Medical & Clinical Vision
Medical image classification, segmentation, and decision-support research across X-ray, MRI, CT, ultrasound, retinal imaging, and dermatology.
- Medical imaging
- Transfer learning
- Segmentation
- Clinical evaluation
COMPUTER VISION · MEDICAL AI · AI EDUCATION
Hello, I am
Simeon Yuda Prasetyo
Ir., S.Kom., M.Kom., IPP, CSCU
AI Researcher and Computer Science Lecturer
I build visual intelligence that people can understand and use.
My research connects medical imaging, efficient deep learning, and interpretable computer vision. I also turn these ideas into funded projects, learning tools, student mentoring, and community programmes.
Based in Indonesia · Open to research, education, and responsible AI collaboration
SIMEON AI LAB
Research you can touch, play, and test.
A separate interactive laboratory turns computer vision, gesture, sound, and lightweight research models into experiences that run locally whenever the model permits it.
On-device firstPrivacy-awareGPU / CPU fallbackBuilt for learning
Creative vision
AI Interactive Canvas
Draw, edit, and transform a digital canvas with hand gestures and intelligent tools.
Enter the AI LabMovement & play
Vision Arcade
Play camera-controlled experiences powered by pose and hand tracking.
Enter the AI LabGesture & sound
Vision Instrument Lab
Turn hand motion into rhythm, harmony, spatial sound, and visual performance.
Enter the AI LabPORTFOLIO MAP
Research, projects, and impact in one connected portfolio.
Explore the scientific questions, publications, funded work, academic service, and educational programmes behind the profile. Each activity is recorded once and linked where it is relevant.
Research
My research asks how computer vision can remain accurate while becoming more efficient, interpretable, and useful in settings where data, computation, and trust are limited.
ExplorePublications
The catalogue combines public scholarly profiles and publisher records. Journal articles, proceedings articles, and conference papers are labelled separately rather than collapsed into one count.
ExploreProjects & Funding
The records below are a static, verified snapshot of the public SINTA research-project listing. “Principal Investigator”, “Co-Investigator”, and “Research Member” are not treated as interchangeable.
ExploreImpact
Each activity is presented once, with its context, contribution, documentation, and source. The focus is on what was delivered and who benefited, rather than repeating the same event across multiple sections.
ExploreResearch
A connected research agenda.
The work moves from visual feature learning to efficient, explainable, and socially relevant AI.
Efficient Vision Models
Feature-space efficiency, lightweight architectures, dimensionality reduction, and model design for constrained computational settings.
- Efficient CNNs
- Feature selection
- Multi-scale learning
- Model compression
Explainable & Reliable AI
Attention mechanisms, visual explanations, evaluation beyond accuracy, and responsible framing for high-stakes use.
- Attention
- Interpretability
- Robust evaluation
- Responsible use
AI Education & Human Capability
Interactive demonstrations, teacher development, student mentoring, and ways to make AI concepts observable and teachable.
- AI literacy
- Learning tools
- Teacher development
- Student mentoring
Research trajectory
Past work, current concentration, and the next research horizon are presented as one continuous line of inquiry.
Foundation
Comparative machine learning and transfer-learning experiments across health, agriculture, and visual-recognition tasks.
Concentration
Medical imaging, visual feature extraction, attention mechanisms, and efficiency-oriented architecture studies.
Current line
Funded projects on paediatric pneumonia, skin-image feature spaces, and collaborative health AI.
Research horizon
Reliable, efficient, and explainable computer vision under limited and heterogeneous data.
Projects & Funding
Funded work with clearly stated roles.
Project leadership and team membership are separated to avoid overstating contribution.
2026
Principal Investigator
Efficiency Characterization of Convolutional Feature Space via Swarm Intelligence-Based Dimensionality Reduction in Skin Problem Imagery
A funded study examining how swarm-intelligence-based dimensionality reduction can characterize and streamline convolutional feature spaces for skin-image analysis.
- Funding scheme
- HIBAH PENELITIAN BINUS 2026 (PPB)
- Listed amount
- Rp 10.000.000
- Project leader
- Simeon Yuda Prasetyo
- Team
- Ghinaa Zain Nabiilah, Erna Fransisca Angela Sihotang
- Status
- Approved
2024
Principal Investigator
Paediatric Pneumonia Detection in Chest X-Ray Images Using ConvNeXt
A principal-investigator project studying ConvNeXt-based classification for paediatric chest X-ray pneumonia detection.
- Funding scheme
- HIBAH PENELITIAN BINUS 2024 (PPB)
- Listed amount
- Rp 10.000.000
- Project leader
- Simeon Yuda Prasetyo
- Team
- Santy, Abram Setyo Prabowo
- Status
- Approved
Publications
Selected publications
2026Conference Paper
Does Explicit Reasoning Improve Translation? Benchmarking Chain-of-Thought vs. In-Context Learning for Indonesian-English Language Pairs
IEEE conference proceedings
Google Scholar2025Conference Paper
CBAM-Enhanced Classification Head for VGG16-Based Pneumonia Detection
Conference proceedings
Google Scholar2025Journal Article
Integrating VGG Re-trained Feature Extraction with Machine Learning for Knee Osteoarthritis Severity Levels Detection Using X-ray Images
ITEGAM-JETIA
Google ScholarImpact
Educational work documented through real programmes and outcomes.
Each activity has one primary page with its context, contribution, documentation, and source.
Mastering Coding & Artificial Intelligence for Teachers
A practical programme in Samarinda focused on coding, artificial intelligence, and classroom-ready digital learning for educators.
Fugo Hotel, SamarindaLearn more
Computational Thinking & AI for Teachers at SMKN 6 Malang
A teacher-development session introducing computational thinking, coding concepts, and artificial intelligence through practical classroom-oriented examples.
SMK Negeri 6 MalangLearn more
Best Practices in Computational Thinking for Future Educators
An educator workshop connecting computational-thinking principles with accessible classroom activities and digital learning.
SMAK St. Albertus, MalangLearn moreAcademic Service
Academic service with confidentiality intact.
Reviewer recognition is shown without exposing manuscript details.
Learn more22Documented reviewer activity7Journal reviewer recognition
Contact
Start with the intended outcome.
For research collaboration, laboratory discussion, invited speaking, educator development, academic review, or applied AI prototyping.