Meet the Team

About Us

Pioneering the future of AI-powered medical diagnostics through cutting-edge research in deep learning, computer vision, and autonomous agent systems at Kyoto University

Professor Liang ZHAO

Liang ZHAO

Professor

Kyoto University, GSAIS

Position

Professor in AI, Network Science, Algorithm, and Informatics-Centered Multidisciplinary Study at GSAIS

Education

  • • Doctor of Informatics - Kyoto University
  • • M.E. - Kyoto University

Previous Positions

  • • Guest Professor - Karlsruhe Institute of Technology
  • • Associate Professor - Kyoto University
  • • Senior Lecturer - Kyoto University
  • • Assistant Professor - Utsunomiya University

Research Interests

AI Network Science Algorithms Optimizations

Leadership

Active member in leadership and international student programs at Kyoto University

Rimsa Goperma

Rimsa Goperma

PhD Student & Researcher

Kyoto University

Position

PhD Student conducting research in AI-powered medical imaging. AURA was developed as a concept as part of her PhD thesis.

Education

  • • Master's Degree - Kyoto University

Research Interests

AI Deep Learning Image Processing VLM Agentic AI Medical AI Glaucoma

Specialized in AI-powered medical diagnostics with focus on vision-language models and autonomous agents

Academic Experience

Visiting Scholar - Medical AI Research

Tsinghua University, Beijing

PhD Researcher

Kyoto University, Japan

Experience

Generative AI Intern

Systems Shared, Tokyo

AI research and development

Rojan Basnet

Rojan Basnet

PhD Student & Researcher

Kyoto University

Position

PhD Student specializing in AI and deep learning with focus on medical imaging and autonomous AI systems

Education

  • • Master's Degree - Kyoto University

Research Interests

AI Deep Learning Image Processing VLM Agentic AI Medical AI

Experience

Generative AI Research Intern

Infosys

6-month internship in AI and software development

Our Mission

To revolutionize ophthalmology through autonomous AI agents that provide accurate, accessible, and instant glaucoma diagnosis. We combine cutting-edge deep learning, multi-agent orchestration, and clinical expertise to save sight and improve lives worldwide.

Our Vision

To become the global standard for AI-powered ophthalmological diagnosis, making advanced glaucoma screening accessible to every corner of the world. We envision a future where preventable blindness is eliminated through early detection and intelligent healthcare.

Future Work

Advancing AURA with next-generation AI technologies and comprehensive clinical integration

Visual Field Test AI

Integration of AI-powered visual field analysis to assess peripheral vision loss and disease progression patterns

OCT-based 3D Modeling

Advanced 3D reconstruction from optical coherence tomography for detailed retinal layer analysis and structural assessment

Multimodal AI Fusion

Comprehensive integration of fundus images, OCT scans, visual field data, and patient demographics for holistic diagnosis

Doctor Feedback Loop

Human-in-the-loop system enabling ophthalmologists to validate, correct, and continuously improve AI predictions through active learning

Longitudinal Analysis

Time-series analysis of patient data to predict disease progression, treatment response, and personalized intervention timing

Enhanced Explainability

Advanced visualization and natural language explanations to help clinicians understand AI reasoning and build trust in automated diagnosis

Federated Learning

Privacy-preserving collaborative learning across multiple hospitals to improve model robustness without sharing sensitive patient data

Mobile Deployment

Edge computing implementation for real-time diagnosis on mobile devices, enabling screening in remote and underserved areas