping-pong, or go for trips in the woods.
Enrico got his master degree in Chemical Engineering at the Politecnico di Torino, followed by a PhD at the MS&T (Missouri Science and Technology). He then did a Post Doc in Germany and in Norway, working on computational approaches for multiscale modelling. His expertise is centered around molecular dynamics simulations and recently, he started using and adoptim AI methods to increase the predictive power of the simulation. Enrico joined Savne lab in 2021, and his focus is the development of improved ML algorithms.
Knut got his MSc and PhD in bioinformatics (UiO, Oslo) working on game theoretic modeling of cancer and graph based genome representations. He is currently doing his postdoc in machine learning in computational immunology, specifically multiple instance learning in immune repertoire classification. When not training models he likes to run on trails and play music.
Mostafa obtained his BAppSci (Hons) and PhD in Information Science at the University of Otago, New Zealand, and is currently working as a Postdoctoral Research Fellow within the BioMedical Informatics group. The focus of the Postdoc is to both investigate how Machine Learning can be used to unearth insights within epidemiology and also to understand how Causal Learning .
Milena obtained her BSc and MSc degrees in Computer Science at the University of Nis, Serbia and is currently doing a PhD in machine learning and computational immunology (co-supervised by Victor Greiff, Torbjørn Rognes and Ludvig Sollid). As a part of her PhD, Milena is working on a platform that would facilitate machine learning method development and applications for immune receptor data such as immune state classification or antigen binding prediction. She is also interested in generalization in ML and causality.
Lonneke obtained a BSc in bioinformatics (Hanze UAS, Groningen) and a MSc in informatics (UiO, Oslo), and is currently working as a PhD candidate in computational immunology (co-supervised by Pavel Pevzner, Victor Greiff and Yana Safonova). The objective of her PhD is to quantify the impact of germline gene variation on immune receptor repertoires. She will develop representations in which immune repertoire variability is decomposed into genotype- and environment-derived components. These representations will be used for machine learning-based disease classification. In her free time Lonneke enjoys drawing, crafting, sewing and going for hikes in the Norwegian mountains.
Ghadi Al Hajj
Ghadi obtained a BSc and an MSc in Biomedical Engineering (Lebanese International University) and is currently working as a Ph.D. student in machine learning (co-supervised with Johan Pensar). His Ph.D. work will be on improving the generalization of machine learning models through the incorporation of domain priors and constraints. He will work with the BioMedical Informatics group and the Digital Signal Processing and Image Analysis group and focus on how causality can be exploited to improve interpretability, transfer learning capability, and generalization performance of learned models. In his leisure time, he likes to hike, bike, and play the piano!
Co-supervised PhD students
Maria received her Master’s degree in Bioinformatics in Russia. Her projects were devoted to analyzing paired 10-x VDJ datasets and to the construction of mixed metabolic and signaling networks. Currently she is trying to clarify the strength and weaknesses of ML methods applied to AIRR data, under supervison of Victor Greiff and Geir Kjetil Sandve. Maria is addicted to tea and podcasts and she is perfectly fine with that.
Ping-Han has studied biomechatronics engineering in his bachelor and later switched his focus to bioinformatics for the master degree at National Taiwan University (Taipei, Taiwan). He is currently working at Centre of Molecular Medicine Norway (University of Oslo) under the supervision of Dr Marieke Lydia Kuijjer and Dr Geir Kjetil Sandve. His research interest lies in machine learning and network biology. The goal of his doctoral project is to build reliable regulatory networks using graph embedding algorithms. Besides doing research, he loves to spend time with his dog, playing the piano and video games.
Robert is a PhD student in computational immunology supervised by Victor Greiff and Geir Kjetil Sandve. He obtained his Master Degree in Computer Science in Germany (FSU-Jena) with a focus on machine learning and statistics. His PhD-Topic is about predicting antibody-antigen binding with machine learning. In his free time, he practices sword fencing, hiking, fitness stuff and learning new things.
PhD student at UiO: Department of Informatics, co-supervised together with Eivind Hovig.
PhD student at UiO: Department of Mathematics, co-supervised together with Ingrid Hobæk Haff.
Emily is a PhD student at UiO with an affiliation to both the department of Biosciences and the department of Informatics, supervised by Kjetill Sigurd Jakobsen, Geir Kjetil Sandve, Ivar Grytten and Helle Tessand Baalsrud. During her master’s degree Emily worked on the evolution and phylogeny of a group of bryozoans. Between her master and PhD she worked as a research assistant and as a science and maths teacher. In her PhD at CEES (IBV) and BMI (IFI), Emily will be working on graph-based representations and analysis of cod fish genomes, as part of the CELS 2 group.
PhD student at UiO: Faculty of Medicine, co-supervised together with Eivind Hovig and Sigve Nakken.
Karthik obtained his BEng in Electronics from India and MSc in Electronics at the University of Surrey, UK. He also worked as an AI Engineer in London for a few years. His PhD project will focus on the intersection of Machine learning and Software Engineering, where he will investigate novel techniques to code and built ML systems and applications that are scalable, maintainable, and evolvable. This project is supervised by Antonio Martini and co-supervised by Geir Kjetil Sandve. In his free time, he likes to travel and read comics.
Katalin has a background in biology (BSc, Hungary) and biomedicine (MSc, Karolinska Institute). However, by a lucky accident, she got involved in bioinformatics and data science (MSc, University of Gothenburg). Her current project is about building machine learning models to learn about the regulatory signatures of human cell types, and breast cancer subtypes. She is located at the Centre of Molecular Medicine Norway (UiO), and working under the supervision of Dr Anthony Mathelier and Dr Geir Kjetil Sandve. She loves endurance sports, and shortly after moving to Norway, discovered that skiing can also trigger the ‘runner’s high’.
Mats is a Master student at UiO studying Informatics: Programming and System Architecture, and is currently working on streamlining the use of parallelization in a software platform for domain-tailored machine learning analyses (supervised by Geir Kjetil Sandve and co-supervised by Milena Pavlovic and Lonneke Scheffer). In his free time Mats likes to play guitar and video games.