About the CenTIR > CUBRC Staff

Alan Blatt
Director

As Director of the CenTIR, Mr. Blatt provides both technical and management oversight to its projects. In addition, he holds appointments in the UB School of Engineering and Applied Sciences and the School of Medicine and Biomedical Sciences. For the past 12 years, he has been involved in research projects to reduce crash related injuries and deaths. Mr. Blatt was program manager for the Automated Crash Notification Field Operational Test and was a key contributor to the Alaska EMS Optimization Project, NYC DOT Pedestrian Fatality and Severe Injury Study, and the Minnesota Mayday Program. Mr. Blatt is a member of the Erie County Traffic Safety Advisory Board.

Marie Flanigan, PhD.
Principal Scientist

Dr. Flanigan has performed technical work in both the Aerospace and Transportation arenas for 20 years.  She is currently the lead investigator on a CenTIR project which examines air medical service response to motor vehicle crashes, Automatic Crash Notification (ACN) technologies and access to post-crash trauma care.   She was previously a key contributor on the Alaska Emergency Medical Services Optimization Project (AKEMSO) and is currently actively involved with the  Montana ACN Project.   More recently for the CenTIR project, she has begun investigating advanced technologies for emergency response and rescue in the Y2030.  Dr. Flanigan serves as the technical editor on CenTIR reports and products and is the author of over 50 technical publications. 

Kevin Majka
Research Scientist

Kevin Majka is a GIS analyst and research scientist at CUBRC in Buffalo, NY and key contributor to CenTIR related projects. He holds degrees in environmental design and geography form the State University of New York at Buffalo with specializations in transportation and GIS analysis. Mr. Majka is experienced in geographical analysis, including the development and management of complex geographic information systems, the use of global positioning and remote sensing technologies, spatial pattern recognition, transport and logistics modeling, and using artificial intelligence in solving geographic problems.

Maile Miller
Project Assistant

Maile Miller is a project assistant and web developer at CUBRC in Buffalo, NY. She is also the data manager of the ADAMS database, which contains 300+ air medical services in the United States. She has contributed to various presentations and technical papers.

John Pierowicz
Senior Research Scientist

Mr. Pierowicz is a Senior Research Scientist at the CenTIR with more than 20 years of vehicle research and technical management experience in the areas of systems design, testing, and in-vehicle sensor system deployment. He was the program manager for the Intersection Collision Avoidance (ICA) project and led a number of programs to develop and test in-vehicle sensors for heavy trucks - one of which led to a demonstration of a wireless roadside inspection system for heavy trucks. Mr. Pierowicz is an authority in the use of accident data in the development of collision avoidance systems and has supported FHWA initiatives to identify gaps in Human Factors research for the Intelligent Vehicle Initiative.  He has multiple patents and over 20 published papers in the transportation community.

Mary Russell
Research Scientist

Mary Russell is a research engineer at CUBRC in Buffalo, NY.  She currently has her Master’s degree in mechanical engineering from the State University of New York at Buffalo with a concentration in biomechanics. Ms. Russell is applying her biomechanics expertise to studying the mechanisms of injury experienced by truck occupants in heavy truck crashes in an effort to identify meaningful, data-driven ways to improve cab safety.  Ms. Russell has also studied the efficacy of valgus unloader bracing for persons with medial knee osteoarthritis through kinematic, kinetic and Electromyographic analysis.  The goals of her research were to better understand the degree to which these unloader braces mediate pain relief by controlling instability, influencing knee adduction moments, and muscle co-contraction while utilizing real-time tracking of human movement.