About me

Welcome to my website!

Update: I have joined AT&T as a Lead Inventive Scientist.

I completed my PhD at Yale, with a focus on the intersection of machine learning methods and next-generation networked systems.

Recently, I have been working on distributed learning in communication networks, focusing on LLM training, fine-tuning, and personalization. The goals of these projects include enhancing privacy protection, improving energy efficiency, and optimizing model performance. I also work on optimization and machine learning for 5G and beyond cellular networks, and wireless SDN architecture.

I am broadly interested in exploring how different deep learning methods, including supervised and reinforcement learning approaches, could be leveraged to optimize the efficiency of the communication networks of the near future. And I am also interested in how such communication infrastructures can be harnessed to realize efficient deployment of deep learning architectures (for learning and inference tasks).

My experience spans different network paradigms including 5G and beyond cellular network, software defined networking, network function virtualization, time sensitive network, segment routing, p4, and more. And I am also experienced with a wide range of deep learning, reinforcement learning, and other machine learning approaches. I have worked on different testbed deployments for realistic measurements, including as a part of my PhD work and during internships.

For further details on my efforts and accomplishments, please explore my website, Linkedin profile, or the resume.