SAMSI & NCCU Host Forensic Science Research Workshop

David Banks, SAMSI Director, gives a talk on how statistics is used in the legal system during the Statistics in the Criminal Justice System Workshop, Mar. 24. Banks talked about his experiences appearing as an expert witness in a trial that centered on discriminatory practices used in law enforcement. The workshop was held at NCCU and was offered to undergraduate and graduate students participating in science and math-based curriculum. This event marked the first time SAMSI has performed a workshop on the campus of a HBCU.

SAMSI co-hosted an undergraduate workshop with North Carolina Central University (NCCU) on their campus, Mar. 24, 2018.

The workshop, Statistics in the Criminal Justice System, was about how statistics is used in forensic science and the legal system. This event was the first time that SAMSI has co-hosted a workshop with a Historically Black College or University (HBCU) and it provided an opportunity to expand awareness about the uses of applied mathematics and statistics to African-Americans and other underrepresented groups.

“We wanted to expose an interesting and important aspect of the use of statistics to the students attending this workshop,” said Elvan Ceyhan, SAMSI Deputy Director and one of the primary organizers for the event. “Our postdocs and graduates also provided important information regarding the opportunities upon graduation.”

The workshop was highlighted by keynote speaker Dr. Kristian Lum. Lum is the Lead Statistician for the Human Rights Data Analysis Group (HRDAG). Her research focuses on how machine learning-based predictive policing models often lead to racially biased law enforcement. Lum’s talk was primarily about how certain statistical algorithms give results that draw law enforcement into positive feedback learning cycles that reinforce false conclusions and fail to fully explore locations where crimes are being committed.

Lum was followed by David Banks, SAMSI Director, who spoke about his experience as an expert witness in a case involving potential ethnic bias and a local sheriff. Banks explained how research professionals are chosen and deposed by the legal system and what criteria were used in his case to determine guilt or innocence.

Part of SAMSI’s future goals are to branch out and include events like this in their annual workshop planning agenda. Feedback from the students who attended was largely favorable and many felt as though events like this would be beneficial at other HBCUs as well.

“I definitely think that a lot of people are interested in statistics and from what I’ve seen there is a large demand for it [statistics] in the future. I think because of that you’ll probably find a lot of interest as you go around to different schools,” said Christian Richardson, a senior biology major and math minor at NCCU.

Recent data shows participation of people of color and women in math and science-based curricula and careers has been on a steady rise. The report suggests that the number of masters and doctoral degrees obtained by people of color and women has been slowly increasing since 2004.

The report captures demographic data on various underrepresented groups and was released by the National Center for Science and Engineering Statistics (NCES) in January 2017. The report, called Women, Minorities, and Persons with Disabilities in Science and Engineering (WMPD), is a congressional mandate that is part of the Science and Engineering Equal Opportunities Act, enacted in December 1980. The WMPD is a biennial report produced by the National Science Foundation (NSF).

The report highlights trends and demographic data of women, people with disabilities and minorities from three racial and ethnic groups – African-American,

Ciara Allen, an undergraduate mathematics major at NCCU, works with R Software during a practical exercise at the Statistics in the Criminal Justice System Workshop on the NCCU campus, Mar. 24. Allen and several other students attended the one day workshop to learn about this software, used in statistical analysis, and how to prepare for a future career in math and/or science fields of study. The event marked the first time SAMSI has hosted a workshop on the campus of an HBCU.

Hispanic and American Indian or Alaska Native. The 2017 report noted that between 2004 to 2014 masters and doctoral degrees among underrepresented groups has increased. This trend has driven a significant increase in employment in science, mathematics and engineering jobs.

SAMSI’s mission is to influence the next generation to pursue careers and research opportunities in applied mathematics, statistics and computer science-based occupations. This is what led to the opportunity for SAMSI to connect with students at NCCU.

“For a long time, SAMSI has wanted to forge a connection with NCCU and other HBCUs in the area,” said Banks. “This program was a great first step and we shall follow it up with more interaction and another workshop in the fall.”

Students attending the workshop also took part in a small tutorial on the use of R software. The students learned how to use data captured in R to predict and, in some cases, help solve actual crimes.

“I came to this program to understand R software to help me with a graduate project,” said Darryn McLaughlin, a graduate student working in the Earth, Environmental and Geospatial Sciences Department at NCCU. “It [R] is new to me and I wanted to use this as an opportunity to get a basic understanding of how I can incorporate it to use in my project.”

Many students were excited to explore the software package and learn about its practical applications. The scenario presented in this workshop centered on using national finger print data to determine links between crime scenes and perpetrators. The goal of the exercise was to see if one could truly identify trends that point to crimes committed in different locations, but by the same perpetrator using the same modus operandi (MO). Using the finger print data at multiple crime scenes, the students got to see how to infer such patterns from the evidence and statistical data acquired at the crime scene.

Students also enjoyed the panel discussion by postdoctoral fellows and MS and PhD candidates. The panelists described their personal challenges and successes as they pursued their own careers in math and science. For some NCCU students, the experience opened their minds to the possibilities of pursuing a career in these fields.

Ciara Allen, a mathematics undergraduate at NCCU, talked about what attracted her to the workshop and what she learned about future pathways towards a career in science and math.

“It was the intro and hands on for the R Studio that attracted me initially…However, after I got the flier in the email and I read over it, I thought this was interesting to see how math can be applied to other ‘not so mathematical’ areas’,” said Allen.

Allen also said she took solace in the fact that even though her future plans in math were uncertain, she learned from the panel that the research in math and science is so broad that a person can study several areas that interest them and eventually find something that’s right for them, or simply continue to pursue new discoveries or opportunities that are of interest to her.

“I think this has been a good first step in reaching out to underrepresented minorities, and we would like to make use of this experience in our future endeavors,” said Ceyhan.

To find out more about what was presented at this workshop, visit the webpage at: https://www.samsi.info/nccu.

Michael Akande (left), a PhD student from Duke University, speaks about his experiences in the field of applied mathematics during a panel discussion about math and science careers. Akande, Postdoctoral Fellows, and other PhD students shared their insight during a panel discussion at the Statistics in the Criminal Justice System Workshop on the NCCU campus, Mar. 24. The panelists discussed their experiences and their personal challenges, as well as successes, they had while pursuing their own careers in math and science.

Undergraduates See Influence of Mathematics at SAMSI Workshop

Elvan Ceyhan, SAMSI Deputy Director, introduces undergraduate students to programs at SAMSI during the Undergraduate Workshop, presented at SAMSI from Feb. 26-27, 2018. The focus of the workshop was to introduce an overview of current and planned SAMSI research programs and also how Quasi-Monte Carlo and High-Dimensional Sampling Methods are used in modern day research to solve a variety of real-world problems

SAMSI completed a two-day workshop focused on providing undergraduate students with an overview on topics of current interest in statistics and applied mathematics.

The workshop, hosted at the SAMSI Institute from Feb. 26-27, 2018, brought together nearly 30 undergraduate students from across the nation. The subject matter emphasized an overview of current and planned SAMSI research programs and primarily how Quasi-Monte Carlo and High-Dimensional Sampling Methods are used in modern day research to solve a variety of real-world problems.

“The goal of the workshop was to expose undergraduates to the broad class of computational algorithms called Monte Carlo methods in various contexts and diverse applications and it did a decent job on this given the limited amount of time,” said Elvan Ceyhan, SAMSI Deputy Director and workshop organizer.

The principles discussed in the lectures helped show how this applied mathematical research could be used across a broad spectrum of research.

“It was a nice workshop for the undergraduates to learn about Monte Carlo methods and see their applications in different contexts,” said Jianfeng Lu, professor of mathematics at Duke University and a guest lecturer at the workshop. Lu presented a talk on an Introduction to Markov chain Monte Carlo Methods to help undergraduates gain perspective on how these methods are used to develop accurate data that can be used to solve a myriad of problems in business and industry.

“The students showed genuine interest on topics that are accessible yet may not be covered in the traditional undergraduate courses, and the speakers were intentionally chosen at different levels of their careers to show students how a mathematical scientist does research,” said Ceyhan.

Yawen Guan, a 2017-18 SAMSI Postdoctoral Fellow, introduces undergraduate students to a brief tutorial on ‘R’ Software during the SAMSI Undergraduate Workshop. The workshop was presented at SAMSI from Feb. 26-27, 2018. The students later used the information from the tutorial to perform simulations using Monte Carlo algorithms.

SAMSI Postdoctoral Fellows also presented hands on demos on using ‘R’ Software to perform Monte Carlo simulations. In addition, these young professionals also conducted a panel to speak about their experiences thus far in their academic careers and what undergraduates should consider if they are interested in pursuing math and science-based jobs.

The undergrad students overall got a lot out of the event and some will return to their schools with a new attitude about pursuing math-based careers. Students thought the lectures were informative, insightful and fun. “[The mathematical] Applications were incredibly valuable for my understanding of theories,” said an attendee. “With a natural interest in science I thought these presentations were very cool.”

Students also enjoyed the panel on applied mathematics and statistics-based career opportunities. “I enjoyed learning about how the panelists felt about their paths to graduate school,” said one student. “I got useful information about the types of research available for statistics majors.”

Students and lecturers alike enjoyed the experience and praised the workshop for its ability to speak at all levels to all types of students.

“It was very enjoyable to speak to the participants of the SAMSI Undergraduate Workshop. The students were interested and engaged and asked insightful questions during and after my lecture,” said Erik Van Vleck, a mathematics professor at the University of Kansas and a speaker at the event.

Van Vleck spoke about how Predictability and Chaos algorithms are developed to create accurate predictions on subjects like climate research. His talk was about an introduction to mathematical chaos and the consequences of chaotic behavior on predictability.

“This type of workshop is a great way to foster interactions between undergraduate students and SAMSI postdocs and visiting researchers,” said Van Vleck.

The workshop’s success was reflected in the numerous amount of positive comments provided by the undergraduate students who attended. “I think [these workshops] are a good way to meet people from outside your university and they expose you to topics that aren’t covered in traditional undergraduate courses,” said a student.

 

Workshops like this are in keeping with SAMSI’s focus: to help raise awareness for the importance of applied mathematics, statistics and computer science. Further, these workshops offer students a new perspective and appreciation for science and math-based curriculum and career opportunities.

 

To find out more about what was presented at this workshop, visit the webpage at: https://www.samsi.info/qmc-ugrad.

Erik Van Vleck, a professor of mathematics at Kansas University speaks to undergraduate students at the SAMSI Undergraduate Workshop. The workshop was presented at SAMSI from Feb. 26-27, 2018. Van Vleck’s talk focused on how Predictability and Chaos algorithms are developed to create accurate predictions on subjects like climate research.

SAMSI Completes Second Workshop in QMC Program

Ilse Ipsen, Associate Director of SAMSI and QMC Program Organizer, speaks to colleagues at Trends and Advances in Monte Carlo Sampling Algorithms Workshop on the Duke University campus Dec. 11, 2017. Ipsen helped bring more than 100 experts in the fields of applied mathematics, statistics and machine learning together for the purpose of exchanging ideas and advancing the broad area of sampling algorithms.

SAMSI hosted the Trends and Advances in Monte Carlo Sampling Algorithms Workshop, part of the Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applied Mathematics (QMC) Program on the campus of Duke University from Dec. 11-15, 2017.

The workshop was attended by more than 100 experts in the fields of applied mathematics, statistics and machine learning for the purpose of exchanging ideas and advancing the broad area of sampling algorithms.

This event was the second workshop presented in the QMC program and featured how Monte Carlo sampling methods can be used to help optimize performance of machines and/or business and industrial processes. This complex methodology is widely used in physics, chemistry, mathematics and statistics, and is most useful when other methods fail due to the high dimensionality of the problem.

Participants enjoyed a week-long workshop that featured talks from innovative mathematicians from around the world. The talks focused on research being done in the field of Monte Carlo sampling and how these applications can be used to tackle real-world problems in business and industry.

The QMC program has ten working groups that were created in the QMC Opening Workshop in late August 2017. The working groups support research being done by applied mathematicians, statisticians and researchers across a wide variety of topics. The working groups will re-convene at the QMC Transition Workshop in May 2018 to discuss their findings and to develop collaborations between colleagues for future research.

The Trends and Advances Workshop is one of many ways in which SAMSI continues to promote the importance of applied mathematics, statistics and computational science. To see the research presented, visit the workshop webpage at: https://www.samsi.info/qmc-trends-and-advances.

Participants at the Trends and Advances in Monte Carlo Sampling Algorithms Workshop display research posters on Dec. 12, 2017. The workshop focused on research being done in the field of Monte Carlo sampling and how these applications can be used to tackle real-world problems in business and industry.

 

New Era Begins at SAMSI with NEW Director

David Banks, SAMSI Director

In January 2018, SAMSI welcomed its third director, David Banks, a Professor of the Practice of Statistics from Duke University’s Department of Statistical Science.
“SAMSI is amazing…I’ve been involved since 2003, and I have watched it grow and evolve,” said Banks upon being announced as the new director.
Banks took over the position from Richard Smith, the Mark L. Reed III Distinguished Professor of Statistics and Professor of Biostatistics from the University of North Carolina at Chapel Hill’s Department of Statistics and Operations Research (STOR). Smith has served as SAMSI Director since 2010 and now assumes the role of an Associate Director at SAMSI.
During his tenure, Smith did a great deal to enhance the SAMSI brand by working to bring in interesting programs that highlighted the importance of statistics and applied mathematics across a broad spectrum of subjects. From forensic science to astronomy or computational methods for large data and climate research, Smith worked with the SAMSI directorate and staff to bring in fresh programs organized by some of the leading experts in their fields from around the world. In his new role as an associate director, Smith will focus more of his efforts towards his passion of teaching and climate research.
Banks obtained his Master of Science in Applied Mathematics from the Virginia Polytechnic Institute and State University in 1982, followed by a Ph.D at the same school in Statistics in 1984. In his career, Banks has served in numerous academic institutions and government organizations. One of Banks’ most prestigious positions was as Chief Statistician of the U.S. Department of Transportation in the late 1990’s, followed by a stint at the U.S. Food and Drug Administration in 2002. Banks returned to academics in 2003, where he joined the Department of Statistical Science at Duke.
“Every time you change jobs you get a new skill set, a new set of friends, some new ideas and a raise,” said Banks. “If you change jobs well, you keep the old friends, skills and thinking. Changing jobs is positive, and I hope my move to SAMSI will be as gratifying has my previous job hopping has been.”
In addition to his many professional accomplishments, Banks has also written scholarly papers and has served as an editor of the Journal of the American Statistical Association, as well as co-founding the journal of Statistics and Public Policy, where he also served as an editor. He has also published 74 refereed articles, edited eight books, and co-authored four monographs.
In his research, Banks enjoys statistical modeling the most because the research offers insight into the explanations of complex problems. His research areas also include models for dynamic networks, dynamic text networks, adversarial risk analysis (i.e., Bayesian behavioral game theory), human rights statistics, agent-based models, forensics, and certain topics in high-dimensional data analysis.
Banks recently served as the president of the International Society for Business and Industrial Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics. He also won the American Statistical Association’s Founders Award in 2015.
Banks’ said that for now, until he gets more comfortable in his new position as director at SAMSI, he will focus research goals towards data science and machine learning methodologies. Everyone at SAMSI welcomes Banks as the new director and looks forward to working with him.

New Deputy Director Begins Term at SAMSI

Elvan Ceyhan, SAMSI Deputy Director

After many months SAMSI is proud to welcome their newest Deputy Director, Elvan Ceyhan.

Ceyhan, who was a visiting associate professor at the University of Pittsburgh in 2016, joined the SAMSI directorate in July this year. He joins the SAMSI team and will also serve as a research associate professor of the Department of Statistics at North Carolina State University (NCSU). He replaces former Deputy Director, Sujit Ghosh, who is currently a Professor of Statistics in the same department at NCSU.

Ceyhan, a Turkish native, received his undergraduate education and a Bachelor of Science in Mathematics from Koc University (KU) in Istanbul, Turkey. In 1997, he came to the United States and originally attended Oklahoma State University’s (OSU) Ph.D. Program in Mathematics, before changing his mind and switching to their statistics master’s program. He went on to receive his Master of Science degree in Statistics from OSU in 2000. That same year, Ceyhan began the Ph.D. program in the Applied Mathematics and Statistics Department at Johns Hopkins University – he went on to receive his Ph.D. from Johns Hopkins in 2004.

From 2004 to 2005, Ceyhan worked as a postdoctoral fellow at the Center for Imaging Science at Johns Hopkins. After his time at Johns Hopkins, he returned to Turkey and served as an assistant professor in the Department of Mathematics at KU until 2011, when he was promoted to an associate professorship. Ceyhan served in that capacity until 2016, when he went to the University of Pittsburgh for the visiting associate professor post. Throughout his academic career, he has (co) authored almost 50 journal articles and given numerous talks and presentations.

What Ceyhan enjoys most about applied mathematics and statistics is data analysis, finding hidden patterns and studying trends in data. “I was always good in math in primary school,” he said. “I entered the university as a physics major and a year later, realized I liked math better, so I switched.”

Ceyhan is easy going and enjoys working with members of the SAMSI directorate, the staff and postdoctoral fellows and visitors that attend the institute. After Elvan took the position, he decided the best thing to do was to pick up where his predecessors had left off in order to increase awareness of how SAMSI supports applied math and statistics fields.

“I would like to continue our conventions and contribute more effort towards diversity in our programs,” said Ceyhan. He also believes SAMSI needs to continue to support heavily data science and big data programs, as these topics are major points of interest in the statistics community.

“I would like to continue our conventions and contribute more effort towards diversity in our programs,” said Ceyhan. He also believes SAMSI needs to continue to support heavily data science and big data programs, as these topics are major points of interest in the statistics community.

Among his many goals as deputy director, Ceyhan will work to expand education and outreach initiatives, support undergraduate workshops and programs and serve as an advisor to postdoctoral fellows in order to help them advance their research and academic careers.

Ceyhan resides with his wife, of nearly 10 years and his two children, daughter Gokce and son Melih. His family moved with him in 2016 when he took the visiting associate professor position in Pittsburgh. The family still misses Turkey and they hope to get back to the country next year to visit.

Ceyhan enjoys watching soccer and studying ancient history in his spare time. SAMSI is glad to have him in this new leadership role within the organization.

SAMSI Welcomes Leslie McClure as New Associate Director of Diversity

Leslie McClure, SAMSI Associate Director of Diversity
Leslie McClure, SAMSI Associate Director of Diversity

Since she began her academic career, Leslie McClure has always had a keen interest and respect for others. It is her passion for representing women and people of color in the mathematical sciences that led to her recently being appointed as the SAMSI Associate Director of Diversity in early August of this year.

“Throughout my education, particularly my undergraduate, I was often one of very few women in my classes, and rarely had female professors,” said McClure. “Women and people of color are represented in lower numbers in the professorate, and have even less representation in the higher levels of academics.”

McClure, who also currently serves as the Chair of the Department of Epidemiology and Biostatistics at the Dornsife School of Public Health at Drexel University, received her Bachelor’s Degree in Mathematics from the University of Kansas. She went on to receive a Master’s Degree in Preventive Medicine and Environmental Health from the University of Iowa and later, a Ph.D. in Biostatistics from the University of Michigan.

Before working at Drexel, McClure spent 11 years as a faculty member at the University of Alabama at Birmingham in the Department of Biostatistics.

“I gravitated towards biostatistics because it was a good fit with my interests, but I think I was also attracted to the field because it appeared more diverse than math,” said McClure.

McClure is a trained clinical trials statistician and her current research is focused on the methods that drive adaptive design in clinical trials, as well as the practical implications of implementing an adaptive design. She also works diligently trying to understand why racial inequalities exist in disease, particularly cardiovascular disease and stroke, and the role that the environment may play in those differences.

“Without diversity of people, we do not have diversity of ideas. Without diversity of ideas, we lose creativity in science, and fail to continue moving forward,” — Leslie McClure

Much like her research, McClure also works as a champion to find ways to make the field of mathematics more inclusive to women and under-represented minorities. “As I have pursued my own academic goals, I have also worked to increase and maintain diversity in the math sciences,” she said.

McClure is also part of the leadership for the National Alliance for Doctoral Studies in the Mathematical Sciences, where she serves as the Associate Director of Statistics. One of the main goals of the Math Alliance, located on the campus of Purdue University, is to foster the growth of the community of mathematical scientists in order to promote a diverse workforce.

SAMSI is proud to have added such an accomplished professional to the directorate. SAMSI believes whole-heartedly in creating an academic environment of equality and inclusivity for all. As the SAMSI Diversity Director, McClure will work with local universities and through her numerous contacts nationwide to research and implement strategies that will work towards advancing the careers of under-represented groups in the field mathematics.

McClure stays busy and focused. When she is not doing research or working for the betterment of others, she stays active running and spending time with her husband (who is a Chemistry Professor at Drexel) and their two children, Lillian and Preston. McClure also enjoys spending time with her dog, Bosco, watching Law and Order reruns.

“Without diversity of people, we do not have diversity of ideas. Without diversity of ideas, we lose creativity in science, and fail to continue moving forward,” said McClure.

SAMSI Kicks Off 2017-2018 Programs on Environment and High-Dimensional Data Sampling

Richard Smith, Director of SAMSI, opens the CLIM Opening Workshop at the N.C. Biotechnology Center on Aug. 21, 2017. The workshop marks the beginning of the CLIM Program, focused on using data and climate models to analyze environmental changes on our Earth.

Much like universities around the country beginning their fall semesters, SAMSI also kicked off their 2017-2018 year-long programs’ opening workshops: Mathematical and Statistical Methods for Climate and Earth Systems (CLIM) and Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applied Mathematics (QMC).

Late August was indeed a busy time for SAMSI as the opening workshops occurred in succession during the end of that month. The week-long CLIM Opening Workshop ran from Aug. 21-25 and the QMC Opening Workshop (Aug. 28 – Sept. 1) served as the starting point for both programs.

The CLIM Program looks at analyzing data and climate models to potentially predict future changes on our Earth that could directly impact our environment and the human population. The CLIM Opening Workshop featured many esteemed minds in the study environmental science. The opening workshop led to the creation of 13 working groups, whose overall purpose is to study various factors and data analysis in order to understand how our environment is evolving.

“Climate Science is important for many reasons in our society,” said Richard Smith, Director of SAMSI and Leader of the CLIM Program about the opening workshop. “It is not widely appreciated just how critical the role of mathematical and statistical methods play in climate science.”

More than 120 participants from universities around the world attended the popular workshop. Twenty-five speakers presented lectures on various topics about the science of the environment and how to use mathematical and statistical data to find the root to the causality seen in the modern world. The two panel discussions held during the workshop created much discussion and offered many contributions that led to the creation of the CLIM Program working groups.

The workshop participants were even treated to a rare solar eclipse that occurred over the continental United States during that time. To accommodate this rare event, organizers planned time during the opening day to go out and view the phenomena as it reached the totality phase. Everyone was excited as they used solar eclipse glasses and/or various safe methods to view the eclipse. The last time a solar eclipse could be viewed from the contiguous United States was Feb. 29, 1979. The eclipse was a special occurrence that was a happy coincidence to fall during the workshop and offered a perspective of how much we are shaped by the world around us.

As the opening workshop closed, participants chose the working groups they would be affiliated with for the remainder of the CLIM program. The workshop created valuable network opportunities between the scientists and mathematicians in attendance so that they can continue their research even after the CLIM program ends in May next year.

“This workshop brought together some of the top experts in climate science with the leading researchers in mathematics and statistics,” said Smith. “The lively discussions generated many ideas that will be developed during the rest of this [CLIM] program.”

Participants use multiple safe methods to view a solar eclipse during a break at the CLIM Program Opening Workshop on Aug 21, 2017. The eclipse was a special event that was viewed almost exclusively from the contiguous United States. Organizers planned time during the opening day to go out and view the phenomena as it reached the totality phase. The workshop marks the beginning of the CLIM Program, focused on using data and climate models to analyze environmental changes on our Earth.

The QMC Opening Workshop began the following week, Monday, Aug. 28, and was hosted at the beautiful Penn Pavilion on the campus of Duke University.

More than 110 mathematicians and statisticians check in for the QMC Program Opening Workshop on Aug. 28, 2017, at the Penn Pavilion, on the campus of Duke University. The goal of the QMC Program is to explore the potential of QMC and other deterministic, randomized and hybrid sampling methods for a wide range of applications, including the numerical solution of PDEs; machine learning; computer graphics; Markov chain sampling, like MCMC and MCQMC; sequential Monte Carlo; and uncertainty quantification.

This workshop brought together more than 110 mathematicians and statisticians, who collectively created 10 specific working groups focused on discussing ways in which they would research how to use big data across a wide range of practical applications.

“Kudos to the QMC Program Leaders Art Owen, Frances Kuo, Fred Hickernell and Pierre L’Ecuyer for getting the year-long SAMSI QMC off to a fantastic start,” said Ilse Ipsen, Associate Director of SAMSI and the QMC Program Leader. “Their commitment, combined with spot-on real-time assistance from SAMSI postdocs Cheng Cheng, Matthias Sachs and Whitney Huang, produced this lively Opening Workshop and an unusually large number of 10 promising working groups.”

The goal of the QMC Program is to explore the potential of QMC and other deterministic, randomized and hybrid sampling methods for a wide range of applications, including the numerical solution of PDEs; machine learning; computer graphics; Markov chain sampling, like MCMC and MCQMC; sequential Monte Carlo; and uncertainty quantification.

More than 20 speakers were invited to speak on a wide variety of sampling methods. The talks generated much discussion amongst participants and created the impetus for the working groups that were created.

Overall, the QMC Opening Workshop was well received by the participants and many looked forward to the future meetings in their respective working groups.

“The QMC Program is well on its way to being super-productive,” said Ipsen.

The research that will come from both the CLIM and QMC programs will help to address ways in which we can improve our environment, improve efficiency and productivity through random sampling across various applications, and advance technology. Research and collaboration are how SAMSI works to advance research in statistics and applied mathematics to innovate the future.

To see what was presented at these workshops, visit: www.samsi.info/clim-ow or www.samsi.info/qmc-ow; to view working groups, visit: www.samsi.info/working-groups.

Mathematicians and statisticians pose for a group photo at the conclusion of the QMC Program Opening Workshop on Sep. 1, 2017, at the Penn Pavilion, on the campus of Duke University. The workshop featured more than 20 speakers and led to the creation of 10 specific working groups focused on discussing ways in which they would research how to use big data across a wide range of practical applications. The goal of the QMC Program is to explore the potential of QMC and other deterministic, randomized and hybrid sampling methods for a wide range of applications, including the numerical solution of PDEs; machine learning; computer graphics; Markov chain sampling, like MCMC and MCQMC; sequential Monte Carlo; and uncertainty quantification.

2017-2018 SAMSI Postdoctoral Fellows

SAMSI welcomes the 2017-2018 Program Postdoctoral Fellows. These eight young professionals will spend the next two years working in their assigned programs: Program on Mathematical and Statistical Methods for Climate and the Earth System (CLIM) or the Program on Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applied Mathematics (QMC). This year’s postdoctoral fellows will bring their own unique talents to work for SAMSI’s programs. SAMSI is proud to present this year’s group!

Cheng Cheng

Cheng Cheng
Cheng is in the SAMSI QMC Program. She earned her Ph.D. in Mathematics from the University of Central Florida in 2017. Her research interests include applied and computational harmonic analysis, emphasis on sampling theory in signal processing, and high dimensional data analysis.

Yawen Guan

Yawen Guan
Yawen is in the SAMSI CLIM Program. She received her Ph.D. in statistics from Pennsylvania State University. During her graduate studies, she was fortunate to work with top scientists in the study of the Antarctic Ice Sheet. She was intrigued by the ice sheet physics and developed a statistical method to combine physics and multiple data sets to study ice streams on West Antarctica. Her research interests are spatial statistics, Bayesian modeling and computational methods for large data.

Huang Huang

Huang Huang
Huang is in the SAMSI CLIM Program. He received his Ph.D. in Statistics from King Abdullah University of Science & Technology (KAUST). His research experiences include computational methods for spatio-temporal statistics and functional data analysis. He enjoys using these statistical tools to collaborate with other scientists who have expertise in climate, oceanography, geophysics, etc., in order to explore interesting environmental problems.

Whitney Huang

Whitney Huang
Whitney is in the SAMSI CLIM Program. His research focuses on statistics of extremes and spatial, spatio-temporal data analysis with applications in climate. Ultimately, his research goal, as a statistician, is to bridge the gap between statistics and atmospheric/oceanic sciences. In his spare time he enjoys hiking, travel, and watching sports (basketball, tennis).

Maggie Johnson

Maggie Johnson
Maggie is in the SAMSI CLIM Program. She received her Ph.D. in Statistics from Iowa State University in 2017. Her broad research interests are in developing statistical methods for solving environmental problems. Some of her particular statistical research interests are in temporal and spatiotemporal statistics, Bayesian statistics, hierarchical modeling, and mixture models. She is originally from Minnesota where her family owns a Highland cattle farm, and in her spare time she enjoys cooking, fly-fishing, and woodcarving.

Mikael Kuusela

Mikael Kuusela
Mikael is in the SAMSI CLIM Program. He is a statistician working on data analysis methods for physical science applications. He is currently working on developing spatio-temporal interpolation techniques for analysis of oceanographic data from Argo profiling floats. In his free time, he enjoys traveling to far-away places, hiking in the summer and skiing in the winter.

Matthias Sachs

Matthias Sachs
Matthias is in the SAMSI QMC Program. During his Ph.D. he has have been working on numerical methods for ergodic stochastic differential equations. He has focused his efforts towards working on discretization methods for variants of the Langevin equation with applications in canonical sampling and molecular modelling. He is currently exploring the application of these models in sampling problems in Bayesian statistics and machine learning.

Christian Sampson

Christian Sampson
Christian is in the SAMSI CLIM Program. He just received his Ph.D. in mathematics from the University of Utah this year. His research interests lie at the interface between geophysics and mathematics. He is interested in sea ice and its role in the Earth’s climate system. While at SAMSI, he will be working with Professor Chris Jones at UNC Chapel Hill.

Graduate Students get Practical Experience in Math and Statistics Research at 2017 IMSM

A graduate student and her group present findings on a problem posed by one of the many program partners at the 2017 IMSM Workshop on the campus of North Carolina State University from July 17-26. The workshop exposes graduate students to methods used by industry and national labs to solve real world problems.

SAMSI completed the 2017 Industrial Math/Stat Modeling Workshop for Graduate Students (IMSM) this past summer. The event was held on the campus of North Carolina State University from July 17-26, and was attended by more than 40 graduate students from across the nation.

The IMSM is an annual educational outreach event that features collaborations with industry, national labs and other governmental organizations. During the workshop graduate students in mathematics, statistics and computational science disciplines are exposed to challenging real-world problems that arise in industrial and government laboratory research.

“This type of summer workshop has been held at N.C. State since 1995,” said Mansoor Haider, a Professor of Mathematics at N.C. State University and the workshop’s organizer.  “The IMSM name has been in place for well over a decade now. This reflects the importance of integrating statistics with mathematics and computation in solving modeling problems arising outside of academia.”

Several prominent leaders in industry and national labs provided first-hand experience and mentorship to the students. This year SAMSI was proud to partner with professionals from: Sandia National Laboratories; Rho, Inc.; U.S. Army Corps of Engineers, PAREXEL and the Environmental Protection Agency (EPA) among others.

This year’s partners presented problems to the attending students. The students were placed into research groups, and then collectively developed and implemented ways to resolve the issues at hand. The various partner representatives and workshop faculty members provided valuable mentorship and direction to the students. The students also received practical experience in problem-solving and first-hand experience in what it is like to work in a research group in a non-academic setting.

“The need for doctorally trained statisticians and mathematicians in industry and national labs is ever increasing,” said Haider.  “By immersing them in an intensive collaborative research experience, we hope to increase students’ awareness of the variety of career options after graduation, and the skills they will need to be successful.”

Graduate students attend a job fair, part of the 2017 IMSM Workshop, on the campus of North Carolina State University from July 17-26. The workshop exposed graduate students to future professional opportunities in the field of mathematics and statistics. It also helped to teach the students various methods used by industry and national labs to solve real world problems.

Some of the problems tackled by this year’s participants included:

  • How to integrate large-scale data from open source Google Earth Engine with air quality monitoring across the country in order to provide real-time air quality information to users.
  • Using coast line bathymetry data to assist in erosion control – to be used in predicting environmental effects after coastal storms or helping humanitarian aid logisticians to identify effective delivery methods by sea to provide critical relief.
  • Determining root causes of allergies in humans by studying the correlation and interactions between microbes in the environment and those inside the nose. Potential applications of this research aim to adapt the design of buildings and control exposure to identified allergens to reduce allergy and asthma among children at risk.

Participants put in long hours, sometimes well into the night. The students worked together and maximized the individual knowledge strengths of group participants to assist in solving their team’s assigned problem. After several days of team research and collaboration with group mentors and faculty, the groups reconvened and presented their findings to their peers and other academic professionals. The partners attending the workshop got valuable responses to the problems they posed, and in some instances, received insight into alternative research avenues or approaches to pursue in the future.

“For many students, this is their first experience tackling mathematical or statistical modeling problems outside of a university research setting,” said Haider.  “The workshop is intensive… It nicely mimics unique challenges in industrial research like identifying, formulating, and solving problems in a team, and then refining, coordinating, presenting and reporting on the results, all in a short time period.”

 The IMSM is one of the many ways SAMSI helps bring new talent together in order to collaborate with relevant applied math, statistics and computational science organizations. These workshops help to prepare and inspire those considering careers in science and math disciplines for the future.

For more on the Industrial Math/Stat Modeling Workshop and to see research presented from previous workshops, visit: www.samsi.info/imsm-history.

A program partner presents a clinical problem for the students to solve, as a group, during the 2017 IMSM Workshop. The workshop was held on the campus of North Carolina State University from July 17-26. The workshop exposes graduate students to methods used by industry and national labs to solve real world problems.

Transition Workshop brings SAMSI’s ASTRO Program to Close

SAMSI recently hosted an ASTRO Transition Workshop from May 8-10, 2017. The workshop was the final event of SAMSI’s Program on Statistical, Mathematical and Computational Methods for Astronomy (ASTRO) and was attended by numerous astrophysicists, astronomers and astrostatisticians from across the country.

Nearly 40 participants attended the workshop in order to discuss their findings compiled from multiple working groups formed throughout the past academic year. The organizing committee for the program listened to spokespersons from each group as they presented their findings. The group also discussed continuing future collaborations between these working groups once the program was over.

SAMSI’s ASTRO program liaison and Deputy Director, Sujit Ghosh, noted that the ASTRO program has been successful in creating a cohesive bond between the statistical and mathematical sciences and the disciplinary sciences, like astronomy and astrophysics. According to Ghosh, this coupling is helping to systematically streamline the analysis of huge data sets that are produced from the Laser Interferometer Gravitational-Wave Observatory (LIGO), gravitational wave (GW) research and exoplanet discoveries.

A panel, consisting of ASTRO program leaders, collected feedback from the numerous researchers in attendance. A significant issue that researchers brought up was the challenge of publishing research articles in domain sciences (i.e. core stat or astrophysics journals) versus the disciplinary sciences. This issue was viewed as a significant obstacle when using these research papers as a reference for tenure-based decisions. The panel of program leaders could not determine the best way to address this situation. Instead they agreed that this topic should be readdressed during future interdisciplinary engagements, like transition workshops.

“This [ICTS-SAMSI] workshop helped form several collaborations to enable what will likely prove to be a fruitful collaboration among people from diverse backgrounds that can propel the progress of science”

Overall, the ASTRO Program focused on ways to create solid partnerships between researchers in applied mathematics, astronomy, astrophysics and statistics (professionals who do not ordinarily work together in the field). In fact, the concept of astrostatistics emerged from numerous collaborations, like this one, between researchers during past SAMSI programs. The partnerships created by this program are important because they could potentially advance research in astronomy. In addition, three mid-program workshops (one on Exoplanets in the Fall of 2016 and two on Synoptic Surveys and GW Astronomy and Astrophysical Population Emulation in the Spring of 2017) were organized by the researchers to support the program during the past year.

SAMSI also expanded its international collaboration capability by organizing a joint workshop with the International Center for Theoretical Sciences (ICTS) in

Bengaluru, India. This workshop enabled scientists to share their ideas and work together across two continents in order to explore the grand challenges in gravitational waves time domain astronomy.

“SAMSI workshops and working groups have helped me understand how my thesis work fits into the larger scientific picture and how to gain a better understanding of what our science priorities are as a community of observational astronomers,” said Jackeline Moreno, a graduate student at Drexel University, who was a member of one of the working groups. Moreno said she was impressed with how the joint workshop brought together experts from around the world and from different research backgrounds to come together and share techniques and insights for analyzing time series data.

Kaustabh Vaghmare, a data scientist from the Inter -University Center for Astronomy and Astrophysics (IUCAA) in Pune, India, who also attended the ICTS-SAMSI workshop, agreed. Vaghmare began by saying that time domain astronomy has improved a great deal in the last decade, due in large part, to advances in robotic telescopes, image processing and database technologies. These advances, according to Vaghmare, have given astronomers the ability to organize several systematic surveys of the sky. In addition to those advances though, Vaghmare sited the importance of the human aspect as a valuable way of sharing information. “This [ICTS-SAMSI] workshop helped form several collaborations to enable what will likely prove to be a fruitful collaboration among people from diverse backgrounds that can propel the progress of science,” he said.

Joint workshops, like the ICTS-SAMSI workshop, help SAMSI to emphasize the value of collaborating with other institutions or across fields of study. The results of these collaborations creates more dynamic ways to solve traditional problems using the tools of applied mathematics and statistics as a guide.

The program offered academic courses on Analytical Methods and Applications to Astrophysics and Astronomy in the fall of 2016 and Time Series Methods for Astronomy this past spring. The program also provided numerous opportunities for graduate and undergraduate students to participate and see what future opportunities are available to them in the field of astronomy from a mathematician’s point of view.

As the ASTRO Program transitions, SAMSI sets its sights on the two new 2017-2018 programs: Program on Mathematical and Statistical Methods for Climate and the Earth System (CLIM) and the Program on Quasi-Monte Carlo and High Dimensional Sampling Methods for Applied Mathematics (QMC). Both programs open this August and will end in May 2018.