As the volume of available information expands, the fraction a person is able to absorb shrinks. To break this cycle, computer scientists say we need new algorithms that prioritize a broader view over fulfilling consumer biases.

In the spring 2020 semester, more than 2,000 students and 242 professors, teaching assistants and mentors relied on Submitty, the open-source tool designed and built by students, faculty, and teaching assistants at Rensselaer Polytechnic Institute.

From a variety of locations in the Capital Region, and throughout the country, Rensselaer Polytechnic Institute faculty, students, and staff are pressing their knowledge and machinery to work making personal protective equipment for those on the front lines of the pandemic.

Rensselaer Polytechnic Institute researcher Malik Magdon-Ismail tailored the robust machine learning models he is developing for the COVID pandemic to work with sparse data points, like those available during the early phase in a pandemic or in smaller cities, which ordinarily make trend-spotting difficult.

Using daily updated data, COVIDMinder, a new data visualization tool, examines how and why COVID-19 impacts regions differently by comparing community risks, mediation tools, and outcomes related to COVID-19 by state across the United States, and by county within New York state.

The U.S. Department of Health and Human Services Agency for Healthcare Research and Quality has awarded a Rensselaer Polytechnic Institute team $15,000 for an app called MortalityMinder, which identifies social conditions contributing to declining life expectancy at a community level.

Deborah McGuinness, the Tetherless World Senior Constellation Chair at Rensselaer Polytechnic Institute, will provide insights into Artificial Intelligence alongside other leading experts during an upcoming public panel discussion titled “A.I. The Future of Climate, Clean Energy and Cybersecurity in the Capital Region.”

A promising semiconductor material could be improved if flaws previously thought irrelevant to performance are reduced, according to research published today in Nature Communications.

An app created by Rensselaer Polytechnic Institute students that identifies social conditions contributing to declining life expectancy at a community level is a Phase 1 winner in a data visualization competition sponsored by the U.S. Department of Health and Human Services.

In partnership with local health insurer, CDPHP, researchers from the Institute for Data Exploration and Applications (IDEA) at Rensselaer Polytechnic Institute are using artificial intelligence to improve patient health by developing a better understanding of high needs patients and identifying aspects of care that lead to better outcomes.