iMulResearch
Group
Informatics ITERAITERAInformatics
ITERA

Students, in two subgroups

Pixel Lab

Image & video

Faces, video and medical images, with models that explain themselves

  • Sigit Kurnia Hartawan

    123140033

    Explainable AI to reveal which facial regions drive blood-pressure estimation

  • Elfa Noviana Sari

    123140066

    Demographic bias and fairness of deep-learning remote photoplethysmography (rPPG) across skin tones

  • Memory Simanjuntak

    123140095

    Cross-population validation of computer-vision models that detect student engagement (DAiSEE dataset)

  • Romualdus Hary Prabowo

    123140083

    Lightweight CNN compression and the reliability of explainable AI (XAI): faithfulness and consistency on medical images

  • Juliani Leony Putri Melati Manalu

    123140029

    Quantitative faithfulness of explainable-AI methods on Vision Transformers for diabetic retinopathy grading

  • Muhammad Fadhilah Akbar

    123140003

    BISINDO sign-language alphabet classification with hybrid multi-variant MobileViT and weighted cross-entropy loss

Waveform

Signals

Brain and heart signals (EEG, ECG) read by interpretable models

  • Riyan Sandi Prayoga

    123140176

    Multilabel ECG classification with unidirectional Mamba

  • Mohd. Musyaffa Alief Athallah

    123140184

    Interpretable machine learning with XGBoost and SHAP to classify thermal comfort from EEG signals (HERO dataset)

  • Muhammad Fajri Firdaus

    123140050

    Interpretable machine learning to find shared and disorder-specific qEEG markers across major psychiatric disorders