The University of Pittsburgh ranks among the top universities in the world for its exceptional research strength and academic programs that focus on areas of great societal need and preparing students for productive and meaningful lives.
Research is a major source of external investment in the university, and Pitt research has a substantial economic impact on society and the world. External expenditures for research were $808 million in FY 2018, and Pitt was in the top five in National Institutes of Health funding. The economic impact of Pitt research was $1.7 billion that year. Pitt researchers submitted a new invention disclosure nearly every day of the year. Translating research for world-wide impact, Pitt executed 162 licenses or options, including a record 23 new companies based on Pitt innovations that have the potential to improve life for millions of people.
Pitt Research, led by the Senior Vice Chancellor for Research, is the core unit at the University of Pittsburgh with responsibility to:
- Facilitate research of impact
- Identify and catalyze strategic opportunities
- Position the University to lead large research collaborations
- Translate scholarly excellence into commercial innovation and economic partnership
- Maintain the highest standards of research integrity
The Senior Vice Chancellor for Research provides strategic vision, leadership, and partnership expertise that helps University of Pittsburgh faculty and students advance their world-class research, scholarship, and innovation. Pitt Research couples the research efforts of faculty and students to funding agencies, corporate sponsors, other institutions, and government entities, and assures integrity, compliance, and excellence.
Pitt is committed to expanding human understanding, improving health, spurring innovation and entrepreneurship, and stimulating solutions to the greatest needs of modern society.
Meet the Senior Vice Chancellor
Rob Rutenbar possesses nearly 30 years of experience in innovation and technology. His research focuses on three broad categories: tools for a wide variety of integrated circuit design issues, methods for managing the statistics of nanoscale chip design, and custom computer architectures for perceptual and data analytics problems.