Sofiya is ...

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

    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

    A Rust Implementation of Raft, a Distributed Consensus Algorithm GitHub
    Visual Question Answering survey pdf
    Edge-Assisted Trackerless Augmented Reality pdf
    Brandeis senior thesis: “Clouds That Think: Applications of Machine Learning Techniques for Elastic Databases". pdf
    For older projects, see the projects page of this website.
(Thanks Ryan! 🙄)