Photo of Miranda, Fabio

Fabio Miranda

Assistant Professor

Department of Computer Science

Contact

Building & Room:

2032 ERF

Address:

842 W. Taylor St, MC 152, Chicago, IL, 60607

CV Link:

Fabio Miranda

Related Sites:

About

I am interested in developing techniques that allow for the interactive visual analysis of large-scale data, combining methods from visualization, data management, machine learning, and computer graphics. In particular, I focus on how visual data analytics can help address different problems cities face by integrating data on different resolutions and from different sources.

I have worked closely with domain experts from different fields and the outcome of these collaborations included not only research published in visualization, database, and AI venues, but also systems that were made available to experts in academia, industry and government agencies. My work has also received extensive coverage from different media outlets, including The New York Times, The Economist, Architectural Digest, Curbed, among others.

See my website for more details, including open positions and updated list of publications.

Selected Publications

See https://fmiranda.me/publications/ for latest publications.

Publication Aggregators

Notable Honors

2023, IEEE VIS 2023 Best Paper Honorable Mentio, IEEE VIS

2023, SIBGRAPI 2023 Best Paper Honorable Mention, SIBGRAPI

2018, SIGMOD 2018 Best Demonstration Award, SIGMOD

2018, Pearl Brownstein Doctoral Research Award, NYU

Education

Ph.D., Computer Science, New York University, 2018.
M.S., Computer Science, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), 2011.
B.S., Computer Science, Federal University of Minas Gerais (UFMG), 2009.

Research Currently in Progress

  • Visualization of Probability Distributions of Geographical Data
  • Interactive Exploration of Large Image Databases
  • Automatic Assessment of Sidewalk Quality from Street-level Images
  • Urban Navigation in Virtual Reality
  • Interactive Profiling of City Land Use Evolution
  • Visual Data Exploration through User-Steerable Projections
  • Commuting Trip Distribution Modeling using Graph Neural Network