Miro Mannino

Research Assistant Affiliation: NYU Abu Dhabi
Education: User Interfaces; Database Systems

Research Areas: User Interfaces; Database Systems

Miro Mannino is a Research Assistant for the Prof. Azza Abouzied. His research work focuses on designing intuitive data querying tools.

Miro's major contributions currently are:

  • Qetch: a tool that allows users to freely sketch patterns on a scale-less canvas to query time series data without specifying query length or amplitude. Qetch won the Best Paper Award during the SIGCHI'18 conference.
  • sPaQL Tools: a Stochastic Package Query Interface for Scalable Constrained Optimization. This project won Best Demo Award during the VLDB’20 conference.
  • EpiPolicy: a population-based epidemic simulator and policy aid that allows users to customize its compartmental model to capture different epidemic scenarios for epidemics like COVID-19.
  • Synner: a tool that helps users generate real-looking synthetic data by visually and declaratively specifying the properties of the dataset such as each field’s statistical distribution, its domain, and its relationship to other fields.
  • Texture: a framework for data extraction over print documents that allows end-users to construct data extraction rules over an inferred document structure.

In his spare time Miro is actively involved on small personal projects, and participated as part-time teaching assistant for the Database System course.