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.
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)
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
- 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.