Postdoc Profile – Kenny Lopiano

Kenny outside of SAMSI

Kenny Lopiano at SAMSI, Fall 2012.

Kenny Lopiano, postdoctorate fellow at SAMSI in the Data-Driven Decisions in Healthcare program, grew up in Jacksonville, Florida, then moved to Ponte Vedra, just east of Jacksonville, when he was about 12-years-old. Kenny attended Allen D. Nease High School, which actually offered statistics classes. Kenny took an AP statistics course as a junior in high school. Since the statistics classes were new in the curriculum, his teacher, Penny Futch, was learning the material along with the students. As a result, Kenny supplemented the in class work with his own independent study of the material . His calculus teacher, Della Caldwell, was married to Bill Caldwell who taught at University of North Florida. Dr. Caldwell came to the high school and taught a linear algebra class, which is usually considered a 3rd year college course. In his spare time, Kenny was active in many sports, including wrestling and football.

Kenny is a big Gator fan!

Kenny is a big Gator fan!

By the time Kenny graduated high school and applied to the University of Florida in Gainesville, he had placed out of the introductory courses, and decided to double major in math and statistics. His first semester he was already taking regression analysis and calculus 3. One of his professors, Yongsung Joo, mentored Kenny and spent time teaching him SAS, which was incredibly helpful to Kenny.

“I spent my first summer working at the Fresh Market in the produce department,” said Kenny, “That job taught me a lot about work ethic. Many times I worked 50-hour work weeks.” He had actually interviewed for a job at Blue Cross Blue Shield for a summer internship, but had only been on campus for two months when the recruiters came to campus, so the interviewer immediately said to him, “You know you are not going to get this job, right?” and Kenny said, “Yes, I know I only have my high school credentials to go on.” He just wanted to get some experience interviewing.

His second summer, though, he applied for an internship at the Mayo Clinic in Rochester, MN after Googling for statistics internships. He was lucky enough to get a phone interview and ultimately the job. He worked with the biostatistics department and saw how various people with statistics degrees worked at the Mayo Clinic. Those with undergraduate degrees had certain job responsibilities, while those with a Master’s degree had other responsibilities and those with a Ph.D. degree had even more responsibilities and freedoms to do things, so it was during this summer working primarily with Dirk Larson and Nancy Diehl he decided he wanted to get a Ph.D.

When he returned for his junior year, he could have gotten a minor in actuarial science, or start working on his master’s program, so he started working on his Master’s program. He immediately saw the difference in the way statistics was handled in graduate level courses. For example, a class he took in regression and design was completely different from the way he had learned it in his undergraduate class and he quickly found out he had to learn the subject from a very different perspective.

At the end of his junior year, he applied again to Blue Cross Blue Shield and the same recruiter interviewed him, but this time he got the job! He spent the summer working with Ryan Little who taught him how to map pharmacy records to risk groups. This helps underwriters to set rates for different groups.

Kenny and Nate at graduation

Graduation with his friend, Nate Holt.

He successfully completed his first year exam for his Master’s degree and when he came back for his second year (his fourth year at UF), he had a different attitude. He had broken off a serious relationship and was playing rugby and was not dedicating as much time to his studies as he admittedly should have. His professors tried to warn him to get more serious before he took his second qualifying exam, which meant either you passed and moved on to work with your advisory team, or you failed and either left the program or would work hard to try again. Eight people took the exam, half passed and half failed. Kenny was one of the people who had failed the exam. He was perplexed. Dr. Brett Presnell, the department chair, wrote him a letter and said if he worked on certain things, he would probably pass. At first, Kenny was mad and crumbled up the letter, but then he got it back out and read the comments each professor had made, then met with each one to find out what he could do better. It was a wakeup call for him. “That letter is now framed and hanging in my home office,” Kenny remarked. When he retook the exam, he passed with flying colors.

with Igert cohorts

Kenny with his Igert cohorts.

Kenny was accepted as a graduate fellow for the newly formed NSF IGERT, the Quantitative Spatial Ecology, Evolution, and Environment (QSE3). The IGERT was really transformative for him because he got to work in an environment that was very multi-disciplinary, which he really enjoyed. He was also working with Mary Christman (who was involved with the IGERT) on a project working on generalized additive models. Dr. Christman thought that Kenny’s research and experience would be of interest to Linda Young, so she introduced Kenny to Dr. Young. Young told Kenny about an opportunity that would be happening that summer at the National Institute of Statistical Sciences (NISS) in RTP in conjunction with the National Agricultural Statistics Service (NASS) in Washington DC. Kenny thought about it and decided it would be a good experience, so he spent the summer of 2009 at NISS and the summer of 2010 at NASS working on a team that was made of all female statisticians. He noted that all along his career path, he has been fortunate to have many female mentors.

Kenny sitting at desk working

Kenny working at NISS in the summer of 2009

The work Kenny has been doing here at SAMSI involves working with people in operations research, which is again giving him exposure to different perspectives and having a chance to collaborate with people from other disciplines, which he really enjoys. The patient flow working group has also interacted with doctors and nurses that have been working with the University of North Carolina’s triage and trying to identify finer subgroups. The emergency severity index (ESI) currently goes from 1-5, where a “1” is a critical patient needing immediate care, to a “5” which is the least urgent. The problem of subgroup mainly lies in patients with a “3” which means they are not critical, but need many resources to treat the person.   In addition, Kenny is working with another group of statisticians on methods related to identifying effective treatments using large observational databases.

Next year, Kenny will spend the year mainly at Duke University and work with Alan Gelfand. He will also follow up on the work started with the Data-Driven Decisions in Healthcare program.

Postdoc Profile – David Lawlor

David in Berlin around the time he was working at CERN.

David in Berlin around the time he was working at CERN.

David Lawlor always knew he would end up in some kind of STEM career. His mother works for IBM, his father is a lecturer at the University of Vermont, and his brother is a chemical engineer. His older brother, Patrick, is a chemical engineer working for Conoco Phillips near St. Louis. David grew up in Vermont, where he played ice hockey through high school. His mild demeanor would never reveal that he was a two-time state champion defense man! He’s also a big fan of the hockey team from the University of Vermont.

David grew up playing hockey.

David grew up playing hockey.

(L-R) David's father, Jack, his brother, Patrick, David and his grandfather, Bill.

(L-R) David’s father, his brother, David and his grandfather when David was graduating from the University of Chicago.

David went to college at the University of Chicago and double majored in Mathematics and Physics. During his senior year, he made math his primary major with the intention of becoming a math teacher. After applying to several positions and interviewing at a boarding school he realized that the emphasis was more often on discipline than on instruction, which was not where he wanted to spend his energy. Around the same time, one of his physics professors emailed him to advertise a position in the Physics department. The professor was a primary investigator (PI) on a the ATLAS tile calorimeter, a subdetector project for CERN (the European Organization for Nuclear Research), the organization that operates the Large Hadron Collider. At that time they were assembling the detectors underground and needed some people to help commission the detector and write some computer code. David was accepted for the job, and three weeks after graduating he moved to Geneva, where he lived for a year.  When he first arrived, he worked mainly on the detector in the experimental cavern, but after a few weeks he broke his arm in a bicycle accident. As a result, instead of working on the physical part of the project, he taught himself how to write computer code and learned how to use Linux, python, C++, and ROOT (a data analysis package for high-energy physics.) There were massive amounts of data being generated by the computer simulations at CERN which record and visualize explosions of particles that result from the collisions at the accelerator. It was during his time at CERN that David became convinced applied mathematics was really the area he wanted to pursue.


David with his advisor, Andrew Christlieb, at Michigan State University.

After returning to the states, David worked for a small research firm in Michigan funded by SBIR grants while he applied to graduate programs in applied math. He ended up going to Michigan State for his graduate degree, where his thesis dealt with sparse Fourier transform (SFT) algorithms.  The SFT is an algorithm that processes data 10 to 100 times faster than what is possible with the fast Fourier transform (FFT), the previous fastest technique. The SFT searches for an area of the spectrum has significant energy and omits those that are sparse. His research applies not only to this year’s Massive Data program but also the LDHD program next year.

David said he first heard about SAMSI when he was reading a research paper in which SAMSI was acknowledged as hosting a workshop that had initiated the research. He went to the website to find out more about SAMSI and discovered the organization had postdoc positions, to which he applied as he approached graduation. He was excited to move to the area, having access to many experts in the field at nearby universities and at SAMSI itself.

“I really liked going to the opening workshop and the astrostatistics workshop,” said David, “It was great to get to meet so many people from various disciplines and to realize that everyone is interested in the same problems.” David also said he particularly liked hearing Tamas Budavari’s (Johns Hopkins University) presentation on statistical methods in astronomy.

David is involved with two working groups that are currently using data that Budavari provided from the Sloan Digital Sky Survey (SDSS). He said it is really interesting to work with the same data using two very different algorithmic approaches. “I’m very grateful that SAMSI is able to bring together practicing scientists, statisticians, and applied mathematicians to work on problems of mutual interest,” said David.

Next year, David will spend his time in the Math department at Duke, but will also be very involved with the LDHD program at SAMSI.

In addition to being an applied mathematician, David likes to think of himself as a foodie. He is very committed to the farm-to-table concept and is currently getting seafood from Walking Fish, a community supported fishery. He also bought his Thanksgiving turkey from Coon Rock Farm and plans to join a CSA (community supported agriculture program) in the spring.