Rizki Nurfauzi
PhD student in Medical Engineering, Chiba University, Japan
Hello, I’m Rizki. I am an AI engineer specialist with a strong background in Medical Image Processing, Signal Processing, and Computer-Aided Diagnosis (CAD). I have over 6 years of experience developing AI applications for medical imaging, such as bleeding detection in whole-body CT images, DR detection in Fundus images, malaria detection in microscopy smear images, etc. Currently, I'm work as Postdoctoral Researcher in biomedical engineering focused on AI-driven medical imaging and Electrical Impedance Tomography (EIT). Conducting research on wearable breast EIT systems, deformation-aware deep learning, and noninvasive diagnostic technologies. Experienced in simulation, 3D image analysis, deep learning, and medical device-oriented research. Contributing to interdisciplinary projects in healthcare technology, signal processing, and intelligent sensing systems. Strong background in translating research concepts into practical clinical solutions, with publications in medical imaging and AI-based diagnosis. Actively collaborating in international research environments and advancing next-generation biomedical measurement systems..
EDUCATION
Doctoral Student in Medical Engineering | Chiba University, Japan | 4/2023 –3/2026
Master of Engineering in Electrical and Information Engineering | Universitas Gadjah Mada, Indonesia | 2/2016 – 11/2017
Bachelor of Science in Physics | Universitas Gadjah Mada, Indonesia | 8/2008 – 3/2013
PROFESSIONAL EXPERIENCE
Research Assistant (Electrical and Information Engineering) -Hanung Adi Nugroho Lab.
Universitas Gadjah Mada, Yogyakarta, Indonesia | 10/2017 – 3/2023
- Developed and optimized AI models for medical image and signal processing.
- Conducted research and development in brain signal analysis and medical image AI analysis applications.
- Collaborated on interdisciplinary projects involving AI-driven diagnostics.
Visiting Researcher (Brain)
CTECH Labs Edwar Technology, Banten, Indonesia | 1/2013 – 11/ 2015
- Focused on brain signal analysis and neuroengineering using ECVT 2-Channels.
SKILLS
- Programming Languages: Python, MATLAB, TensorFlow, PyTorch, Keras
- Medical Image Processing: CT, MR, OCT,
- Computer Vision: Object Detection, Image Segmentation
- Signal Processing: Brain Signals, EEG Analysis
FUNDING & FELLOWSHIPS
- All-Directional, Challenging Fusion Innovator Doctoral Talent Development Project (ALDIC-PHD) | Chiba University, Japan | April 2024 – March 2026
- Research Fellowship for Informatics-based Medical Engineering (RIME) | Center for Frontier Medical Engineering, Chiba University, Japan | April 2023 – March 2024
PATEN
- I-Retino (2023),No: EC00202318492, Level: National.
HONORS
- Best Presenter and audience choice awards, 3-Minute Presentation, Chiba University (2025)
- Best Paper, ICOIACT (2019)
SELECTED PUBLICATIONS
- Automated Traumatic Bleeding Detection in Whole-Body CT Using 3D Object Detection Model| Appl. Sci. | 2025
- Automated detection of traumatic bleeding in CT images using 3D U-Net# and multi-organ segmentation |BPEEX | 01/2025
- A combination of optimized threshold and deep learning-based approach to improve malaria detection and segmentation on PlasmoID dataset
FACETS | 01/2023 - Autocorrection of lung boundary on 3D CT lung cancer images | JKSU - Computer and Information Sciences| 06/2021
Email: [email protected]