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.
- Deep Neural Network Inference
- Edge Cloud Services
- Network Function Virtualization
- Userspace Networking
- Machine Learning
aditya.dhakal [at] email [dot] ucr [dot] edu
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).