Bilde av Salahuddin, Suaiba Amina
Bilde av Salahuddin, Suaiba Amina
PhD Student / Machine Learning Department of Physics and Technology suaiba.a.salahuddin@uit.no Tromsø

Suaiba Amina Salahuddin


Job description

I am a PhD student at the UiT Machine Learning Group and SFI Visual Intelligence. My research focuses on developing and implementing advanced AI frameworks for analysing mammography images. This includes creating AI models for classifying breast cancer and breast density, as well as leveraging vision-language models to integrate radiology reports with imaging data, enabling the development of explainable vision AI systems.


  • Solveig Thrun, Stine Hansen, Zijun Sun, Nele Blum, Suaiba Amina Salahuddin, Kristoffer Wickstrøm et al.:
    Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
    Lecture Notes in Computer Science (LNCS) 20. September 2025 DOI
  • Suaiba Amina Salahuddin, Elisabeth Wetzer, Kristoffer Wickstrøm, Solveig Thrun, Michael Kampffmeyer, Robert Jenssen :
    Assessing the Efficacy of Multi-task Learning in Mammographic Density Classification: A Study on Class Imbalance and Model Performance
    Lecture Notes in Computer Science (LNCS) 16. June 2025 DOI
  • Stine Hansen, Srishti Gautam, Suaiba Amina Salahuddin, Michael Christian Kampffmeyer, Robert Jenssen :
    ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement
    Medical Image Analysis 2023 DOI / ARKIV
  • Srishti Gautam, Ahcene Boubekki, Stine Hansen, Suaiba Amina Salahuddin, Robert Jenssen, Marina Marie-Claire Hohne et al.:
    ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model
    Advances in Neural Information Processing Systems 2022 DOI / ARKIV
  • Suaiba Amina Salahuddin, Stine Hansen, Srishti Gautam, Michael Kampffmeyer, Robert Jenssen :
    A self-guided anomaly detection-inspired few-shot segmentation network
    CEUR Workshop Proceedings 2022 ARKIV
  • Solveig Thrun, Stine Hansen, Zijun Sun, Nele Blum, Suaiba Amina Salahuddin, Xin Wang et al.:
    Reconsidering Spatial Alignment for Longitudinal Breast Cancer Risk Prediction
    07. December 2025
  • Solveig Thrun, Stine Hansen, Zijun Sun, Nele Blum, Suaiba Amina Salahuddin, Kristoffer Wickstrøm et al.:
    Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
    20. September 2025
  • Elisabeth Wetzer, Suaiba Amina Salahuddin, Robert Jenssen, Michael Christian Kampffmeyer, Torkil Stoltz :
    Verdens nordligste KI-konferanse
    08. January 2025
  • Suaiba Amina Salahuddin, Elisabeth Wetzer, Kristoffer Wickstrøm, Solveig Thrun, Michael Kampffmeyer, Robert Jenssen :
    Assessing the Efficacy of Multi-task Learning in Mammographic Density Classification: A Study on Class Imbalance and Model Performance
    2025
  • Elisabeth Wetzer, Suaiba Amina Salahuddin, Srishti Gautam, Petter Bjørklund :
    What causes an AI program to treat genders differently?
    uit.no 2024
  • Petter Bjørklund, Elisabeth Wetzer, Srishti Gautam, Suaiba Amina Salahuddin :
    Hva får et KI-program til å behandle kjønn ulikt?
    uit.no 2024
  • Petter Bjørklund, Srishti Gautam, Elisabeth Wetzer, Suaiba Amina Salahuddin :
    UiT-forskere peker på tre løsninger for mindre skjev KI
    2024
  • Changkyu Choi, Shujian Yu, Michael Kampffmeyer, Arnt-Børre Salberg, Nils Olav Handegard, Suaiba Amina Salahuddin et al.:
    Explaining Marine Acoustic Target Classification in Multi-channel Echosounder Data using Self-attention Mask, Information-Bottleneck, and Mask Prior
    2022
  • Magnus Oterhals Størdal, Suaiba Amina Salahuddin :
    PhD candidates' view on the next generation of deep learning for medical images
    2022

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