Rizki Nurfauzi

PhD student in Medical Engineering, Chiba University, Japan

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Hello,I am a Medical Engineering researcher with interdisciplinary expertise in artificial intelligence, biomedical imaging, biosignal analysis, signal processing, computer-aided diagnosis, and electrical impedance tomography. I have more than six years of experience developing AI-based methods for medical imaging and diagnostic applications, including traumatic bleeding detection in whole-body CT, diabetic retinopathy screening, and malaria parasite detection.

I currently work as a Postdoctoral Researcher at Chiba University, focusing on EIT, wearable biomedical sensing, physiological monitoring, simulation-based modeling, and deep learning for biomedical measurement and reconstruction. My research bridges medical imaging, biomedical signal processing, intelligent sensing, and medical device-oriented research, with a strong emphasis on translating engineering and AI methods into practical healthcare applications.

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

Post-Doctoral
Chiba University, Japan | Mar 2026 – Now)
Conducting research on wearable breast EIT systems, deformation-aware deep learning, and noninvasive diagnostic technologies. Experienced in 3D image analysis, deep learning, and medical device-oriented research

AI Researcher - [AI X Medical] -
LPIXEL - Tokyo, Japan | 9/2025 – 3/2026

developed deep learning models to segment mice’s bones

Research Assistant
-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

  1. Automated Traumatic Bleeding Detection in Whole-Body CT Using 3D Object Detection Model| Appl. Sci. | 2025
  2. Automated detection of traumatic bleeding in CT images using 3D U-Net# and multi-organ segmentation |BPEEX | 01/2025
  3. A combination of optimized threshold and deep learning-based approach to improve malaria detection and segmentation on PlasmoID dataset
    FACETS | 01/2023
  4. Autocorrection of lung boundary on 3D CT lung cancer images | JKSU - Computer and Information Sciences| 06/2021

Email: [email protected]

  • Education
    • PhD in Medical Engineering, Chiba University
    • Master of Electrical Engineering, Gadjah Mada Univ