Brown Technology Innovations has published its first Quarterly Newsletter for fiscal year 2024.

Brown Technology Innovations has published its 2023 Annual Report.

Mathematics and engineering professor George Karniadakis was noted as a machine learning expert to follow by Digilab Academy based on his groundbreaking work in Physics-Informed Neural Networks (PINNs).

Pedialydx’s technology was utilized in a recent study that analyzed premature infants’ cries for acoustic features that may predict future behavioral and developmental deficits.

Professor Nitin Padture was elected to the Materials Research Society (MRS) 2023 Fellows Class for his research in advanced composites, high-temperature coatings, and emerging photovoltaics. Padture has been awarded eight patents in his career.

Brown faculty, students, post-docs, and staff will attend the American Association for Cancer Research (AACR) meeting in Orlando, FL this month. Investigators from the Legorreta Cancer Center will present work across many areas of cancer research.

Researchers from the Institute at Brown for Environment and Society (IBES) and the School of Engineering met with senior leaders from FM Global to discuss climate change and risk management in relation to the insurance industry, with a focus on climate science, technology, policy, and solutions.

Want to embark on a Medical Device or Digital Health entrepreneurship journey? Our partners at NEMIC just launched the NEMIC Virtual Classroom. Learn where you want, when you want!

The Engine is seeking applications from aspiring entrepreneurial scientists and engineers for their Spring 2023 Blueprint program. The program website contains additional information and a section to apply by Friday, March 17.

PedialyDX, recently secured a $1.8M SBIR Phase 2 grant from NICHD, and an Exclusive License Agreement with Brown, that will allow them to conduct a 7-site study to conduct further research on their NOWS recognition device.

Brown Innovation Fellow Josephine Kalshoven’s story “Connected Player” has been published in Nature Futures, the publication’s award-winning science fiction section.

Dr. Srivastava and colleagues are developing a new machine learning technology that utilizes convolutional neural networks (CNN) to analyze ultrasound wave patterns in metal pipelines to locate cracks and prevent catastrophic events like gas explosions.

Dr. Laiwalla has been accepted to the 2023 MedTech cohort of the 6-month Equalize Program, pairing women academic researchers with mentors in entrepreneurship across therapeutics, medical technologies, physical sciences, and digital tools sectors.

A patent was recently awarded to Dr. Sherief Reda’s lab in the School of Engineering for new technology in deep neural networks.

Neil Veloso and Brian Demers were featured in the January 2023 University-Industry Engagement Advisor discussing technology scouting, startups, and industry-academic partnerships and commercialization timelines.