Open Source · 530+ Stars
An agentic AI framework featuring a dual-layer memory architecture for context-aware autonomous agents. Combines SQLite-backed persistent memory with an in-memory transient layer for fast, session-scoped working memory.
Key Contributions
- •Designed and implemented the memory mechanism as core developer
- •Architected a dual-layer memory system for context-aware agent behaviour
- •Built a persistent memory layer backed by SQLite for long-term knowledge retention and retrieval across agent sessions
- •Developed an in-memory storage layer for transient, session-scoped context, enabling low-latency access to short-lived working memory during agent reasoning
- •Enabled agents to maintain coherent state across sessions while keeping real-time reasoning latency low
Dual-GAT Fault Diagnosis
Scientific Reports (Nature), 2025
Developed a dual graph attention network (Dual-GAT) for automated fault detection and classification in photovoltaic inverter systems. The model leverages both spatial and spectral graph convolutions to capture complex inter-feature relationships, enabling robust diagnosis under noisy and imbalanced operating conditions.
Key Contributions
- •Proposed a Dual-GAT architecture combining spatial and spectral graph convolutions
- •Captured complex inter-feature relationships in photovoltaic inverter fault signals
- •Achieved robust fault diagnosis under noisy and imbalanced conditions
- •Published in Scientific Reports (Nature), vol. 15, no. 1, p. 31330, 2025
Hyperspectral Image Classification
ICCIT 2022 (IEEE)
Proposed an attention-aware memory aggregation network that combines spectral-spatial feature extraction with an external memory module for improved classification of hyperspectral remote sensing imagery.
Key Contributions
- •Designed an attention-aware memory aggregation network for hyperspectral image classification
- •Combined spectral-spatial feature extraction with an external memory module
- •Developed an attention mechanism that selectively emphasises discriminative spectral bands
- •Memory module retains representative class prototypes across training iterations
- •Published at the 25th ICCIT, IEEE, 2022