Aditya Dhakal

I have received my M.S. degree in Computer Science from University of Connecticut, Storrs, Connecticut (2014) and B.E. degree from Kyushu Institute of Technology, Iizuka, Japan. Currently, I am pursuing my Ph.D. degree at Department of Computer Science and Engineering, University of California, Riverside. My academic advisor is Professor K. K. Ramakrishnan.

Research Interest

• Deep Neural Network Inference
• Edge Cloud Services
• GPU
• Network Function Virtualization
• Userspace Networking
• Machine Learning

Contact Info

Publications

• Dhakal, Aditya, Kulkarni, Sameer, and K. K. Ramakrishnan. "ECML: Improving Efficiency of Machine Learning in Edge Clouds." IEEE International Conference on Cloud Networking (CloudNet 2020). Awarded Best Student Paper Award


• Dhakal, Aditya, Kulkarni, Sameer, and K. K. Ramakrishnan. "GSLICE: Controlled Spatial Sharing of GPUs for a Scalable Inference Platform." Proceedings of the ACM Symposium on Cloud Computing (SOCC 2020). Paper


• Dhakal, Aditya, Kulkarni, Sameer, and K. K. Ramakrishnan. "Machine Learning at the Edge: Efficient Utilization of Limited CPU/GPU Resources by Multiplexing" AI towards Mission-Critical Communications and Computing at the Edge (AIMCOM2) workshop in ICNP 2020.


• Dhakal, Aditya, and K. K. Ramakrishnan. "NetML: An NFV Platform with Efficient Support for Machine Learning Applications." 2019 IEEE Conference on Network Softwarization (NetSoft 2019). Paper


• Dhakal, Aditya, and K. K. Ramakrishnan. "Machine learning at the network edge for automated home intrusion monitoring." 2017, IEEE ICNP Workshop on Machine Learning and Artificial Intelligence in Computer Networks (ML&AI @ Network 2017).

Links

• UCR CSE Networks Lab
• UCR CSE
• UC Riverside