Alvaro Fernandez Quilez

Associate Professor

Alvaro Fernandez Quilez

Contact

Email: alvaro.f.quilez@uis.no

Location: KE-E437

Department

Faculty of Science and Technology

Department of Electrical Engineering and Computer Science

About me

I am currently leading Stavanger AI Laboratory (SAIL). Feel free to reach out if you're interested in hearing about opportunities for collaboration! (https://www.uis.no/nb/forskning/stavanger-ai-lab/teknologi-og-naturvitenskap/stavanger-ai-lab)

Research interest(s)

My main research area is applied AI in healthcare, with a particular interest in medical imaging (radiology) and in challenges related to reaching clinically useful AI developments.

From a more broad perspective, I'm also interested in the consequences of AI for education and society.

Background 

  • Physics
  • Telecommunications Engineering 
  • Computational Biomedical Engineering
  • Artificial Intelligence

Teaching

Follow me online

LinkedIn

Publications

Vitenskapelige publikasjoner

Hammonds, Solveig Kristina; Eftestøl, Trygve Christian; Oppedal, Ketil; Fernandez Quilez, Alvaro

(2024)

Unraveling Gender Fairness Analysis in Deep Learning Prediction of Alzheimer’s Disease. I: 2024 4th International Conference on Applied Artificial Intelligence (ICAPAI).

IEEE conference proceedings.

ISBN 979-8-3503-4976-4.

DOI: 10.1109/ICAPAI61893.2024.10541140

Gade, Marius; Nguyen, Kevin Mekhaphan; Gedde, Sol; Fernandez Quilez, Alvaro

(2024)

Impact of uncertainty quantification through conformal prediction on volume assessment from deep learning-based MRI prostate segmentation.

Insights into Imaging.

ISSN 1869-4101.

Volum 15.

Hefte 1.

DOI: 10.1186/s13244-024-01863-w

Nguyen, Kevin Mekhaphan; Fernandez Quilez, Alvaro

(2024)

Segmentation Uncertainty with Statistical Guarantees in Prostate MRI.

European Signal Processing Conference.

ISSN 2076-1465.

s.1636-1640.

DOI: 10.23919/EUSIPCO63174.2024.10715449

Rolfsnes, Erlend Sortland; Thangngat, Philip; Eftestøl, Trygve Christian; Nordström, Tobias; Jäderling, Fredrik; Eklund, Martin; Fernandez Quilez, Alvaro

(2024)

On Undesired Emergent Behaviors in Compound Prostate Cancer Detection Systems.

Lecture Notes in Computer Science (LNCS).

ISSN 0302-9743.

Volum 15199.

s.73-82.

DOI: 10.1007/978-3-031-73376-5_7

Fernandez Quilez, Alvaro; Andersen, Christoffer Gabrielsen; Eftestøl, Trygve Christian; Kjosavik, Svein Reidar; Oppedal, Ketil

(2023)

3D Masked Modelling Advances Lesion Classification in Axial T2w Prostate MRI.

Proceedings of the Northern Lights Deep Learning Workshop.

Volum 4.

DOI: 10.7557/18.6787

Anaya-Isaza, Andres; Mera-Jimenez, Leonel; Fernandez Quilez, Alvaro

(2023)

CrossTransUnet: A New Computationally Inexpensive Tumor Segmentation Model for Brain MRI.

IEEE Access.

ISSN 2169-3536.

Volum 11.

s.27066-27085.

DOI: 10.1109/ACCESS.2023.3257767

Fernandez Quilez, Alvaro; Nordström, Jon Tobias; Jäderling, Fredrik; Kjosavik, Svein Reidar; Eklund, Martin

(2023)

Prostate Age Gap: An MRI Surrogate Marker of Aging for Prostate Cancer Detection.

Journal of Magnetic Resonance Imaging.

ISSN 1053-1807.

DOI: 10.1002/jmri.29090

Kurbatskaya, Anna; Jaramillo-Jiménez, Alberto; Ochoa-Gomez, John Fredy; Brønnick, Kolbjørn Kallesten; Fernandez Quilez, Alvaro

(2023)

Assessing Gender Fairness in EEG-Based Machine Learning Detection of Parkinson's Disease: A Multi-Center Study.

European Signal Processing Conference.

ISSN 2076-1465.

DOI: 10.23919/EUSIPCO58844.2023.10289837

Kurbatskaya, Anna; Jaramillo-Jiménez, Alberto; Ochoa-Gomez, John Fredy; Brønnick, Kolbjørn Kallesten; Fernandez Quilez, Alvaro

(2023)

Machine Learning-Based Detection of Parkinson’s Disease From Resting-State EEG: A Multi-Center Study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

ISSN 2694-0604.

DOI: 10.1109/EMBC40787.2023.10340700

Pons, Maria Isabel; Mill, Jordi; Fernandez Quilez, Alvaro; Olivares, Andy L.; Silva, Etelvino; De Potter, Tom; Camara, Oscar

(2022)

Joint Analysis of Morphological Parameters and In Silico Haemodynamics of the Left Atrial Appendage for Thrombogenic Risk Assessment.

Journal of Interventional Cardiology.

ISSN 0896-4327.

Volum 2022.

s.1-10.

DOI: 10.1155/2022/9125224

Fernandez Quilez, Alvaro

(2022)

Deep learning in radiology: ethics of data and on the value of algorithm transparency, interpretability and explainability.

AI and Ethics.

ISSN 2730-5953.

DOI: 10.1007/s43681-022-00161-9

Fernandez Quilez, Alvaro; Eftestøl, Trygve Christian; Kjosavik, Svein Reidar; Goodwin, Morten; Oppedal, Ketil

(2022)

Contrasting Axial T2W MRI for Prostate Cancer Triage: A Self-Supervised Learning Approach.

IEEE International Symposium on Biomedical Imaging.

ISSN 1945-7928.

DOI: 10.1109/ISBI52829.2022.9761573

Fernandez Quilez, Alvaro; Eftestøl, Trygve Christian; Kjosavik, Svein Reidar; Goodwin, Morten; Oppedal, Ketil

(2022)

Multi-Planar T2W MRI for an Improved Prostate Cancer Lesion Classification.

IEEE International Symposium on Biomedical Imaging.

ISSN 1945-7928.

DOI: 10.1109/ISBI52829.2022.9761514

Fernandez Quilez, Alvaro; Eftestøl, Trygve Christian; Kjosavik, Svein Reidar; Oppedal, Ketil

(2022)

Learning to triage by learning to reconstruct: a generative self-supervised approach for prostate cancer based on axial T2w MRI.

Proceedings of SPIE, the International Society for Optical Engineering.

ISSN 0277-786X.

Volum 12033.

DOI: 10.1117/12.2610623

Fernandez Quilez, Alvaro; Parvez, Omer; Eftestøl, Trygve Christian; Kjosavik, Svein Reidar; Oppedal, Ketil

(2022)

Improving prostate cancer triage with GAN-based synthetically generated prostate ADC MRI.

Proceedings of SPIE, the International Society for Optical Engineering.

ISSN 0277-786X.

Volum 12033.

DOI: 10.1117/12.2606557

Fernandez Quilez, Alvaro; Ullah, Habib; Eftestøl, Trygve Christian; Kjosavik, Svein Reidar; Oppedal, Ketil

(2022)

One class to rule them all: detection and classification of prostate tumors presence in bi-parametric MRI based on auto-encoders.

Proceedings of SPIE, the International Society for Optical Engineering.

ISSN 0277-786X.

Volum 12033.

DOI: 10.1117/12.2602884

Minne, Petter; Fernandez Quilez, Alvaro; Aarsland, Dag; Ferreira, Daniel; Westman, Eric; Lemstra, Afina W.; Ten Kate, Mara; Padovani, Alessandro; Rektorova, Irene; Bonnani, Laura; Nobili, Flavio Mariano; Kramberger, Milica G.; Taylor, John-Paul; Hort, Jakub; Snædal, Jon; Blanc, Frederic; Antonini, Angelo; Oppedal, Ketil

(2022)

A study on 3D classical versus GAN-based augmentation for MRI brain image to predict the diagnosis of dementia with Lewy bodies and Alzheimer's disease in a European multi-center study.

Proceedings of SPIE, the International Society for Optical Engineering.

ISSN 0277-786X.

Volum 12033.

DOI: 10.1117/12.2611339

Fernandez Quilez, Alvaro

(2022)

Deep learning for an improved diagnostic pathway of prostate cancer in a small multi-parametric magnetic resonance data regime.

Universitetet i Stavanger.

ISBN 978-82-8439-090-1.

Fernandez Quilez, Alvaro; Larsen, Steinar Valle; Goodwin, Morten; Gulsrud, Thor Ole; Kjosavik, Svein Reidar; Oppedal, Ketil

(2021)

Improving prostate whole gland segmentation in T2-weighted MRI with synthetically generated data. I: 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI).

IEEE conference proceedings.

ISBN 9781665412469.

s.1915-1919.

DOI: 10.1109/ISBI48211.2021.9433793

Castellanos-Perilla, Nicolas; Borda, Miguel Germán; Fernandez Quilez, Alvaro; Aarsland, Vera Vårin Birkemo; Sønnesyn, Hogne; Cano-Gutierrez, Carlos Alberto

(2020)

Factors associated with functional loss among community‐dwelling Mexican older adults.

Biomédica.

ISSN 0120-4157.

Volum 40.

Hefte 3.

s.546-556.

DOI: 10.7705/biomedica.5380

Formidling

Wetzer, Elisabeth; Kozyri, Elisavet; Fernandez Quilez, Alvaro; Razavian, Nages

(2024)

Panel Discussion on "Diversity in AI".

Diversity in AI Event at Northern Lights Deep Learning Conference;

2024-01-09.

Fernandez Quilez, Alvaro; Tjersland, Trond; Podhraski, Andrijana; Gonzalez Velez, Maria Camila; Oppedal, Ketil

(2021)

EARLY DETECTION OF PSYCHOSIS IN PARKINSON’S DISEASE BASED ON NEUROPSYCHOLOGICAL TESTS AND DEMOGRAPHICS: A MACHINE LEARNING APPROACH.

International Conference on Alzheimer's&Parkinson's diseases;

2021-02-01 - 2021-02-05.