Office: E2-381
2138423063
obel «at» ucsc·edu
Website
Oceane Bel
Google Scholar link: Oceane's Google Scholar Page
Oceane is a Ph.D. student in CRSS/SSRC who started in Fall 2016. Her current interest lies in machine learning applied to systems. She previously worked on CAPES: A Computer Automated Performance Enhancement System and Inkpack: Drive theft resistant system with Kenneth Chang, Professor Miller and Professor Long.
Current Research
Now she is working on Geomancy: Automated Performance Enhancement through Data Placement Optimization which will serve as part of her thesis. She developed Geomancy, a tool that automatically optimizes the placement of data within a distributed storage system by leveraging a neural network architecture that accurately forecasts future performance-based access metrics.
Past education:
She did her undergraduate at USC, majoring in computer engineering and computer science. During her undergraduate career she conducted research with Stanford on how to use robotics to teach computer science to k-12 students. Additionally she conducted research on smart watches and voice recognition with USC.
Publications
| Date | Publication | |
|---|---|---|
| Jun 4, 2018 |
Oceane Bel,
Kenneth Chang,
Daniel Bittman,
Hiroshi Isozaki,
Darrell D. E. Long,
Ethan L. Miller,
Inkpack: A Secure, Data-Exposure Resistant Storage System,Proceedings of the 11th ACM International Systems and Storage Conference (SYSTOR 2018), June 2018. [Secure File and Storage Systems] [Storage Class Memories] |
|
| Nov 13, 2017 |
Yan Li,
Oceane Bel,
Kenneth Chang,
Ethan L. Miller,
Darrell D. E. Long,
CAPES: Unsupervised Storage Performance Tuning Using Neural Network-Based Deep Reinforcement Learning,Supercomputing '17, November 2017. [Scalable High-Performance QoS] [Tracing and Benchmarking] [Ultra-Large Scale Storage] |