RNET has recently been awarded a NASA Phase I STTR to develop lightweight Neural network models to identify, track, and aggregate lightning event data onboard satellite platforms.
RNET has recently been awarded a NASA Phase II SBIR to develop a Rapid Data Analytics Platform using machine learning uses a novel dimensional reduction algorithm.
RNET has recently been awarded a Department of Energy Phase II SBIR to develop a Machine Learning Based Data Compression (MLDC) algorithm for numeric simulation data.
RNET has recently been awarded an NIH Phase II SBIR to design and develop Machine Learning tools to help Pathologists overcome the limitations of current computing hardware to design more accurate deep learning models for use in clinical diagnostics. These models will be able to analyze very large digitized images of glass slides (i.e., Whole Slide Images) to aid pathologists in tasks like cancer detection. The ability to analyze these images in their entirety instead of in small parts will improve the diagnostic accuracy of models and will accelerate algorithm development efforts.
5335 Far Hills Avenue
Suite 315
Dayton, OH 45429
(937) 433-2886
RNET Technologies is a Computer Science and Engineering firm located in Dayton, OH. We focus on research and development of advanced HPC software for Linux, Unix, Windows, and Embedded Systems. We specialize in the optimization of large scale numerical simulations, machine learning, and graph analytics codes for emerging high performance compute architectures and future exascale systems (including multi-core, many-core, and GPU based platforms) and the development of tools to improve the usability of these codes and systems. In order to address large scale computer science problems, we routinely collaborate with government laboratories, university researchers, and prime contractors. Our mission is to develop leading edge software products for our customers (Department of Energy, Air Force, DARPA, MDA, Navy, NASA, prime contractors and other commercial customers) that enables improved usage of large scale High Performance Computing systems.
Please contact us, we want to talk to you! We are always open to new projects and collaboration opportunities.