Rensselaer AI and Reasoning Laboratory
Research and development in the RAIR Lab ranges across a number of applied projects, as well as across many of the fundamental questions AI raises (e.g., Are we machines ourselves? If so, what sort of machines?). Everything is to a high degree unified by the fact that the formalisms, tools, techniques, systems, etc. that underlie the lab's R&D are invariably based on reasoning.
Network Science and Technology Center
The Network Science and Technology (NEST) Center is focused on the fundamental research and engineering of natural and technological networks, ranging from social and cognitive networks to computer networks.
Rensselaer-IBM Artificial Intelligence Research Collaboration
The Rensselaer-IBM Artificial Intelligence Research Collaboration (AIRC), a member of the IBM AI Horizons, is dedicated to advancing the science of artificial intelligence and enabling the use of AI and machine learning in research investigations, innovations, and applications of joint interest to both Rensselaer and IBM.
Tom Morgan
Dr. Morgan has spent over forty years doing what is now called data analytics, much of it on big data sets in remote sensing and image analysis. He has conducted data acquisition, processing and analysis research for a variety of public and private organizations in oil and gas exploration, medical imaging, non-destructive testing and radio astronomy.
Health INCITE
The Rensselaer Health Informatics Challenges in Technology Education (INCITE) Pipeline recruits and prepares students at Rensselaer and worldwide to be data scientists in healthcare using early data analytics courses and experiential research projects centered on real-world health challenges.
With the advent of electronic healthcare records (EHR) and precision medicine, healthcare increasingly relies on health informatics (HI), the philosophy and tools of data science (DS) and their application in healthcare. Rensselaer Health INCITE is a innovative, replicable program that directly expands the health informatics workforce pipeline at the early undergraduate level for students at RPI and worldwide.
SCALES
This project addresses the challenge of agent driven smart contracts on the blockchain with semantics, advances in machine learning, and state of the art in multi agent systems research.