To improve the quality of human life with breakthrough research in AI and to comprehensively equip future AI practitioners and scientists.

The RIT Center for Human-aware AI (CHAI) is composed of a transdisciplinary team of AI researchers and students at RIT, who are interested in solving AI's grand challenges.​ CHAI's mission is to:

  1. Conduct transformative research on computing systems capable of tasks that ordinarily require human intelligence or that enable humans to perform optimally;
  2. Work toward the development of AI computing systems that are continually learning, trustworthy, and capable of solving complex tasks with minimal resources.
The center is focused on advancing four synergistic research pillars: brain-inspired computing, human-centered AI, machine learning and perception, and automation. From 2015 - 2017, our group raised over $2 million in external funding, including awards from AFRL, AFOSR, NASA, DARPA, and NSF.

Revisit this website to learn of recent and upcoming CHAI events, or join our mailing list.

Students and potential postdocs interested in joining CHAI should contact individual CHAI faculty members about opportunities.

CHAI's core faculty have been supported by the National Science Foundation, DARPA, US Air Force, AFRL, Department of Energy, NSA, NVIDIA, IBM, Intel, Seagate, Kodak-Alaris, Raytheon, Semiconductor Research Corporation, and more.

See our charter to learn more about CHAI's mission, joining CHAI, and CHAI's organizational structure.

CHAI's Research Pillars

Brain-Inspired Computing

Can our understanding of human neural processing and perception lead to new AI algorithms and hardware advances?

Machine Learning and Perception

How can we extend and transform AI methods to address challenging tasks in understanding natural language, images, video, and multi-modal data?


How can AI technologies lead to new innovations and efficiencies in domains where intelligent systems or robots collaborate in future workplaces?

Human-Centered AI

How can we develop and design usable AI-based cognitive technologies for interacting with human users, including understanding behavior, experiences, and negotiating users’ trust?

Core Faculty

CHAI is composed of scientists at the Rochester Institute of Technology working on artificial intelligence and human-computer interaction.

Andreas Savakis


Computer Vision

Christopher Kanan

Associate Director
Machine Learning & Perception Lead

Deep Learning & Neuromorphic Algorithms

Cecilia Ovesdotter Alm

Human-centered AI Lead

Multimodal Sensing, Natural Language Understanding

Reynold Bailey

Visualization & Multi-modal Data

Travis Desell


Matthew Huenerfauth

Human-Computer Interaction

Raymond Ptucha

Automation & Robotics Co-Lead

Deep Learning & Robotics

Ferat Sahin

Automation & Robotics Co-Lead


Linwei Wang

AI in Health

Qi Yu

Data Mining

Affiliate Faculty

Andres Kwasinski

Cognitive Radios; Networking

Alexander Loui

Computer Vision

Victor Perotti

AI in Business

Advisory Board

Chris Eliasmith

Director, Centre for Theoretical Neuroscience
University of Waterloo

Roni Rosenfeld

Professor and Department Head
Machine Learning Department
Carnegie Mellon University

Amit Gupta

AI Research Lead
Canon Research Australia

Nathan Pendelton

Senior Systems Engineer
Argo AI

Scott Yih

Principal Research Scientist
Allen Institute for AI (AI2)

News & Events