News

Industry awards from Google and Samsung

September 29th, 2021in Award, Funding, News

We are delighted to announce two recent industry gifts CASP Lab received: A 2021 Data Acquisition, Processing and Analysis (DAPA) Award by Google to continue our work on self-managed stream processing systems, understanding the characteristics of streaming state access workloads, and designing workload-aware streaming state stores. A Samsung Memory Solutions... More

Two new PhD students join the group

September 1st, 2021in News

This fall, we welcome two new PhD students to the group: Yuanli Wang and Emmanouil Kritharakis. Yuanli recently graduated with a Master's degree from the University of Minnesota and is interested in all things distributed systems. Emmanouil got his M.Eng Degree in Electrical and Computer Engineering from the Technical University of... More

Hariri FRP Proposal Award

May 28th, 2021in Award, Funding, News

We are delighted to announce that our Focused Research Program Proposal “Continuous Analysis of Mobile Health Data among Medically Vulnerable Populations" has been selected by the Hariri Institute for Computing for an award. The proposal was led by co-PIs Dr. Nicole Spartano, Dr. Lisa Quantiliani, and Dr. Vasiliki Kalavri, and... More

Showan’s work was accepted for presentation at the EuroSys Doctoral Workshop (EuroDW 2021)

March 25th, 2021in News, Research

Showan's submission "Toward Workload-Aware State Management in Streaming Systems" was accepted for presentation at the 15th EuroSys Doctoral Workshop (EuroDW 2021). Here's the abstract: Modern streaming systems rely on persistent KV stores to perform stateful processing on data streams. Although the choice of the state store is crucial for the system’s performance, More

Secrecy: New preprint available

February 2nd, 2021in News, Publication, Research

In out latest work, we study the problem of composing and optimizing relational query plans under secure multi-party computation (MPC). MPC enables mutually distrusting parties to jointly compute arbitrary functions over private data, while preserving data privacy from each other and from external entities. We have released a new preprint on the... More