Jason Kolodziej
Associate Professor
Jason Kolodziej
Associate Professor
Education
BS, MS, Ph.D., State University of New York at Buffalo
Bio
Dr. Jason Kolodziej is an Associate Professor of Mechanical Engineering at the Rochester Institute of Technology (RIT). He received his BS, MS, and Ph.D. in mechanical engineering from SUNY at Buffalo. His research focus was primarily in controls and nonlinear system identification for parameter and state estimation from measurement data using a statistical variance approach.
For eight years Dr. Kolodziej worked in industry for General Motors Fuel Cell Activities as a Sr. Research Engineer with his principle duties in hybrid electric-fuel cell vehicle powertrain controls and system architecture. To date he has applied for, or has been granted, 15 U.S. Patents related to fuel cell vehicle systems mainly as the principle investigator.
Dr. Kolodziej’s research plan is to utilize his research experience in online system analysis, measurement, and control, to continue the study of fault detection, diagnosis, and prognostic health assessment of engineering systems. He currently has projects covering a wide range of industrial applications from: electromechanical actuators for aircraft applications to fuel cell automotive powertrains to large scale reciprocating compressors to implantable ventricular heart pumps.
He has more than ten years’ experience as a part-time and full faculty member teaching at the undergraduate and graduate level including mentoring more than 34 multidisciplinary senior design teams.
Select Scholarship
Currently Teaching
In the News
-
June 3, 2024
Engineering faculty and cardiologist collaborate to design heart pump assessment prototype
Researchers at RIT are developing technology that will be able to determine the lifespan of a heart valve with more precision.
-
October 24, 2018
Researchers improve upon stethoscope design
Researchers at RIT and URMC developed a new digital stethoscope that combines precision sensors, electrocardiogram technology and machine learning applications into one piece of equipment to better detect heart ailments and problems that might occur with an implanted heart pump.