Funded research with roles, schemes, and amounts stated precisely.
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.
Funding snapshot
Funding snapshot
Rp 120.000.000Total value represented across five listed projects
2Projects led as Principal Investigator
3Projects joined as collaborator or member
Funded research records
Funded research records
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.
Optimizing Feature Extraction in CNNs for Skin Cancer Classification: A Dilated Convolutional and Squeeze-Excitation Network Approach
A collaborative project investigating dilated convolution and squeeze-excitation mechanisms for feature extraction in skin-cancer image classification.
Funding values, schemes, status, and roles are presented as listed by SINTA on 29 July 2026. The website does not claim that the full project value was personally secured by a team member who was not the project leader. SINTA
What the portfolio of grants reveals
What the portfolio of grants reveals
Medical computer vision
Three projects address pneumonia, skin cancer, or skin-image analysis.
Efficiency as a research question
The 2026 lead project treats feature-space efficiency as a central scientific problem.
Leadership and collaboration
Two projects are led as Principal Investigator; three are collaborative roles.
Contact
Start with the intended outcome.
For research collaboration, laboratory discussion, invited speaking, educator development, academic review, or applied AI prototyping.
