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- Spatial Multi-Omics Fusion — Graph neural networks for integrating spatial transcriptomics and ATAC-seq data
- Diffusion Models — Diffusion language models (D3PM, SEDD), DDPM, and their applications
- Multi-Agent Orchestration — Coordinating multiple AI agents for complex task automation
- Cross-disciplinary ML — Machine learning applications in genomics and protein structure prediction
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Spatial Multi-Omics Fusion Algorithm Graph-neural-network-based spatial multi-omics (RNA + ATAC-seq) fusion & clustering. Dual-graph GAT encoder, asymmetric cross-modal attention, cross-modal reconstruction. Avg ARI 0.903 on 5 datasets (3rd of 10 methods).
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Multi-Agent Orchestration System Coordinates multiple AI agents on complex tasks with centralized task dispatch, context passing, exception handling, and an auditable execution layer for traceability and interpretability.
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Languages & Frameworks
ML / DL
Tools
Cross-disciplinary
Currently Learning
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