Aditya Dhakal

I have graduated with Ph.D. in 2022 and I am working in Hewlett Packard Labs at Milpitas, CA.


Ph.D., Computer Science

University of California, Riverside

I completed my Ph.D. in 2022 and I am currently working in Hewlett Packard Labs. I was a Ph.D. candidate at Department of Computer Science and Engineering, University of California, Riverside. My research focused on effective use of GPU in supporting different kind of Machine learning (ML) and Deep Neural Network (DNN) applications in network setting. My Ph.D. advisor is Professor K. K. Ramakrishnan.

Education

University of California, Riverside

Ph.D.
Computer Science
Department of Computer Science and Engineering
2015 - 2022

University of Connecticut

Masters of Science
Computer Science
Computer Science and Engineering Department
2013 - 2014


Kyushu Institute of Technology (Japan)

Bachelor of Engineering
System Design and Informatics
2009 - 2013

Work Experience

Hewlett Packard Labs

Milpitas, CA, US

Research scientist at Hewlett Packard Labs.

2022-Present

Futurewei Technologies

Santa Clara, US

Summer internship at Futurewei technologies.

2019

Hewlett Packard Enterprise

Palo Alto, US

Summer internship at Hewlett Packard Enterprise.

2016

Publications

  • Dhakal, Aditya, Kulkarni, Sameer, and K. K. Ramakrishnan. "Primitives Enhancing GPU Runtime Support for Improved DNN Performance", IEEE International Conference on Cloud Computing (CLOUD 2021). Awarded Special 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).

  • 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. "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).

  • 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).

    • Awards & Honours

    • Dean's Distinguished Fellowship, 2015-2016 UC Riverside
    • Japanese Ministry of Education (Monbukagakusho) scholarship, 2008-2013