High-fidelity CubeSat digital twin built using Qt6, C++ and Python. Realtime telemetry visualization, LoRa reconstruction protocols, onboard AI inference and autonomous mission governance systems.
Built intelligent radar signal pipelines using BIRCH-DPGMM clustering, XGBoost and emitter-agnostic feature extraction for advanced ESM analysis.
Developed VICReg-based self-supervised learning pipelines using multi-channel GADF representations for radar signature discovery.
Systematic research on federated learning architectures for CubeSat and Low Earth Orbit environments focusing on synchronization, communication efficiency and adaptive intelligence.
Realtime university ecosystem built using Flutter, PostgreSQL and Firebase featuring dynamic updates, event systems and connected campus infrastructure.
[ COMMUNICATION NODE ]Experimental messaging architecture focused on realtime synchronization, communication pipelines and distributed interaction systems.
[ BIO SIGNAL SYSTEM ]AI-assisted health monitoring interface integrating realtime analytics, predictive systems and intelligent tracking workflows.
Experimental secure file-sharing mesh between Linux and Windows systems using Qt6 networking and native cross-platform protocols.
Exploring bootloaders, assembly internals, protected mode transitions, memory architecture and kernel-level execution systems.
Deep learning pipelines, computer vision systems, clustering architectures, neural inference workflows and intelligent automation research.
Engineering modern platforms using React, Angular, FastAPI, Spring Boot, PostgreSQL and distributed backend systems.
Building terminal-inspired experiences, cybernetic UI systems, immersive interaction models and unconventional digital environments.
Systematic review of federated learning architectures for satellite intelligence systems with mission-specific deployment decision matrices.
Defense-oriented research using BIRCH-DPGMM clustering and emitter-agnostic feature extraction for complex radar environments.
Real-time radar classification framework using multi-channel time-frequency imaging and feature fusion pipelines.
Comparative study on hybrid machine learning and deep learning architectures for radar mode intelligence systems.