Department of Statistics Unitmark
Dietrich College of Humanities and Social Sciences

After graduating with an undergraduate math major and completing his mandatory military service, Carnegie Mellon Statistics alumnus Mario Peruggia (Ph.D. 90) spent several months at a research institute in Milan, Italy.  Under the guidance of his undergraduate advisor, Bruno Betrò, and sitting in on a course taught at the University of Milan by Eugenio Regazzini, he became more and more interested in statistical theory and applications.

 

“It was around that time that I applied for a fellowship of the Italian National Council of Researches to visit the Statistics Department at Carnegie Mellon.  The fellowship application required an invitation from a researcher at a foreign institution, and that researcher was Prof. Bill Eddy, who had visited Bruno in Milan and stayed in touch with him.

 

“Having been granted a fellowship for six months, I landed in Pittsburgh in August of 1985 thinking that I would return to Italy at the end of the academic year.  Clearly things turned out a little differently!

 

“In those years computing was rapidly evolving and those changes were to have an enormous impact on how people did statistics, both in the way they formulated problems and in the way they carried out the analysis of data. 

 

“The Statistics Department at Carnegie Mellon was a leader in the field of statistical computing, with state-of-the-art facilities and an instructional curriculum that took full advantage of those facilities and taught us the principles of modern, interactive data analysis.  That, paired with a rigorous theoretical training, helped me tremendously in my professional development. 

 

“Of course, there is no single reason why an academic department succeeds, and many people have made outstanding contributions throughout the years, but I think that Bill’s keen insight on how to extract information from data, his understanding of the importance of computing for modern statistics, and his efforts to equip the department with outstanding computing facilities, including a video lab for dynamic visualization of data, were all very instrumental in establishing the department as a leader in the discipline,” he said.

 

Today, as a Professor of Statistics at Ohio State University, Mario teaches while also engaging in statistical research.

 

“In a way, an academic job gives me the opportunity to be a graduate student for life, just with less hair on my head and a slightly higher income.  I like the challenges that come with the job and the freedom that I have to choose what problems to work on and what research directions to pursue.  I also think that the constant interaction with younger generations of students helps to keep my thinking fresh and my mind engaged. 

 

“My wife, Amy Ferketich, is also a professor at OSU, where she teaches epidemiology in the College of Public Health.  Her main area of research is tobacco control and smoking cessation, and she can take credit for my kicking the habit.

 

“Her strategy was negative reinforcement, by having me set up a smoking lounge in the dingy basement of our first apartment, next to the trash can.  We keep our academic lives separate, which helps us to better enjoy the time we spend together, often in the company of our two cats, Curly and Moe.  We take occasional road trips to Pittsburgh to catch an opera performance or a Pirates game.

 

“Not having paid enough attention to odds calculations in my probability classes, or possibly because of my warped personal utility, I play the lottery twice a week.  Quite naturally, because of that, my future goals are conditional.  If I don’t win, I will keep teaching and doing statistical research for the foreseeable future.  But if I win…  Well, that’s my little secret!” he said.

 

Bill Eddy said Mario has another secret:  three years after graduating with his Ph.D., Mario published the book, Discrete Iterated Function Systems, which is based on his dissertation.

 

In it, he explores the connections and disparities of continuous and discrete Iterated Function Systems (IFS), and illustrates some surprising implications of his discretization method.

 

The book also includes a discussion on how IFS techniques can be applied to produce animated motion pictures.

 

Bill keeps a copy on his bookshelf.