Conor Flynn
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Interests
Conor Flynn has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Aaron Green
Rensselaer Polytechnic Institute
1 shared publication - John S. Erickson
Rensselaer Polytechnic Institute
1 shared publication - Kristin P. Bennett
Rensselaer Polytechnic Institute, Troy, USA
1 shared publication - Oshani Seneviratne
Rensselaer Polytechnic Institute, Troy, NY, USA
1 shared publication
Latest Publications
- Open Access
Enabling Cross-Language Data Integration and Scalable Analytics in Decentralized Finance
With the agile development process of most academic and corporate entities, designing a robust computational back-end system that can support their ever-changing data needs is a constantly evolving challenge. We propose the implementation of a data and language-agnostic system design that handles different data schemes and sources while subsequently providing researchers and developers a way to connect to it that is supported by a vast majority of programming languages. To validate the efficacy of a system with this proposed architecture, we integrate various data sources throughout the decentralized finance (DeFi) space, specifically from DeFi lending protocols, retrieving tens of millions of data points to perform analytics through this system. We then access and process the retrieved data through several different programming languages (R-Lang, Python, and Java). Finally, we analyze the performance of the proposed architecture in relation to other high-performance systems and explore how this system performs under a high computational load.
Open AccessEnabling Cross-Language Data Integration and Scalable Analytics in Decentralized Finance
With the agile development process of most academic and corporate entities, designing a robust computational back-end system that can support their ever-changing data needs is a constantly evolving challenge. We propose the implementation of a data and language-agnostic system design that handles different data schemes and sources while subsequently providing researchers and developers a way to connect to it that is supported by a vast majority of programming languages. To validate the efficacy of a system with this proposed architecture, we integrate various data sources throughout the decentralized finance (DeFi) space, specifically from DeFi lending protocols, retrieving tens of millions of data points to perform analytics through this system. We then access and process the retrieved data through several different programming languages (R-Lang, Python, and Java). Finally, we analyze the performance of the proposed architecture in relation to other high-performance systems and explore how this system performs under a high computational load.