Bio:

I’m an analytical and results-driven Software Engineer with over 8 years of experience in cloud infrastructure, networking systems, and observability engineering. My work spans across C, C++, Go, and Python, with a deep focus on Azure networking, eBPF, Kubernetes, and performance benchmarking.

At Microsoft, I work on Windows Container Networking and Retina Data Path Observability, where I lead large-scale performance benchmarking efforts and integrate Cilium-based eBPF observability on Windows. I’ve contributed to the eBPF-for-Windows open-source project and led the deployment of the Azure Dependency Agent across multiple global regions—enhancing reliability, efficiency, and customer experience for Azure Monitor and VM Insights.

Before joining Microsoft, I worked at Cisco Systems, where I implemented high-availability networking solutions (In-Service Software Upgrades) and developed GRPC-based CLI frameworks to improve visibility and management across distributed systems. Earlier in my career, I interned at Juniper Networks and Versa Networks, where I built automation frameworks, real-time communication features, and pub-sub IPC models for core network components.

Outside of work, I’m passionate about giving back to the tech community. I’ve served as a hackathon judge and mentor at events such as Tidal Hacks, Uncommon Hacks, Diamond Hacks, and Hackabyte, where I enjoy mentoring student developers and evaluating innovative solutions in AI, networking, and cloud technologies.

I hold a Master’s degree in Electrical Engineering from the University of Southern California (USC) and am currently pursuing a Postgraduate Program in Artificial Intelligence and Machine Learning at the University of Texas at Austin, focusing on machine learning, NLP, and deep learning.