Bilde av Salahuddin, Suaiba Amina
Bilde av Salahuddin, Suaiba Amina
Overingeniør / COAT, Stipendiat / Maskinlæring Centre for Climate-ecological Observatory Arctic Tundra suaiba.a.salahuddin@uit.no Tromsø

Suaiba Amina Salahuddin


Stillingsbeskrivelse

Jeg er Overingeniør ved Climate-Ecological Observatory for Arctic Tundra (COAT), hvor jeg arbeider med datahåndtering, formatering og visualisering for COATs dataportal.

Jeg er også stipendiat ved UiT Machine Learning Group og SFI Visual Intelligence. Forskningen min fokuserer på å utvikle og implementere avanserte KI-rammeverk for å analysere mammografibilder. Dette inkluderer å lage KI-modeller for klassifisering av brystkreft og brysttetthet, samt å utnytte synsspråkmodeller for å integrere radiologiske rapporter med bildedata, noe som muliggjør utvikling av forklarbare KI-systemer.


  • Solveig Thrun, Zijun Sun, Suaiba Amina Salahuddin, Kristoffer Wickstrøm, Elisabeth Wetzer, Stine Hansen m.fl.:
    Longitudinal Multi-View Breast Cancer Risk Prediction
    Lecture Notes in Computer Science (LNCS) 2026 ARKIV
  • Solveig Thrun, Stine Hansen, Zijun Sun, Nele Blum, Suaiba Amina Salahuddin, Kristoffer Wickstrøm m.fl.:
    Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
    Lecture Notes in Computer Science (LNCS) 20. september 2025 DOI / ARKIV
  • 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. juni 2025 DOI / ARKIV
  • 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 m.fl.:
    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, Zijun Sun, Suaiba Amina Salahuddin, Kristoffer Wickstrøm, Elisabeth Wetzer, Stine Hansen m.fl.:
    Longitudinal Multi-View Breast Cancer Risk Prediction
    25. september 2026 ARKIV
  • Solveig Thrun, Zijun Sun, Suaiba Amina Salahuddin, Kristoffer Wickstrøm, Elisabeth Wetzer, Stine Hansen m.fl.:
    BCRBench: A Breast Cancer Risk Benchmark
    27. september 2026 ARKIV
  • Solveig Thrun, Stine Hansen, Zijun Sun, Nele Blum, Suaiba Amina Salahuddin, Xin Wang m.fl.:
    Reconsidering Spatial Alignment for Longitudinal Breast Cancer Risk Prediction
    05. januar 2026 ARKIV
  • Solveig Thrun, Stine Hansen, Zijun Sun, Nele Blum, Suaiba Amina Salahuddin, Xin Wang m.fl.:
    Reconsidering Spatial Alignment for Longitudinal Breast Cancer Risk Prediction
    07. desember 2025 ARKIV
  • Solveig Thrun, Stine Hansen, Zijun Sun, Nele Blum, Suaiba Amina Salahuddin, Kristoffer Wickstrøm m.fl.:
    Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
    20. september 2025 ARKIV
  • Elisabeth Wetzer, Suaiba Amina Salahuddin, Robert Jenssen, Michael Christian Kampffmeyer, Torkil Stoltz :
    Verdens nordligste KI-konferanse
    08. januar 2025 ARKIV
  • 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 ARKIV
  • Elisabeth Wetzer, Suaiba Amina Salahuddin, Srishti Gautam, Petter Bjørklund :
    What causes an AI program to treat genders differently?
    uit.no 2024 ARKIV
  • Petter Bjørklund, Elisabeth Wetzer, Srishti Gautam, Suaiba Amina Salahuddin :
    Hva får et KI-program til å behandle kjønn ulikt?
    uit.no 2024 ARKIV
  • Petter Bjørklund, Srishti Gautam, Elisabeth Wetzer, Suaiba Amina Salahuddin :
    UiT-forskere peker på tre løsninger for mindre skjev KI
    2024 ARKIV
  • Changkyu Choi, Shujian Yu, Michael Kampffmeyer, Arnt-Børre Salberg, Nils Olav Handegard, Suaiba Amina Salahuddin m.fl.:
    Explaining Marine Acoustic Target Classification in Multi-channel Echosounder Data using Self-attention Mask, Information-Bottleneck, and Mask Prior
    2022 ARKIV
  • Magnus Oterhals Størdal, Suaiba Amina Salahuddin :
    PhD candidates' view on the next generation of deep learning for medical images
    2022 ARKIV

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