News

  • May 1, 2020

    student wearing sunglasses highlights paper under colorful light.

    First-year students develop imaging system to study historical artifacts

    A multidisciplinary team of first-year students has been working to develop an imaging system that can reveal information hidden in historical documents for their Innovative Freshmen Experience project-based course. But with the shift to remote classes, the students left campus with the device nearly complete. Although disappointed, they shifted focus to the opportunities the new situation would create.

  • April 24, 2020

    Student to Student: NUDIX hydrolase enzymes

    After transferring to RIT, Kevin DiMagno became a biochemistry major to prepare for medical school after graduation. In this student spotlight, he talks about his interest in characterizing the function of NUDIX hydrolases enzymes and the focus of his research.

  • April 24, 2020

    cattle in pasture

    Essential pandemic partners

    Learn how environmental scientists combine their love of nature with cutting-edge research to help understand the origins of infection.

  • April 23, 2020

    researcher pointing at equations on dry-erase board.

    Fixing the forgetting problem in artificial neural networks

    An RIT scientist has been tapped by the National Science Foundation to solve a fundamental problem that plagues artificial neural networks. Christopher Kanan, an assistant professor in the Chester F. Carlson Center for Imaging Science, received $500,000 in funding to create multi-modal brain-inspired algorithms capable of learning immediately without excess forgetting.

  • April 22, 2020

    simulation of the magnetic field lines from a rotating neutron star.

    NSF funds RIT researchers to develop code for astrophysics and gravitational wave calculations

    The National Science Foundation recently awarded researchers at RIT, the University of Illinois at Urbana-Champaign, Louisiana State University, Georgia Tech and West Virginia University grants totaling more than $2.3 million to support further development of the Einstein Toolkit, a community-developed code for simulating the collisions of black holes and neutron stars, as well as supernovas and cosmology.