Sofiya is ...

I'm a second 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.

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) pdf


    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


    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 more, see the projects page of this website.
(Thanks Ryan! 🙄)