About
I am a doctoral research fellow at the Digitial Signal Processing and Image Analysis (DSB) group at University of Oslo, Norway. My research focuses on enhancing the stability and effectiveness of self-supervised learning (SSL) methods for visual data, under the supervision of Prof. Adín Ramírez Rivera and Prof. Michael Kampffmeyer.
Education
- 2024-2027: PhD in Machine Learning at DSB Group, University of Oslo, Norway.
- 2022-2024: MSc in Data Science at Uppsala University, Sweden.
- 2020-2022: BSc in Applied AI at Mälardalen University, Sweden.
- 2018-2020: BSc International Business Management at Mälardalen University, Sweden.
Selected Publications
Gabriel Y. Arteaga, Marius Aasan, Rwiddhi Chakraborty, Martine Hjelkrem-Tan, Thalles Silva, Michael Kampffmeyer, Adín Ramírez Rivera
International Conference on Learning Representations (ICLR), 2026
Project Paper OpenReview Code
Martine Hjelkrem-Tan, Marius Aasan, Gabriel Y. Arteaga, Adín Ramírez Rivera
CVF/ICCV Efficient Computing under Limited Resources: Visual Computing (ECLR) Workshop, 2025
Project Paper OpenReview Code
Gabriel Y. Arteaga, Thomas B. Schön, Nicolas Pielawski
Northern Lights Deep Learning Conference (NLDL), 2025
Paper OpenReview Code
Recent News
February 16, 2026, Research Visit: I will conduct a six-week research visit at the University of Aberdeen in Scotland. The visit will focus on a joint project with Athinoulla Konstantinou on unifying invariant and equivariant self-supervised learning for visual data.
January 26, 2026, Accepted Paper: Our paper, Why Prototypes Collapse: Diagnosing and Preventing Partial Collapse in Prototypical Self-Supervised Learning, has been accepted to the International Conference on Learning Representations (ICLR).
Paper Project OpenReview Code
January 6-8, 2026, NLDL: Attended the Northern Lights Deep Learning Conference (NLDL) in Tromsø, Norway.
October 19-23, 2025, ICCV: Attended the International Conference on Computer Vision (ICCV) in Honolulu, Hawai’i to present our paper SPoT: Subpixel Placement of Tokens in Vision Transformers.
August 14, 2025, Research Visit: Conducted a five-week research stay in Tromsø, Norway, at the Machine Learning Group, UiT Arctic University of Norway, hosted by Prof. Michael Kampffmeyer.
June 20, 2025, Accepted Paper: Our paper SPoT: Subpixel Placement of Tokens in Vision Transformers has been accepted to the Efficient Computing under Limited Resources: Visual Computing (ECLR) workshop at the International Conference on Computer Vision (ICCV) conference. We will present it on October 19 in Honolulu.
Paper Project Code
June 10-14, 2025, Summer School: Participated in the NORA Summer School on Multi-Modal Learning, organized by the Norwegian Artificial Intelligence Research Consortium (NORA) and hosted by Østfold University College in Fredrikstad.
Official Website Course Syllabus
January 23, 2025, PhD Contract Extension: I received a one-month extension to my PhD contract to support the organization of social activities for PhD candidates in the Department of Informatics, including the coordination of monthly lunches.
January 14, 2025, Accepted Paper: Our paper Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-tuned Models has been accepted to the Northern Lights Deep Learning (NLDL) conference. Last week, I had the privilege of delivering both an oral and a poster presentation, where I showcased our method and results.
Paper Slides Poster Code
October 23, 2024, PhD Lunch: Organized a lunch for PhD students at the Department of Informatics which attracted 40 attendees.
September 30, 2024, Guest Lecture: Held a guest lecture on hallucinations in LLMs in a MSc level course on LLMs at Uppsala University.
Slides
September 23-25, 2024, VIGS and VI Days: Attended the 2024 edition of Visual Intelligence Days.
September 4, 2024, Preprint Paper: Our paper Hallucination Detection in LLMs: Fast and Memory-Efficient Finetuned Models is now available as a pre-print paper.
arxiv
August 8, 2024, PhD: Started my PhD at the DSB research group at University of Oslo, Norway.
June 7, 2024, MSc Thesis Defence: I successfully defended my Master Thesis titled “Hallucination Detection in LLMs: Using Bayesian Neural Network Ensembling”.
DiVA