M. Rifqi AzkiyaJamaludin
AI researcher, evaluation integrity in clinical AI.
M.Sc. in Information System, 2026.
Open to PhD positions, research roles, and analyst or engineer roles.
About my research
- Based in
- Bandung, Indonesia
- Degree
- M.Sc. in Information System, Pukyong National University
- Languages
- Indonesian, English, Korean
My research addresses trustworthy medical AI, with a focus on evaluation integrity, data-leakage detection and the honest reporting of results in clinical AI benchmarks. I also work on LLM-based explanation and reasoning layers for clinical decision support, explainable AI in safety-critical domains, and computer vision and multimodal learning for medical data. Hybrid quantum-classical machine learning serves as a methodological area.
Awards and scholarships
- Best Paper Award2025
- Global Korea Scholarship (GKS)2023-2026
- Jabar Future Leaders Scholarship (JFLS)2019
Education
- M.Sc., Pukyong National University2024–Aug 2026
- B.Eng. (S.T.), Universitas Islam Negeri Sunan Gunung Djati2018–2022
Publications
- Evaluation integrity in hybrid quantum-classical skin lesion classification: A data-leakage audit and lesion-level correction on HAM10000Journal article2026
- Stable training of hybrid quantum-classical skin lesion classifiers via offline data augmentationLocal conference, poster2026
- Enhanced quantum-based DNA sequence alignment with noise handling and error detectionJournal article2025
- Minimizing qubit requirements in scalable quantum models: Leveraging QECC error detection principlesLocal conference, oral2025
Get in touch
I welcome enquiries about PhD positions, research roles and analyst or engineer roles, and about collaboration on trustworthy medical AI.