I’m always eager to connect with researchers and tech innovators working across computer science, network engineering, and IoT security.
I am an incoming MSc student and a Computer Science & Engineering graduate from United International University (UIU), where I majored in Network & Communication. During my undergraduate studies, I consistently earned merit-based tuition waivers for academic excellence, building a strong theoretical foundation that now drives my research at the intersection of IoT security, TinyML, and advanced computer networking.
My current research focuses on securing resource-constrained environments and advancing decentralized learning. I am actively preparing my final year thesis on federated learning and TinyML for publication in an international conference. Concurrently, I am exploring the emerging domain of Large Language Model (LLM) security, specifically investigating its integration within IoT ecosystems to uncover novel vulnerabilities, defensive frameworks, and research outcomes.
I approach my work with a strict emphasis on empirical validation and mathematical rigor. My methodology involves combining extensive simulation testing using frameworks like Flower, systematic data extraction and structuring, and deep mathematical validation to verify my findings.
My technical toolkit includes Python, TensorFlow, and comprehensive data processing pipelines. I am particularly interested in connecting with academic peers and principal investigators focused on IoT Security, Tiny Machine Learning, Federated Learning, and future computer network subdomains.
Always happy to connect and have thoughtful conversations around computer science research, network innovations, and future academic collaborations.

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