data science

This post describes our midterm work status and some achievements we have done so far in the project for the noWorkflow package. The initial weeks I started doing a bibliographical review on reproducibility in the Data Science (DS) and Machine Learning (ML) realms.

Hello everyone, my name is Jesse and I’m proud to be a fellow in this 2023 Summer of Reproducibility program, contributing to noWorkflow project. My proposal was accepted under the mentorship of João Felipe Pimentel and Juliana Freire and aims to work mapping and testing the capture of the provenance in typical Data Science and Machine Learning experiments.

The Data Storage Research Vision 2025, organized in an NSF workshop, calls for more “AI for storage” research. However, performing ML-for-storage research can be a daunting task for new storage researchers.

PolyPhy is a GPU oriented agent-based system for reconstructing and visualizing optimal transport networks defined over sparse data. Rooted in astronomy and inspired by nature, we have used an early prototype called Polyphorm to reconstruct the Cosmic web structure, but also to discover network-like patterns in natural language data.

AsterixDB is an open source parallel big-data management system. AsterixDB is a well-established Apache project that has beedddn active in research for more than 10 years. It provides a flexible data model that supports modern NoSQL applications with a powerful query processor that can scale to billions of records and terabytes of data.

FasTensor is a parallel execution engine for user-defined functions on multidimensional arrays. The user-defined functions follow the stencil metaphor used for scientific computing and is effective for expressing a wide range of computations for data analyses, including common aggregation operations from database management systems and advanced machine learning pipelines.

FasTensor is a parallel execution engine for user-defined functions on multidimensional arrays. The user-defined functions follow the stencil metaphor used for scientific computing and is effective for expressing a wide range of computations for data analyses, including common aggregation operations from database management systems and advanced machine learning pipelines.

Polyphorm is an agent-based system for reconstructing and visualizing optimal transport networks defined over sparse data. Rooted in astronomy and inspired by nature, we have used Polyphorm to reconstruct the Cosmic web structure, but also to discover network-like patterns in natural language data.

DirtViz is a project to visualize data collected from sensors deployed in sensor networks. We have deployed a number of sensors measuring qualities like soil moisture, temperature, current and voltage in outdoor settings.