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.

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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.

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Exploring the Impacts of Climate Change on Social and Political Stresses

The following was written by Richard Smith, Director of SAMSI.

Richard Smith

Richard Smith, Director of SAMSI.

What is it like to work on a committee of the National Research Council (NRC), especially if it’s on a topic that has the potential to make headlines? I had the chance to find out recently when I was asked to serve on the committee that produced the report Climate and Social Stress: Implications for Security Analysis (http://www.nap.edu/openbook.php?record_id=14682&page=1). Although the committee members and NRC staff were careful not to overplay the conclusions, the implications – that climate change could become a trigger for civil unrest and even war – were sure to attract attention.

It wasn’t the first time I had served on an NRC committee – some years ago, I served on a committee charged with reviewing one of the reports of the US government’s Climate Change Science Program. But that was very much an under-the-radar report, reviewing somebody else’s document rather than coming up with original conclusions of our own. This one was likely to be different.

The committee itself was a diverse group, including a former chairman of the National Intelligence Council and the former national security adviser to Vice President Al Gore, but was mostly composed of academics, including a number of social and political scientists, three climatologists, a decision science expert from RAND, and one statistician (me). The climatologists included two people I already knew well – Dave Easterling from the National Climatic Data Center (NCDC) in Asheville, and Otis Brown, Director of NC State’s Cooperative Institute for Climate and Satellites (also based at NCDC). Holding everything together was the study director, Paul Stern of the NRC. Paul did an amazing job of coordinating the entire activity, keeping everything on time and, I suspect, writing a considerable part of the actual text of the report.

There were four meetings of the committee, three at the National Academies main building in Washington and the fourth on the campus at Stanford (to even up, at least a little, the travel requirements on the east and west coasters). Each of the meetings was divided into private and public portions. The public portions included hearing from the study’s sponsor about the interest of the U.S. intelligence community in supporting this committee, and talks from outside experts (including Dan Cooley, who spent last Fall as a SAMSI visitor and led our spatial extremes working group).

 Simulations by global climate models show that when sea ice is in rapid decline, the rate of predicted Arctic warming over land can more than triple. The image at left shows simulated autumn temperature trends during periods of rapid sea-ice loss, which can last for 5 to 10 years. The accelerated warming signal (ranging from red to dark red) reaches nearly 1,000 miles inland. In contrast, the image at right shows the comparatively milder but still substantial warming rates associated with rising amounts of greenhouse gas in the atmosphere and moderate sea-ice retreat that is expected during the 21st century. Most other parts of the globe (in white) still experience warming, but at a lower rate of less than 1 degree Fahrenheit (0.5 Celsius) per decade.Photo courtesy of University Corporation for Atmospheric Research

Simulations by global climate models show that when sea ice is in rapid decline, the rate of predicted Arctic warming over land can more than triple. The image at left shows simulated autumn temperature trends during periods of rapid sea-ice loss, which can last for 5 to 10 years. The accelerated warming signal (ranging from red to dark red) reaches nearly 1,000 miles inland. In contrast, the image at right shows the comparatively milder but still substantial warming rates associated with rising amounts of greenhouse gas in the atmosphere and moderate sea-ice retreat that is expected during the 21st century. Most other parts of the globe (in white) still experience warming, but at a lower rate of less than 1 degree Fahrenheit (0.5 Celsius) per decade.Photo courtesy of University Corporation for Atmospheric Research.

So let me try to summarize some of the issues related to climate extremes, as they came up in this committee. There has been a lot of discussion in the literature about the extent to which the increasing frequency of extreme weather events may be said to have been a consequence of human-induced climate change. Superstorm Sandy is the most recent example of this kind of event. However, the experts are still not unanimous about the extent to which extreme events may be attributed to the human influence, and our committee decided not to try to address that issue. Instead, we focused on the changing probability of extreme events, and trying to understand how they are changing regardless of the underlying cause. Another feature of this committee’s work was to focus on fairly short-term events – projections to the end of the century may be of interest to the Intergovernmental Panel on Climate Change, but the feeling here was to concentrate on the next ten years. So the question became: how will probabilities of extreme events change over the next ten years? In the end we agreed that there was not enough published literature on this question to allow us to draw definitive conclusions, beyond a general agreement that such events are becoming more frequent. So we ended up with the rather imprecise but hard to argue conclusion: “Expect Surprises”.

Downed tree from Hurricane Sandy in Jamaica, NY

Downed tree from Hurricane Sandy in Jamaica, NY

Statistics of single extreme events, however, were not the only part of our focus. The report also discussed clusters of extreme events. The idea was that dependences between events in different places might lead to cascades of events, with possibly much greater consequences than just single extreme events. It seemed that bivariate (or spatial) extreme value theory might be a useful tool for this, which is why the committee invited Dan Cooley to speak.

Well, it turned out it wasn’t quite so easy to apply bivariate extreme value theory to the kinds of events the committee was interested in. One focus of our attention was the simultaneous occurrences of high temperatures in Russia and flooding in Pakistan during July and August 2010. A 2012 paper analyzed data from both these events and concluded that there was a plausible physical link between the two. However, an analysis of historical data did not find previous instances of this particular pairing of extreme events, so it was difficult to draw conclusions about joint tail probabilities.

Nevertheless, bivariate extreme value theory did prove useful in a different and unexpected context. Dave Easterling drew my attention to a 2008 paper that pointed out a connection between drought occurrences in the south west USA and the coast of Argentina (likely connected with the meteorological phenomena known as La Niña). Dave asked me whether this correlation would also apply to extreme events – the answer turned out to be yes.

So what was the take-home message? There are various plausible mechanisms by which climate change could affect national, and global, security, but quantifying the risk is far from easy. It was definitely a worthwhile activity in which to take part, and suggested a number of potential topics for my, and maybe also SAMSI’s, future research.

As a final irony, the report was due to be released to the public in Washington on October 31 – the day after Sandy struck much of the eastern seaboard. The press conference was hastily rescheduled for the following week. Expect surprises, indeed.