When you first meet venture capitalist Fred Warren (ME’60, WG’61), two things become immediately apparent: He excels in the art of good conversation, and his inquisitiveness about the world underpins his passion for Penn Engineering and in discovering the next great innovation. “I have an unrequited curiosity about most things. I enjoy learning and having deep conversations with smart people, particularly about technology,” he says. Warren has devoted more than 30 years to the oversight of both the University (as a member of the Board of Trustees) and Penn Engineering (as an Overseer). He and his wife Robin are also founding donors of the Warren Center for Network and Data Sciences (warrencenter.upenn.edu), Penn Engineering’s incubator of forward-thinking, collaborative research that is shaping how network science improves many aspects of life.
How does your education meld with being a venture capitalist?
My Penn Engineering education enabled me to understand the aspects and importance of innovation, while my Wharton MBA gave me the ability to understand markets and the economic upside of technology. Those skills have served me well in venture capital investing.
What inspired you to establish the Warren Center?
The impetus to be the founding donor and continued supporter of the Warren Center is the energy Michael Kearns, National Center Professor of Management & Technology in Computer and Information Science, brings to the table. I was so impressed with his NETS engineering program for undergraduates that I asked him what else he wanted to do in this area. When he answered that he wanted to build a graduate center, I said, “Let’s do it.”
What fascinates you about the research underway at the Warren Center?
It’s where some of the most compelling research in machine learning is being done — and being done better than anywhere else. How could this research impact venture capitalism? As a venture capitalist, I’m concerned with privacy — who has access to what data. I’m also concerned with getting the most accurate information to make good investment decisions. But the massive amount of data that must be sifted through can hamper that process. Machine learning can help us better quantify the sensitivity of data to enhance a global data privacy framework, as well as achieve faster and more accurate analysis of complex data.
What underscores your commitment to Penn Engineering?
I am personally compelled to give back to Penn, which has contributed greatly to my success. I was honored to be part of the Board of Trustees and proud of our accomplishments. Now, as an Overseer, it’s exciting to help secure the future of Penn Engineering in a world where technology and education are rapidly changing.