I work remotely as an AI researcher at a European-based AI startup. Our main focus is on developing cutting-edge methods and frameworks to enhance LLMs in reasoning, adaptability, and efficiency. During my PhD, my research centered around deep learning applications in healthcare, particularly medical image analysis. I have contributed to AI research through publications and by serving as a reviewer for venues such as MICCAI, MIDL, and MIUA.
- 🧮 Deep Learning
- 🧠 Medical Image Analysis
- ⚖️ Fairness in AI
- 🌏 Open Science & Reproducibility
- 🔍 Recently, I’ve been exploring LLMs 📖🤖
- 🔮 How You Split Matters [Fairness in AI]
- Beyond my PhD research on advancing deep learning techniques for brain MRI analysis, I took the initiative to independently explore the study of data leakage and splitting strategies within the context of longitudinal data. I realized the importance of fairness and avoiding such biases after noticing a lack of attention to them in my region.
- 🛠️ ADNI-processing [Open Science & Reproducibility]
- A structured, reproducible pipeline for preprocessing ADNI MRI data, including DICOM-to-NIfTI conversion, subject organization, and batch processing with SPM. Designed for scalability and ease of use in neuroimaging research.
I am open to collaboration, discussion, or just answering your questions if you have any!
- Email: djrumala[at]gmail[dot]com
- Check my publications here: Google Scholar
- I sometimes write technical tutorials and share my experiences in STEM to promote diversity and inclusion
- My Website: djrumala.github.io (English)
- Medium: Dewinda (English and Bahasa Indonesia)