I study deep learning from a computational perspective, with a focus on optimizing memory, computation, and energy efficiency in resource-constrained environments. I investigate how these models can be deployed as secure services, enabling efficient inference without exposing sensitive model parameters. As AI continues to scale rapidly, conventional computing architectures are becoming increasingly unsustainable, making energy-efficient and private AI a central challenge for next-generation intelligent systems.

Research Interests:

• AI on the Edge
• Private AI
• Energy-Efficient AI

I am looking for motivated PhD student. Applicants demonstrating strong research interest will be given preference.