I'm a second year Ph.D. student at the University at Buffalo, where I study computer science and, specifically, caching and prefetching on mobile systems, with applications in robotics and computer vision.
Previously, I interned at Google, where I developed a machine learning model to inform prefetching decisions on Chrome. I was also a full time software engineer at edX for a year, where I worked on all the stacks on the "full stack" - from accessible front-end components and CSS-tinkering, to countless management commands and APIs in Python and Django, to devops and system administration for VEDA, edX's video encoding and delivery pipeline.
I graduated from Brandeis University with a degree in computer science in 2017.
Links
Publications
-
Ryan Marcus, Olga Papaemmanouil, Sofiya Semenova, and Solomon Garber. "NashDB: An Economic Approach to
Fragmentation, Replication and Provisioning for Elastic Databases." 37th ACM Special Interest Group in Data
Management 2018. (SIGMOD 2018) pdf
-
Ryan Marcus, Sofiya Semenova, and Olga Papaemmanouil. “A Learning-based Service for Cost and Performance Management
of Cloud Databases (Demonstration).” IEEE International Conference on Data Engineering (ICDE) 2017. (ICDE 2017)
pdf
Workshops
-
Ali J. Ben Ali, Sofiya Semenova, and Karthik Dantu. "Platform Variability in
Edge-Cloud Vision Systems." 20th International Workshop on Mobile Computing
Systems and Applications (HotMobile 2019). pdf
Projects
- Brandeis senior thesis: “Clouds That Think: Applications of Machine Learning Techniques for Elastic Databases". pdf
-
Edge-Assisted Trackerless Augmented Reality pdf
-
For more, see the projects page of this website.
(Thanks Ryan! 🙄)