I'm a third year Ph.D. student at the University at Buffalo, where I study computer science and, specifically, mobile and edge systems for robotics and computer vision applications.
In the summer of 2019, I interned at Google, where I developed a machine learning model to inform prefetching decisions on Chrome to decrease in user-perceived page load latency. Before starting the Ph.D. program, I was a software engineer at edX for a year, where I worked on all the layers of the "full stack" - from creating an entirely accessible essay-writing module in Javascript for keyboard-only users, to countless management commands and APIs in Python and Django, to running and analyzing A/B tests with Optimizely, 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
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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
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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
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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
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A Rust Implementation of Raft, a Distributed Consensus Algorithm GitHub
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Visual Question Answering survey pdf
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Edge-Assisted Trackerless Augmented Reality pdf
- Brandeis senior thesis: “Clouds That Think: Applications of Machine Learning Techniques for Elastic Databases". pdf
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For older projects, see the projects page of this website.