Thorsteinn Rognvaldsson

Thorsteinn Rognvaldsson

Högskolan i Halmstad

H-index: 28

Europe-Sweden

About Thorsteinn Rognvaldsson

Thorsteinn Rognvaldsson, With an exceptional h-index of 28 and a recent h-index of 15 (since 2020), a distinguished researcher at Högskolan i Halmstad, specializes in the field of Artificial Intelligence, Machine Learning, Bioinformatics, Data Mining.

His recent articles reflect a diverse array of research interests and contributions to the field:

Advances and challenges in meta-learning: A technical review

Improving Concordance Index in Regression-based Survival Analysis: Discovery of Loss Function for Neural Networks

Personalized Federated Learning with Contextual Modulation and Meta-Learning

Meta-learning for efficient unsupervised domain adaptation

Multimodal meta-learning through meta-learned task representations

The Concordance Index decomposition: A measure for a deeper understanding of survival prediction models

Material handling machine activity recognition by context ensemble with gated recurrent units

A Framework for Evaluating Synthetic Electronic Health Records

Thorsteinn Rognvaldsson Information

University

Position

Professor of Computer Science

Citations(all)

2932

Citations(since 2020)

823

Cited By

2355

hIndex(all)

28

hIndex(since 2020)

15

i10Index(all)

45

i10Index(since 2020)

23

Email

University Profile Page

Högskolan i Halmstad

Google Scholar

View Google Scholar Profile

Thorsteinn Rognvaldsson Skills & Research Interests

Artificial Intelligence

Machine Learning

Bioinformatics

Data Mining

Top articles of Thorsteinn Rognvaldsson

Title

Journal

Author(s)

Publication Date

Advances and challenges in meta-learning: A technical review

Anna Vettoruzzo

Mohamed-Rafik Bouguelia

Joaquin Vanschoren

Thorsteinn Rognvaldsson

KC Santosh

2024/1/24

Improving Concordance Index in Regression-based Survival Analysis: Discovery of Loss Function for Neural Networks

Mohammed Ghaith Altarabichi

Abdallah Alabdallah

Sepideh Pashami

Mattias Ohlsson

Thorsteinn Rögnvaldsson

...

2024

Personalized Federated Learning with Contextual Modulation and Meta-Learning

Anna Vettoruzzo

Mohamed-Rafik Bouguelia

Thorsteinn Rögnvaldsson

2024

Meta-learning for efficient unsupervised domain adaptation

Neurocomputing

Anna Vettoruzzo

Mohamed-Rafik Bouguelia

Thorsteinn Rögnvaldsson

2024/3/14

Multimodal meta-learning through meta-learned task representations

Neural Computing and Applications

Anna Vettoruzzo

Mohamed-Rafik Bouguelia

Thorsteinn Rögnvaldsson

2024/2/23

The Concordance Index decomposition: A measure for a deeper understanding of survival prediction models

Artificial Intelligence in Medicine

Abdallah Alabdallah

Mattias Ohlsson

Sepideh Pashami

Thorsteinn Rögnvaldsson

2024/2/1

Material handling machine activity recognition by context ensemble with gated recurrent units

Engineering Applications of Artificial Intelligence

Kunru Chen

Thorsteinn Rögnvaldsson

Sławomir Nowaczyk

Sepideh Pashami

Jonas Klang

...

2023/11/1

A Framework for Evaluating Synthetic Electronic Health Records

Emmanuella Budu

Amira Soliman

Kobra Etminani

Thorsteinn Rögnvaldsson

2023/5/1

Predicting vehicle behavior using multi-task ensemble learning

Expert systems with applications

Reza Khoshkangini

Peyman Mashhadi

Daniel Tegnered

Jens Lundström

Thorsteinn Rögnvaldsson

2023/2/1

Towards Explaining Satellite Based Poverty Predictions with Convolutional Neural Networks

Hamid Sarmadi

Thorsteinn Rögnvaldsson

Nils Roger Carlsson

Mattias Ohlsson

Ibrahim Wahab

...

2023/10/9

How AI ‘sees’ the world–what happened when we trained a deep learning model to identify poverty

The Conversation

Ola Hall

Hamid Sarmadi

Thorsteinn Rognvaldsson

2023

Bridging the Gap: A Comparative Analysis of Regressive Remaining Useful Life Prediction and Survival Analysis Methods for Predictive Maintenance

PHM Society Asia-Pacific Conference

Mahmoud Rahat

Zahra Kharazian

Peyman Sheikholharam Mashhadi

Thorsteinn Rögnvaldsson

Shamik Choudhury

2023/9/4

Understanding Survival Models through Counterfactual Explanations

Abdallah Alabdallah

Jakub Jakubowski

Sepideh Pashami

Szymon Bobek

Mattias Ohlsson

...

2023

Evaluation of Multi-Modal Learning for Predicting Coolant Pump Failures in Heavy Duty Vehicles

PHM Society Asia-Pacific Conference

Yuantao Fan

Amine Atoui

Slawomir Nowaczyk

Thorsteinn Rognvaldsson

2023/9/4

Toward Solving Domain Adaptation with Limited Source Labeled Data

Kunru Chen

Thorsteinn Rögnvaldsson

Sławomir Nowaczyk

Sepideh Pashami

Jonas Klang

...

2023/12/4

Discovering Premature Replacements in Predictive Maintenance Time-to-Event Data

Abdallah Alabdallah

Thorsteinn Rognvaldsson

Yuantao Fan

Sepideh Pashami

Mattias Ohlsson

2023

Meta-learning from multimodal task distributions using multiple sets of meta-parameters

Anna Vettoruzzo

Mohamed-Rafik Bouguelia

Thorsteinn Rögnvaldsson

2023/6/18

Optimal Task Grouping Approach in Multitask Learning

Reza Khoshkangini

Mohsen Tajgardan

Peyman Mashhadi

Thorsteinn Rögnvaldsson

Daniel Tegnered

2023/11/14

Practical joint human-machine exploration of industrial time series using the matrix profile

Data mining and knowledge discovery

Felix Nilsson

Mohamed-Rafik Bouguelia

Thorsteinn Rögnvaldsson

2023/1

Semi-supervised learning for forklift activity recognition from controller area network (CAN) signals

Sensors

Kunru Chen

Thorsteinn Rögnvaldsson

Sławomir Nowaczyk

Sepideh Pashami

Emilia Johansson

...

2022/5/30

See List of Professors in Thorsteinn Rognvaldsson University(Högskolan i Halmstad)

Co-Authors

H-index: 64
Carsten Peterson

Carsten Peterson

Lunds Universitet

H-index: 55
Achim J. Lilienthal

Achim J. Lilienthal

Örebro Universitet

H-index: 54
Leif Lönnblad

Leif Lönnblad

Lunds Universitet

H-index: 40
Mattias Ohlsson

Mattias Ohlsson

Lunds Universitet

H-index: 38
Fredrik Levander

Fredrik Levander

Lunds Universitet

H-index: 34
Henrik Andreasson

Henrik Andreasson

Örebro Universitet

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