Postdoc Profile – Benjamin Risk

Ben on top of a mountain in the Galapagos

Benjamin Risk traveling in the Galapagos Islands.

As Ben Risk was growing up in Northbrook, Illinois, (a suburb of Chicago) he always liked to look out in the yard and see the birds soaring above. “As a kid, I was really interested in biology and ecology and birds,” said Ben.

He went to Dartmouth for his undergraduate work where he decided to major in environmental and evolutionary biology. He collected data on the breeding demography of a songbird called the black-throated blue warbler, which got him interested in statistics. “As an undergraduate I had to do a lot of statistical analysis and I had to get help on that because I didn’t have the training. That was the first exposure I had to the importance of statistics,” Ben commented.

Ben writing notes in a notebook on a mountain

Ben in Wrangell St. Elias National Park in Alaska.

After graduating, he moved to Oakland, California, and worked for a few years for an economic consulting firm, Charles River Associates, where he applied statistical methods to anti-trust litigation and environmental economics. “We would come up with a dollar value for how much companies had increased prices through collusion and things like that,” Ben explained, “I was following the instructions of the statisticians, and that also motivated me to consider becoming one of those statisticians.”

He then went to graduate school and received a Master’s degree in environmental science from the University of California, Berkeley. His thesis developed a Bayesian formulation of a metapopulation model. “I was realizing that by specializing in statistics I could be involved in many different fields. I also wanted to be involved in research that would have applications to human health, so I decided I wanted to pursue biostatistics research,” said Ben. It was at that point that Ben enrolled in the Ph.D. program in statistics at Cornell University.

A lot of people at Cornell have been involved with SAMSI, and Ben’s advisors, David Ruppert and David Matteson, also mentioned SAMSI as a place to apply to after he finished his degree. The program on computational challenges in cognitive neuroscience was also announced at JSM 2014, which prompted him to email Haipeng Shen.

Ben is currently researching statistical methods for the analysis of MRI. He is working on one project with Hongtu Zhu, where they are developing a spatial model of the heritability of cortical attributes that are correlated with intelligence. “We are looking at cortical thickness and volume to assess the degree of nature versus nurture,” he explained. He is also working with Daniel Rowe to examine how image processing may affect the conclusions people make regarding which parts of the brain are connected.

Ben typing in his computer on a rock in the Galapagos

Taking measurements of a tortoise in the Galapagos Islands.

Ben is involved in three working groups. He is in the Functional Imaging Methods and Functional Connectivity working group with Jon Aston and Hernando Ombao. He is in the Big Data Integration in Neuroimaging working group with Martin Lindquist and Timothy Johnson. He is also in the Acquisition, Reconstruction, and Processing of MRI Data working group with Dan Rowe.

Ben is an NIH trainee, so will continue his research at SAMSI next year. He is also associated with UNC’s biostatistics department, so will spend time there as well.

When Ben has time, he likes to go cycling and to play guitar. Of course, he still loves birds, so he also likes to go birding when he has time.

Postdoc Profile – Christopher Strickland

Christopher Strickland on a hill with the ocean in the background

Christopher Strickland hiking in New Zealand.

SAMSI postdoctoral fellow, Christopher Strickland was born in Houston, Texas and lived briefly there and in Dallas before he could really remember either place. He grew up in Oxford, Mississippi. His grandfather was Chair of Modern Languages at the University of Mississippi and helped to establish a study abroad program, and his grandmother was originally from France, so many summers his father and grandfather traveled to France. When Christopher went to ” Ole Miss,” in the honors college, he minored in physics before switching degrees and getting a double degree in Mathematics and French.

At first he was following a more pure math route. He went to the University of Florida in Gainesville for his Master’s degree and was studying logic, but after about a year and a half, he realized this was not the area he preferred. After changing his focus to dynamical systems and defending his Master’s thesis, he stayed in Gainesville for a year as he tried to figure out what to do next and taught mathematics at Santa Fe Community College. He knew he would prefer to get into an area that involved applied math instead of pure math. He became interested in mathematical ecology and had heard that Colorado State University had a great program in ecology and the natural sciences, so he applied there to get his mathematics Ph.D.

Christopher considers Patrick Shipman, who was a new faculty member at Colorado State at the time, and Gerhard Dangelmayr, who is the Chair of the department, to be his mentors. They were also his co-advisors. Christopher and Patrick started collaborating on projects right away.

“I was headed toward dynamical systems which is really related to mathematical ecology, so I worked with Patrick and Gerhard for the next six years,” Christopher said, “I still collaborate with both of them, and we are currently applying for a research grant to work with the U.S. Fish and Wildlife Commission.” Christopher has also collaborated with Patrick Shipman and Snehal Shetye at Colorado State on a project modeling the mechanical properties of spinal cords.

Nate Burch told me about SAMSI originally,” said Christopher. “Nate and I were colleagues at Colorado State.” So, when the Ecology program was announced, he applied and was accepted.

Christopher Strickland standing on a rocky edge

Christopher Strickland hiking in Australia.

While he’s been at SAMSI, Christopher has worked on getting various parts of his dissertation re-written into smaller parts so that he can publish each part in various journals. He has three of the four published. The manuscript of the fourth one is completed, and has been submitted as of June 2015.

Christopher has been participating in two working groups this year: The Tipping Point group and the Physical Ecology group. The Physical Ecology group led by Laura Miller, has been particularly interesting for him. “We recently had this really great workshop at SAMSI, which was for the people participating in the working group. We invited Nadia Kristensen from the University of Queensland who brought in all this great data from parasitoid wasp release and spread. That’s been really nice because I mostly do modeling of dynamic systems and the model that she had with this data could be something I could help her improve,” he commented.

“We are also working on a review paper, which is something the working group conceived of sometime around December. The entire working group and even some other people, including some ecologists and my advisor from Colorado State, Patrick, is working on this review,” Christopher said. He believes the review will be completed by the end of this summer.

Much of Christopher’s research focuses on networks, specifically looking at spread and control of contagions on the network. One example would be to look at container shipping networks or airline networks. He is working on a grant that is looking at white nose bat syndrome that involves a network of caves. While bats could spread the disease themselves from cave to cave, there is also the concern that hikers or cavers could get the fungus on their boots and spread the disease when they hike in a different cave. By figuring out how these networks work, it may help ecologists figure out where the disease might spread next, or help them to get a disease under control.

Christopher Strickland makes a kick

Christopher practicing Cuong Nhu.

When Christopher is not at work, he is either playing a game of soccer (he used to be on a math league!) or he is practicing the art of Cuong Nhu, (meaning hard/soft in Vietnamese) a type of martial arts that was brought to the United States in Gainesville, Florida. Christopher is on target to get his black belt, probably in about a year. “A lot of scholarly people actually do this type of martial arts. It has been a good way to network,” quipped Christopher. He also spends time with his girlfriend, Anne Ho, who is a theoretical mathematician. They like to travel a lot, many times to national parks or overseas.

In the fall, Christopher will be teaching at the University of North Carolina at Chapel Hill while he completes his second year as a postdoctoral fellow for SAMSI.

A day on Capitol Hill

The following was written by Kimberly Kaufeld, SAMSI postdoctoral fellow.

The American Statistical Association (ASA) and the Statistical and Applied Mathematical Sciences Institute (SAMSI) paired up to participate in meetings with staffers from Congress and an exhibition for the Coalition for National Science Funding (CNSF) on Wednesday, April 29th in D.C.

The day led off by meeting representatives from Congress to communicate the importance of NSF. Our group consisted of Jessi Cisewski, a former graduate fellow of SAMSI and visiting faculty at Carnegie Mellon University;

three people next to a scientific poster

(L-R) Jessi Cisewski, Richard Smith and Kimberly Kaufeld.

Kimberly Kaufeld, a current postdoctoral researcher at SAMSI ; Richard Smith, the director of SAMSI; and Steve Pierson, Director of Science Policy for the ASA. Together, we had several meetings with staffers from both the Senators and Representatives in North Carolina.

The exhibition in the evening featured science, mathematics and engineering research and education projects supported by the National Science Foundation (NSF). Over 50 projects were represented, including researchers, students, and educators from across the US, as well as program officers from NSF as well as representatives of the Senate and House of Representatives. The SAMSI/ASA poster featured a variety of work from SAMSI. Jessi demonstrated her work in the field of astrostatistics, using statistics for astronomy problems one universe at a time. Kimberly showed her work in the current SAMSI statistical and mathematical ecology program on the impact of bark beetle outbreaks and climate change in the West. Richard talked about what SAMSI is about and past and upcoming programs that SAMSI offers and the number of researchers involved in the programs across the United States.

SAMSI people with Rep. Jerry McNerney

(L-R) Jessi Cisewski, Rep. Jerry McNerney (D-CA-9) and Kimberly Kaufeld.

During the event, representative Eddie Bernice Johnson (D-TX-30), the ranking member of the House Science, Space and Technology Committee talked to Richard Smith about SAMSI and how NSF has contributed to SAMSI’s development. Rep. Jerry McNerney (D-CA-9) also spent some time at the SAMSI booth – he has a PhD in Mathematics and has long bene known as a champion of science in Congress. Several NSF program officers stopped by to talk to Jessi and Kimberly about their research and provided them with different funding opportunities within NSF.

Overall, it was a great experience to meet and talk to representatives of the Senate and House about how NSF is a vital part of the statistical and mathematical community. It was welcoming to see all the different NSF supported programs come together to the Capital to show all the different projects and programs in the United States that NSF is supporting.


SAMSI Postdoctoral Profile: Jyotishka Datta

Jyotishka's wife, Shalini, and Jyotishka with their dog, Max.

Jyotishka’s wife, Shalini, and Jyotishka with their dog, Max.

SAMSI postdoctoral fellow Jyotishka Datta decided not to follow the family tradition and become a doctor. Instead, he decided to follow his other passion, which was mathematics and statistics.

Students at Purdue

Left to right: Shaunak, Prashant, Aravind, Shabih, Saif, Ranjit and Jyotishka.

Jyotishka grew up in Kolkata, India. He went to Ramakrishna Mission Residential College Narendrapur, for his higher secondary education. This was one of the best schools in the region and here he had the opportunity to study with some of the brightest and extremely motivated students. It was then that he decided to pursue a career in a field of research.

Jyotishka went to the Indian Statistical Institute (ISI, Kolkata) for his B.Stat and M.Stat degrees. He developed a strong background in theoretical statistics and was introduced to programming and real-life applications in human genetics. “I had many wonderful teachers there. Not only did they inspire my love for Statistics and Probability, their teaching helped me in many ways on my path to become a researcher and teacher. One of them was Professor Partha Pratim Majumder. He is the head of the human genetics unit at ISI, and the director of the National Institute of Biomedical Genomics (NIBMG) in India. “He used interesting real life examples to demonstrate the need for powerful statistical methods in human genetics that inspired me to develop methods for complex, high dimensional genomic data. I fully realized the importance of his teaching only after I joined the ‘Beyond Bioinformatics’ program at SAMSI,” said Jyotishka.

Jyotishka with friends outside wearing suits

From left to right – Abhishek Sarkar, Anirban Bhattacharya, Nilabja Guha and Jyotishka Datta.

After working with Barclays Bank in Mumbai for a year developing policies and evaluation strategies for customers prior to their acquisition at the bank, Jyotishka came to the U.S. to study at Purdue University for his doctorate in Statistics. He started working with Alan Qi, who is an associate professor in the Departments of Computer Science, Statistics and Biology. After working for one year in Statistical Machine Learning with Prof. Qi, Jyotishka started working under the guidance of Jayanta K. Ghosh, who became his thesis advisor at Purdue. They worked on the theoretical aspects of multiple testing and model selection. “One day he showed me this new paper on the Horseshoe prior that had excellent numerical properties and was becoming very popular in the Bayesian community,” said Jyotishka. One aspect that needed to be looked at was the theoretical properties. After about a year, he could prove theorems that this horseshoe prior was asymptotically optimal.

One of the authors of the Horseshoe Prior was Nicholas Polson, professor at Chicago Booth School who visited Purdue in March, 2014 and they talked about these special class of priors. “I was also working on these priors for a different problem with Anindya Bhadra at Purdue who is also a visitor at SAMSI now. Anindya introduced me to Nick and he proposed this new idea that we can extend the Horseshoe prior to sharpen its ability to extract signals from noise. We named this prior ‘Horseshoe Plus’ prior,” explained Jyotishka.

He said it’s been nice to be able to collaborate with Anindya face-to-face at SAMSI as they begin to complete this research.

Receiving the Studden Award

Receiving William J. Studden award for an outstanding publication in a Mathematical Statistics Journal, from Jeff Roberts, Dean of the College of Science, Purdue University.

Currently Jyotishka is working with Duke Statistics professor David Dunson. They are working on Bayesian non-parametric analysis of ‘sparse’ point processes. This is motivated by a variety of application areas, where the interest is in flexible modeling of the intensity of ‘rare’ event realizations. One particular example is cancer genomic studies collecting data on rare variants, where the focus may be on assessing differences in the variant profile between two groups. There is a growing interest in this area as the common variants identified by the Genome Wide Association Studies (GWAS) often account for a small fraction of heritability and susceptibility to a disease. This is also made challenging by the fact that the number of potential locations of these variants is massive but the intensity is zero in a vast majority of the locations. This also brings the issues of computational efficiency to the fore.

Jyotishka is also collaborating with Sandeep Dave, Associate Professor, Division of Oncology, at the Duke School of Medicine and they are studying RNA-seq analysis of diffuse large B-cell lymphoma (DLBCL). “One of our main objectives is to build a robust supervised classifier to classify subjects into two known subtypes of DLBCL, namely ABC and GCB”.

Shalini with Jyotishka on his graduation day

Shalini with Jyotishka on his graduation day.

Jayanta Ghosh, his advisor at Purdue, was the first person to recommend to Jyotishka that he consider coming to SAMSI for a postdoctoral fellowship. And his good friend, Sanvesh Srivastava, who is a SAMSI second year postdoc this year, also told him about the various nice opportunities that this program offers to a postdoc.

When Jyotishka isn’t working at SAMSI, he likes to read books and occasionally write poetry and scripts for theatre. He was involved in theater at ISI and together with his friends started an inter-college drama festival at ISI. The idea was to create a platform for college students to gather and perform their own plays. Jyotishka also loves drawing and has a long-cherished dream of writing a graphical novel someday.

Jyotishka married Shalini in 2012. They have a dog, Max, who is a terrier. They love going for long walks with Max and exploring local family-owned restaurants and coffee shops. He also likes to blog. (Guess what he will get to do at SAMSI now?)

SAMSI Postdoctoral Profile: Daniel Taylor-Rodriguez

Daniel and Natalia near a mountain range

Daniel and his wife, Natalia.

Daniel Taylor-Rodriguez is a new postdoctoral fellow at SAMSI and is participating in the Ecology program this year. He came from the University of Florida. His wife, Natalia, is still in Gainesville currently working on her Ph.D. in animal science.

Daniel grew up in the bustling metropolis of Bogota, Colombia. When he was 10, his father, who was working for IBM, was temporally transferred to White Plains, New York, so Daniel and his family moved there. After year and a half, Daniel’s family moved back to Colombia to Barranquilla on the coast. Daniel entered a bilingual school to continue his skills in English. Later, his family moved back to Bogota and he continued at a school that offered an International Baccalaureate (IB) program. Tony Cleaver, an inspiring IB economics teacher, strongly influenced Daniel’s decision to pursue a degree in economics.

Daniel studied economics at the Universidad Los Andes from 1998-2003, “I especially enjoyed the econometric courses; to me it made more sense to let data speak by itself,” commented Daniel. He then went on to get a specialization (similar to a professional Master’s degree in the United States) in statistics. At the same time, he started working as a consultant under his game theory professor Luis Jorge Ferro. In particular, they developed optimal incentive and penalty mechanisms in contracts for large-scale highway concession projects required by the National Concessions Institute of Colombia.

About a year later, a group of his friends from National University of Colombia who were wildlife veterinarians were starting up a wildlife conservation organization called Fundación Vida Silvestre Neotropical (FVSN). They invited Daniel to come work with them and he decided to help them out. Their first project was to help cattle ranchers identify what management practices reduced the risk of predation from panthers (pumas) using various quantification protocols. “I really enjoyed being in the field, talking to people, collecting data and making a meaningful contribution”, said Daniel. These findings informed local governments in the implementation of programs to mitigate predation risk in livestock ranches.

Although he continued to participate in FVSN as an honorary member, Daniel went to work as a quantitative risk analyst at Bancolombia, Colombia’s largest banking institution. There he developed models to quantify credit risk components. He also built in-house models to forecast macroeconomic series affecting risk behavior of client portfolio. Through Bancolombia he applied to a Fulbright Scholarship, which he was awarded to pursue a Master’s degree in statistics at the University of Florida, at the end of which he would have to return.

group of seven people from University of Florida

Daniel (lower right) along with former SAMSI postdoc Kenny Lopiano (lower row, center) at the University of Florida

While at the University of Florida, he studied under George Casella, who made him aware of the wonderful opportunity he would miss if he left without doctoral training. Daniel made arrangements with the bank’s directives to stay for the PhD; however, a semester before concluding his Master’s, a new CEO was appointed to the bank bringing along his own team. Due to the new conditions Daniel was requested to return to Colombia. Intent on pursuing his doctoral studies, he turned down this request. Fortunately enough the new bank’s directives reconsidered and decided that it was not their place to truncate Daniel’s academic aspirations. They terminated his contractual obligations with the bank, but left the doors open for him to come back if he ever wished to do so.

Daniel in the Gators stadium

Daniel at a Gators game.

He stayed at University of Florida to receive his Ph.D., but eager to learn more about ecology, he enrolled in the interdisciplinary ecology program with concentration in statistics. Daniel truly appreciates the strong bonds and collaborative approach to research that George Casella fostered within his working group. After Dr. Casella’s passing he received the continued and insightful supervision of Professors Linda Young and Nikolay Bliznyuk.

In the course of his studies, he contributed to projects with researchers in the Animal Sciences, Ophthalmology, and Horticulture Departments at UF, and took part in the NSF funded program IGERT Quantitative Spatial Ecology, Evolution, and Environment (QSE3). In his collaborations he worked jointly with scientists from diverse backgrounds to develop interdisciplinary solutions to important applied problems.

Daniel’s doctoral research focused on developing Bayesian procedures for variable selection with good frequentist properties, and adapting these methodologies to models widely used in population ecology. The Jaguar Corridor Initiative, a large-scale conservation effort lead by Panthera foundation, inspired Daniel’s work. Panthera is a nonprofit organization that helps large felines through scientific research and global conservation. The corridors established by Panthera across South and Central America, aim to ensure an active pathway that preserves the link between the last two jaguar populations in the world. A preliminary but crucial step in building the corridor in Colombian territory is to produce accurate density maps for jaguars and their prey, which can be obtained using models that account for imperfect detection. Surveys conducted to fit these models collect information about a large number of predictors. However, there is need to improve the methods used to identify the relevant predictors and to assess uncertainty in the model parameter estimates due to selection.

At SAMSI Daniel will study questions associated with the dynamics of infectious diseases, and will expand his work on population ecology, modeling the joint behavior of species sharing the same ecosystem. His two years at SAMSI will give him the opportunity to meet and collaborate with researchers from different backgrounds and to engage in new and exciting projects.

Daniel at a marathon

Daniel enjoys running.

Daniel also enjoys running, mountain biking, watching movies and, of course, spending time with Natalia.

Become a SAMSI Postdoc Fellow!

a collage of the postdocs from 2013-14

Our 2013-14 SAMSI postdocs.

SAMSI has a great opportunity for six people to become a postdoctoral fellow next year! Get the chance to collaborate, and mingle with top researchers in your field of interest.

You can apply for either of the two SAMSI Research Programs: Challenges in Computational Neuroscience (CCNS) and Statistics and Applied Mathematics in Forensic Science (Forensics). Appointments (up to 2 years) will begin in August 2015, and will offer competitive salaries, travel stipend and health insurance.

The Challenges in Computational Neuroscience (CCNS) program will develop mathematical and statistical methods for neuroscience applications to understand the underlying mechanisms that bridge multiple spatial and temporal scales, linking the activity of individual components (e.g., molecular biology, genetics, and neuron networks), and their interactions to the complex dynamic behavior of the brain and nervous system. Brain theory, modeling, and statistics will be essential to turn data into better understanding of the brain. The CCNS program will address the underlying methodological, theoretical, and computational challenges. Probability and statistics, dynamical systems, geometry, and computer science will be combined with respect to theory and in applications.

SAMSI’s program on Statistics and Applied Mathematics in Forensics is focused on strengthening the statistical and applied mathematical foundations of forensic science. Forensic science is fundamentally based upon statistical comparisons of the characteristics of materials left at a crime scene to characteristics of possible sources or suspects. These comparisons are often acknowledged by forensic scientists to be highly subjective. A series of reports by the National Research Council (NRC) has raised deep questions about major forms of forensic evidence and has made a clear case for heeding statistical underpinnings for forensic procedures. Evidence from a crime include fingerprints, patterns and impressions (footprints and tire tracks), toolmarks and firearms, hair, fibers, documents, paints and coatings, bloodstains, and fire debris.

To apply, go to, SAMSIPD2015, Job #6133. In your cover letter, please indicate which of the two research programs you are interested in. The deadline for full consideration is December 15, 2014, although later applications will be considered as resources permit.

Criteria for selection of SAMSI Postdoctoral Fellows include demonstrated research ability in statistical and/or applied mathematical sciences, computational skills along with good verbal and written communication abilities, and finally, a strong interest in the SAMSI program areas.

SAMSI is an AA/equal opportunity employer All qualified applicants are encouraged to apply, especially women and members of minority groups.

Former Postdoc Kenneth Lopiano Speaks at RTP180

Dr. Kenneth Lopiano, co-founder of Roundtable Analytics and former postdoctoral fellow at SAMSI, spoke to a sold out crowd last night at the RTP180 event. RTP180 is a monthly after-hours get together where speakers spend about 5 minutes talking about a topic they are passionate about, and that highlights some of the research happening in the Triangle region. It’s kind of like a mini TED talk meets Pecha Kucha.

Kenneth Lopiano on stage

Kenneth Lopiano talking at RTP180.

Lopiano spoke about the simulation model he and others developed to help ER departments become more efficient. You can read more about it here.

Some of the comments on Twitter included: @nxtstop1 “”Round table analytics” ~ does work in ERs using simulation models to determine best practice for that particular dept~

@Jnewbay “Emergency departments moving more efficiently? I’m in! Shorter wait times in the ER?

@bentanthony01 “ pitching at – Are you tired of waiting at Emergency Department? ED simulation models

@HealthView “We need actionable insights to healthcare data says Roundtable Analytics <Hear! Hear!”

You can watch the full video, including Kenneth Lopiano’s presentation here.

Professional Development Luncheon Featured Robert Rodriguez of SAS Institute

Bob Rodriguez of SAS talking to postdoctoral fellows

Bob Rodriguez of SAS shares his experience working for industry.

Robert N. Rodriguez, senior director of statistical research and development at SAS Institute in Cary, North Carolina, spoke to the SAMSI postdoctoral fellows at a professional development luncheon today. Dr. Rodriguez is responsible for the development of statistical software, including SAS/STAT and SAS/QC software.

table of postdoctoral fellows listening to Bob Rodriguez

Everyone was interested in hearing what Bob Rodriguez of SAS had to say.

Rodriguez shared with the postdocs some tips about pursuing a career in industry. While many postdocs enter academia, several are also interested in careers in industry and government. It was extremely valuable to them to have a fresh perspective on what a career in industry is like.

Two people listening to Bob Rodriguez as he talks

(l-r) Sujit Ghosh, Tom Witelski and Ilse Ipsen, Associate Directors for SAMSI, also enjoyed Bob Rodriguez’ talk

Graduate Students Work on Real-World Problems at 20th IMSM Workshop

The 20th Industrial Mathematical and Statistical Modeling Workshop for Graduate Students (IMSM) just wrapped up its workshop last week. The students met for 10 days and broke into five teams, working with mentors from government and industry on real-world problems.

group shot on stairs

20th IMSM workshop participants and their mentors.

Thirty one graduate students from 28 different institutions participated in this year’s workshop. The first day the representatives from industry and government presented their projects, which ranged from developing a water purification system to finding where a meteor might have crashed in Russia in 2013.

Lincoln Lab group shot

Pictured (L-R) are: Michael Minner, Drexel; Jingnan Fan, Rutgers; Benjamin Levy, U. Tennessee; Het Mankad, U. of Texas at Dallas; Alex Farrell, Arizona State; Hossein Aghakhani, SUNY at Buffalo; Ya-Ting Huang, U. New York-Stony Brook; John Peach, MIT Lincoln Laboratory and Minh Pham, SAMSI.

The “Hunt for Red Hot Rock-tober” group was mentored by John Peach, MIT Lincoln Laboratory, and Minh Pham, SAMSI, included: Hossein Aghakhani, SUNY at Buffalo; Jingnan Fan, Rutgers; Alex Farrell, Arizona State; Ya-Ting Huang, Stony Brook; Benjamin Levy, U. Tennessee; Het Mankad, U. of Texas at Dallas; and Michael Minner, Drexel.

They tried to figure out exactly where a meteor landed that had exploded in an airburst on February 15, 2013 somewhere south of the city of Chelyabinsk, Russia. The group used Bayesian search methods to formulate as many hypotheses they could about what happened to each object assuming that it most likely broke up into several smaller chunks as it entered the atmosphere. For each hypothesis, they constructed a probability density function for the location of each object. The other scenario is that it stayed in one piece and hasn’t been found yet. The group used Google Earth images and created a Google Earth sensor to detect meteor-like shapes. They made a probability map of where chunks of the meteor may have landed, sorted by the highest probability down. They only searched the top 90% and then looked at images before and after the event. They needed to reduce the false alarms, so they converted the images to gray scale and then to binary. They re-grayed the imaged and used a Gaussian blur to detect differences in the before and after images that were round-shaped like a crater would be. This reduced the false alarms from 71 to 27. Seven of these images seemed acceptable, but none of the images they looked at ultimately were craters. They concluded that there was a 57.2% chance that there was no crater in the area.

Army Corps of Engineers group shot

Pictured here from (L-R) are: Benjamin Ritz, Clarkson; Monica Nadal-Quiros, U. of Puerto Rico; Caleb Class, MIT; Tyson Loudon, Colorado School of Mines; Star-Lena Quintana, Temple; Lea Jenkins, Clemson; Matthew Farthing, U.S. Army Corps of Engineers, Fei Cao, Pennsylvania State; and Xiangming Zeng, North Carolina State U.

The group working with Matthew Farthing, U.S. Army Corps of Engineers and Lea Jenkins, Clemson University, on the project entitled “Water purification via Membrane Separation,” included: Fei Cao, Pennsylvania State; Caleb Class, MIT; Tyson Loudon, Colorado School of Mines; Monica Nadal-Quiros, U. of Puerto Rico; Star-Lena Quintana, Temple; Benjamin Ritz, Clarkson; and Xiangming Zeng, North Carolina State U.

They were looking at a way to create the best water purification system. While filtration is typically used to remove a particular contaminant, it can also be used to retrieve valuable components. This would be used for other industries, such as the pharmaceutical industry, or polymer processing. The group used a simulation-based optimization to look at how to improve membrane performance for filtration and separation processes. One of the important applications for this project was to purify water for army personnel in the field who need to reduce pathogens, quickly purify water and reduce the incidence of clogging the membrane. Due to time restraints, the group focused on one-dimensional models, but suggested that future work would use 2-D or 3-D models to better represent the dynamics of the separation process.

CDC group shot

L-R- Isabel Chen, Emory; Christina Edholm, U. Lincoln-Nebraska; Howard Chang, Emory; Simone Gray, CDC; Rachel Grotheer, Clemson; Tyler Massaro, U. Tennessee; Yiqiang Zhen, Purdue.

The “Geographic and Racial Differences of Persons Living with HIV in the Southern United States” group was mentored by Simone Gray, Centers for Disease Control and Prevention (CDC) and Howard Chang, Emory. The group included: Isabel Chen, Emory; Christina Edholm, U. Lincoln-Nebraska; Rachel Grotheer, Clemson; Tyler Massaro, U. Tennessee; Yiqiang Zhen, Purdue.

The group was tasked to quantify the contribution of race and socioeconomic determinants to the overall presence of HIV, particularly focusing on the Southeast. They used the 2010 U.S. Census data and the American Community Survey, along with the DCD’s National Center for HIV/AIDS, Viral Hepatitis, STD and TB Prevention (NCHHSTP) Atlas and looked at several variables including unemployment, education level, race, urban status, poverty and income at the county level, which included 1,422 counties in 16 states. They used three types of regression modeling including multiple linear, conditional autoregressive, Bayesian Poisson hierarchical mode; non-metric multidimensional scaling and two types of cluster analysis (K-Means and Besag-Newell) to analyze the data. They concluded that the non-Hispanic black ethnicity remained the most important indicator of HIV prevalence rate in the southern United States.

Rho Inc. group

L-R- Yuanzhi Li, Utah State; Hongjuan Zhou, U. of Kansas; Anastasia Wilson, Clemson; Tamra Heberling, Montana State; Nancy Hernandez Ceron, Purdue; Augustin Calatron, Rho Inc.; Alexej Gossmann, Tulane; and Herman Mitchell, Rho Inc.

Another group worked on the “Allergy, Asthma and Exposures in the Homes of the US Population” problem. The group, mentored by Agustin Calatroni, Herman Mitchell and Russ Helms of Rho, Inc. and Sanvesh Srivastava of SAMSI, included: Alexej Gossmann, Tulane; Tamra Heberling, Montana State; Nancy Hernandez Ceron, Purdue; Yuanzhi Li, Utah State; Anastasia Wilson, Clemson; and Hongjuan Zhou, U. of Kansas.

From 1980-2012, cases of asthma in the U.S. has increased by 171% . Allergies and asthma cost about $56 billion a year. An extensive study called the National Health and Nutrition Examination Study (NHANES) was conducted in 2005-06 to develop a prediction model for asthma based on allergies and exposures in the home. They surveyed about 10,000 people to determine the prevalence of major diseases and the risk factors for those diseases. Rooms in the participant’s homes were vacuumed to collect dust samples. The students used logistic regression, LASSO regression and random forest models to examine the data. They concluded that the random forest models had the highest accuracy rate for prediction.

SAS group

L-R-Kenny Lopiano, SAMSI and Duke; Obeng Addai, Youngstown State; Shrabanti Chowdhury, U. California at Riverside; Piaomu Liu, South Carolina; Mark Wolf, SAS; Karianne Bergen, Stanford; Xin Huang, U. Texas at Dallas and Fatena El-Masri, George Mason.

Another group worked on the “Analysis of Self-Reported Health Outcomes Data ” project. The group that was mentored by Mark Wolf, SAS, and Kenneth Lopiano, SAMSI and Duke, included: Fatena El-Masri, George Mason; Karianne Bergen, Stanford; Obeng Addai, Youngstown State; Piaomu Liu, South Carolina; Shrabanti Chowdhury, U. California at Riverside and Xin Huang, U. Texas at Dallas.

This group looked at self-reported health outcomes data from web based media sources. Usually clinical outcomes are derived from surveys of patients and formal reports from physicians when a side effect occurs from taking a drug, for example. However, many people are on forums, bulletin boards and social media outlets talking about drug-related or health-related data that gives more instantaneous feedback about how a drug may be performing. Text mining techniques are very important to get this kind of feedback. The group used SAS Enterprise Miner to parse, filter and identify topics in each document they examined. They proposed a set of methods taking advantage of SAS Text Miner to break the words up into nouns, verbs, adjectives, etc. They then used a filter to decide whether to keep or drop the word, and then had the program classify the word into a category. They looked at author interactions and applied a page rank algorithm. They then conducted a sentiment analysis to gather any emotion around the posts and then took out the useless posts and just kept the ones that seemed to be noteworthy. They looked at topics trending to see if there was increased chatter on a topic using a burst detection method, then used a Markov model to analyze the inter arrival gaps.

To get a much better understanding of the work that was conducted during this workshop, read the final report here.


Emergency Department Simulator Uses Analytics to Help Administrators Make Data-Driven Decisions

Emergency departments (EDs) are under growing pressure; while the number of ED visits have sharply increased, the number of EDs serving this need has actually decreased. According to a report from Rand Corporation, ED doctors are increasingly becoming the decision-makers regarding hospital admissions. Today, nearly half of all non-obstetrical hospital admissions occur through the ED. With the adoption of the Affordable Care Act, it is expected the number of ED visits will continue to rise. ED staffs are, therefore, looking for ways to make effective decisions to make their departments more efficient.

A group of researchers from the University of Florida and the Statistical and Applied Mathematical Sciences Institute (SAMSI) have created an online simulator to help hospital ED administrators understand how analytics and simulation can be used to inform decisions in the ED. In particular, the simulator reveals how various factors or decisions affect the flow of patients through the ED. The group includes, Kenneth Lopiano, SAMSI; Joshua Hurwitz, Jo Ann Lee, Scott McKinley, James Keesling, University of Florida Department of Mathematics; and Joseph Tyndall, University of Florida Department of Emergency Medicine.

flow map of an ED

Flow map.

The simulator is freely available on the web at On the website doctors or administrators can change several different variables to best mimic the conditions in their particular ED. For example, one can change the number of beds, number of doctors, number of nurses for various hours of the day, or number of patients entering the ED at different times of the day.

Lopiano, who was a postdoctoral fellow at SAMSI during this past year’s Data-Driven Decisions in Healthcare research program, learned about the power of simulation in healthcare through SAMSI-sponsored working groups. It was during a visit to his alma mater, the University of Florida, to discuss his SAMSI experiences when Lopiano learned of lead author Joshua Hurwitz’s efforts. There Lopiano connected with former SAMSI postdoctoral fellow and assistant professor Scott McKinley who introduced Lopiano to Hurwitz. Realizing their common research interests, the core research group was formed which led ultimately to the online simulator, principally developed by Lopiano and Hurwitz. The online simulator has seen substantial increases in traffic since the publication of their research paper in BMC Medical Informatics and Decision Making.

photo of Dr. Kenneth Lopiano

Dr. Kenneth Lopiano

The simulator recognizes that the causes of ED crowding are variable and require site-specific solutions. For example, in a nationally average ED, provider availability can cause bottlenecks in patient flow while investments in other resources may not have the positive impact an administrator would expect. Further, the simulator recognizes that by reallocating resources and creating alternate care pathways, some EDs can dramatically expedite care for lower acuity patients without delaying care for higher acuity patients.

Lopiano, co-founder and principal collaborator of Roundtable Analytics, a healthcare analytics company based in Raleigh, North Carolina, said, “A simulator is very effective because it is risky for health systems to implement overhauls in their care-delivery systems. By using a simulator, administrators are able to evaluate many different scenarios without making these costly and time-consuming changes. Most importantly, administrators can understand the consequences of operational decisions, both intended and unintended.”

The paper published in BMC Medical Informatics and Decision Making is available at: Kenneth Lopiano may be contacted at