Advancing Healthcare Through Artificial Intelligence
Computational Healthcare Intelligence Lab
The CHI Lab is ICRI-STE’s dedicated research healthcare lab for transforming complex medical data into actionable clinical insights. We bridge the gap between advanced computational science and modern medicine, providing researchers and healthcare professionals with the cutting-edge algorithms and predictive models needed to pioneer the next generation of patient care.
Our Mission & Core Focus
Designed to bridge the divide between computational theory and clinical practice, the CHI Lab harnesses advanced machine learning and deep learning to revolutionize diagnostics and health systems. We empower interdisciplinary researchers to turn complex biomedical data into life-saving solutions.
- Diagnostics: Developing high-accuracy predictive algorithms for early disease identification and risk stratification.
- Personalization: Creating data-driven models that tailor therapeutic treatments to individual patient profiles and clinical histories.
- Integration: Translating theoretical algorithms into scalable, clinical-grade software applications for global healthcare networks.
ICRI-STE & Open Science Nominated Researchers
CHI Lab Research Community
Proposed Role: Principal Scientist (R3-B) & Founding Director
Primary Domain: Computational Healthcare Intelligence, Systems Biology & AI
Potential Contribution: Strategic leadership in computational healthcare research, systems biology modeling, AI-driven biomedical control, computational cancer research, federated learning, virtual lab of agentic system development, interdisciplinary collaboration, and early-career researcher mentorship within the Lab.
Proposed Role: Principal Scientist (R3-A)
Primary Domain: Computational Drug Discovery & Antibody Engineering
Potential Contribution: Antibody modeling, structure-based drug design, computational pharmaceutical research, medicinal chemistry, and AI-driven biomedical innovation within the Lab.
Proposed Role: Senior Scientist (R2-B)
Primary Domain: Bioinformatics & Computational Biology
Potential Contribution: Multi-omics, genomics, reproducible research, AMR surveillance, and machine learning for biomedical applications.
Proposed Role: Senior Scientist (R2-C)
Primary Domain: Intelligent Biomedical Control & Computational Systems Engineering
Potential Contribution: Intelligent therapeutic optimization, biomedical control systems, reinforcement learning, scientific machine learning, cancer therapy modeling, and computational approaches for glucose regulation.
Proposed Role: Junior Research Scientist (R1-C)
Primary Domain: Bioinformatics & Computational Biology
Potential Contribution: Bioinformatics analysis, genomic/transcriptomic research, computational workflows, and data-driven biomedical research.
Proposed Role: Junior Research Scientist (R1-A)
Primary Domain: Computer Science & Artificial Intelligence
Potential Contribution: AI-driven research support, computational workflow development, programming and automation, data analysis, and collaborative computational research.
Proposed Role: Early Career Researcher (ECR1-C)
Primary Domain: Artificial Intelligence, Machine Learning & Computational Biology
Potential Contribution: Medical AI, multimodal computational biology, federated learning, LLMs/RAG, biomedical data analysis, cancer research, and privacy-preserving AI systems
Proposed Role: Early Career Researcher (ECR1-C)
Primary Domain: Artificial Intelligence, Biomedical AI & Computational Biology
Potential Contribution: Multimodal cancer-cell analysis, scRNA-seq research, medical LLMs/RAG, federated learning, biomedical data analysis, and privacy-preserving AI for computational cancer research.
Proposed Role: ECR1-B