Each year SAMSI welcomes a new crop of postdoctoral researchers that support their annual academic programs. This year, SAMSI welcomes five new researchers who are focused on supporting the 2018-19 PMED and MUMS Programs.
Supporting the Program on Statistical, Mathematical and Computational Methods for Precision Medicine (PMED)
Xinyi Li received her Ph.D. in Statistics from Iowa State University in 2018, under the supervision of Dr. Lily Wang. Her research interests are in developing statistical methods as well as designing computational algorithms in sparse learning, functional data analysis, and high-dimensional nonparametric regression. Her application areas include neuroimaging, genomics, and public health. In her spare time she enjoys sports (badminton, hiking, skiing, etc), reading and watching sports (tennis, football, badminton, etc).
John Nardini received his Ph.D. from the University of Colorado, Boulder, where his dissertation was on mathematical models of epidermal wound healing. He is interested in the derivation and analysis of partial differential equation models of biological phenomena, as well as inverse problems to fit these models to experimental data. While at SAMSI, he will be working with Professors Kevin Flores from NC State and Greg Forest from UNC Chapel Hill.
Supporting the Program on Model Uncertainty: Mathematical and Statistical (MUMS)
Pulong Ma received his Ph.D. in Statistics from University of Cincinnati. He has worked on spatial and spatio-temporal statistics with applications in remote-sensing science and climate science in his dissertation. In particular, he developed flexible (e.g., nonstationary and non-separable) covariance function models for massive spatial and spatio-temporal datasets. He also proposed a statistical downscaling framework to simulate high-resolution geophysical fields in global observing system simulation experiments (OSSEs). While at SAMSI, he will be working with Professor Jim Berger, from Duke University, in the area of uncertainty quantification (UQ). He is currently exploring interesting applications with focus on building statistical emulators for expensive computer models.
Wenjia Wang received his Ph.D. in Operations Research from Industrial and Systems Engineering, Georgia Tech. His research interests are focused on statistical modeling, statistical design and theoretical analysis of Gaussian process as well as Kriging. He is also interested in their applications in computer experiments, machine learning and uncertainty quantification.
Lei Yang earned her Ph.D. in Statistics from Colorado State University in 2018. During her Ph.D. study, she developed theoretical framework and computational methods for stochastic inverse problem, which turns out to be related to generalized fiducial inference. She is also interested in bayesian projected normal time series model applied to protein sequence data as well. At her spare time, she enjoys swimming and getting hands dirty on predictive modeling projects.
The MUMS program brings together statisticians and applied mathematicians with disciplinary scientists from a wide-range of fields to understand the effects of modeling and uncertainty on predictions. The focus of the workshop was to layout the foundations for the MUMS program by examining the theoretical basis for statistical uncertainty, the strengths and weaknesses of models of real world processes and the uncertainty of those processes.
The workshop featured statisticians, mathematicians and data science researchers who presented their talks on how model uncertainty and uncertainty quantification methodologies can be used across a broad spectrum of subjects.
“The kickoff meeting brought together the world leaders in uncertainty quantification, many of
whom continue to work and interact at SAMSI as long-term visitors,” said David Banks, Director of SAMSI and the program’s directorate liaison. “Additionally, the participants are teaching a graduate course in model uncertainty,
which has drawn in students from all over the Triangle.”
In addition to the working groups, a fall course is being presented for graduate students that introduces statistical and mathematical sensitivity analysis and uncertainty quantification techniques for large-scale models arising in current applications. The course is ongoing through December.
“The MUMS program is a classic melding of applied mathematics and statistics,” said Banks.
“Uncertainty quantification is an exciting new field, with important applications in weather forecasting, modeling of pyroclastic flows, and materials science,
The working groups will meet throughout the academic year and discuss ways to use these uncertainty principles in a diverse variety of disciplines, such as: engineering, probability, operations research and machine learning, just to name a few.
“One of the grand challenges scientists face is how to make probability statements when the model is so complex and intractable that it cannot be studied with standard tools from mathematical statistics,” said Banks. “The MUMS program provides a general solution strategy, by approximating the complex model with Gaussian processes. Bayesian methods enable the scientist to not only fit the most accurate Gaussian process, but also to estimate a discrepancy function, which indicates where the approximation is poor.”
The goal of the PMED program is to bring together mathematical, statistical, computational, and biomedical scientists in order to develop innovative advances in data-driven, quantitative methodology for precision medicine.
“Personalized medicine is a recently developed hot area in bio medicine and medicine that is about custom-tailoring treatments, medicines and interventions for the individual person,” said Elvan Ceyhan, Deputy Director of SAMSI and a directorate liaison for the PMED Program. “There are a lot of methodological, statistical and mathematical and practical challenges, so there is a dire need to address these issues.”
Researchers from all over the United States attended the week-long event that opened SAMSI’s 2018-19 academic programs. There were numerous talks from some of the most influential minds in biomedicine, applied mathematics and statistics. The researchers highlighted a wide-range of methodologies and approaches used in precision medicine
“I have been interested in this general area for quite some time…I am a biostatistician, so I work with problems in the health sciences,” said Marie Davidian, professor of statistics in the Department of Statistics at NCSU and a local scientific contributor to the PMED program. “This is the big challenge in how science research can personalize treatment to the patient. My research area involves statistical methodologies directed toward that goal.”
PMED produced eight working groups and one subgroup for this academic program year. The working groups will focus primarily on medical issues that require more refined and accurate data derived by biostatisticians, applied mathematicians and other researchers.
“In general, in regular medicine, statistics is applied for the average person, but an average person is not really a person as much as it is median data point, there is no ‘average person,’ said Ceyhan. “In personalized medicine, each person is an individual and different. In this field, the treatment would be customized to the individual, which causes a lot of uncertainty from person to person and unexpected outcomes. Statistics is very useful in predicting bounds or quantifying those uncertainties.”
This SAMSI workshop is helping to bring together a diverse group of professionals who do not ordinarily collaborate. Programs like this one in precision medicine are forging a path towards using more dynamic and broad-based methods to ensure that more effective and efficient medicines and treatments can be used to improve an individual’s healthcare needs.
“What strikes me, just from the talks I’ve seen, is the diversity of the approaches that different disciplines are taking to address these problems,” said Davidian.
Davidian is hopeful that the internal collaborations on the working groups lead to some innovative approaches as to how statisticians can make an impact into improving precision medicine.
The issues being discussed are not only beneficial to the more senior researchers, but also to the next generation of statisticians – Master of Science and Ph.D. students.
“The thought of personalized medicine and tailoring treatments to individual characteristics is exciting to me,” said Yeng Saanchi, a statistics student enrolled in the graduate program at NCSU. “I don’t think giving generic treatments to everybody, irrespective of their individuality is the way to go, especially if we want healthcare to be efficient and effective.”
Saanchi appreciated the opportunity to have access to a large number of experts in her field and in medicine. In many ways it has helped her to realize where her talents in statistics can be valuable.
“Aside from the great exposure to the work that is being done in the field in precision medicine and meeting all of these knowledgeable people and talking to them about their work, I hope to be able to see how my research could possibly tie into the personalized medicine field,” she said.
“SAMSI workshops are great in order to get a conversation started about a particular subject and building networks to address various problem definitions in those subjects,” said Ceyhan. “SAMSI is very experienced in this…We have received positive feedback already from participants that they have met new people from new areas of study and they look forward to further collaborations.”
In addition to the opening workshop and working group research, the PMED program will also host a spring course for graduate students in 2019. It will be interesting to see what new and innovative ideas come out of this experience.
Almost 40 students from more than 30 universities nationwide attended the annual workshop that began in 1993. The workshop offered students something they don’t ordinarily get in a classroom and gave them a snapshot of life as a data science researcher.
“Students worked in groups of six or seven on problems that came from industry or national labs,” said Mansoor Haider, who is an Associate Director at SAMSI, a professor in the math department at N.C. State University and also Chair of the IMSM workshop. “It’s often their first experience working on problem solving, using mathematics and statistics that come from folks outside of academia.”
From day one of the workshop, the students in attendance relied, not just on their personal knowledge of mathematics, but also on developing relationships with their peers so that they could work together as a team to present their findings. The collaborative environment is intentionally setup each year in order to mirror current industry trends.
“The thing that I think is really unique about IMSM is that it’s a short period of time where you really have to work collaboratively to get something done,” said Grant Weller, a Vice President for Research at Savvysherpa, a division of the United Healthcare Group. “The projects we [Savvysherpa] tend to work on are very large and require collaborative work and people of different backgrounds and disciplines working with each other. It’s been impressive to see how this group has come together.”
Weller is very familiar with SAMSI. He supported the 2011-2012 Uncertainty Quantification Program as a graduate student visitor. Like Weller, many former SAMSI undergraduate and graduate students and postdocs come back to attend SAMSI programs and workshops later in their professional and academic careers. They share their knowledge and their experience with the next crop of talented applied mathematicians, statisticians and computer scientists.
This year’s supporting organizations included:
Saavysherpa (a division of the United Healthcare group)
MIT – Lincoln Laboratories
Sandia National Laboratories
Rho – a national drug development company
The U.S. Environmental Protection Agency (EPA)
The US Army Corps of Engineers (USACE)
“This was the first workshop I have been to of this kind and I wanted to get a feel what a job in industry would be like and this workshop was a really good experience for me in terms of that,” said Michael Byrne, an attending graduate student enrolled in the applied math Ph.D. program at Arizona State University. “It was a great opportunity for me to work with other people that are industry-minded and to get an idea of what people do in industry on a daily basis.”
In addition, to their group research, students also participated in a short career fair where they got an opportunity to connect and network with this year’s partner organizations. Companies and organizations often comment that there is a shortage of math and statistical science students to fill the critical roles they need to address their current research. IMSM helps to potentially fill that void.
“We really viewed this as an opportunity to connect and develop relationships with SAMSI, which is a great research institution in statistics and applied mathematical sciences, and is the primary focus of what we [Savvysherpa] do,” said Weller.
At the end of week-long event, each group presented their findings to their peers and faculty and industry mentors. The students walked away from the experience with a new perspective on how research is conducted and they also walked away with new contacts and friendships from the experience.
There is a proverb that states, “March comes in like a lion and out like a lamb.” It is a proverb that truly explains the extreme swings of the weather effects on our environment.
Much like this proverb, the Program on Mathematical and Statistical Methods for Climate and the Earth System (CLIM ) also came in like a lion and then transitioned quietly this May to complete another successful SAMSI year-long program.
The CLIM Program began in spectacular fashion with a solar eclipse, followed by the first of three devastating hurricanes to hit the United States in the summer of 2017 – and that was just the opening workshop!
During the academic year, the CLIM program hosted a distinguished atmospheric scientist from MIT, Kerry Emanuel. Widely regarded as the world’s leading hurricane expert, Emanuel gave a fascinating talk the future of hurricanes and how changes in our environment are causing these storms to become more and more intense.
A research course for graduate students was also hosted in the fall semester, called “Statistics for Climate Research.” The course was taught by seven different instructors who were part of the nearly 15 academic visitors for the CLIM program. Over 20 students registered for the course (plus several auditors in regular attendance) with students from departments such as Marine Sciences at UNC and Economics at NCSU, in addition to the local mathematics and statistics departments. The fall course was followed up by a spring course that covered statistical and computational methods for the analysis of data arising from climate research.
The program was a huge success and it attracted some of the most talented minds in environmental research today. The Transition Workshop met in May and each working group presented their findings to their peers that addressed their particular research topic.
Though the CLIM Program has transitioned, the research captured during the program is still ongoing and the environmental and applied math and statistical scientists will continue to collaborate for further study. To see an overview of the CLIM program, visit: https://www.samsi.info/clim.
SAMSI completed their Undergraduate Modeling Workshop in May. The week-long workshop brought more than 30 undergraduate students from across the country together to understand how applied mathematics, statistics and computer science technologies can be used to interpret and predict ongoing changes in our environment.
“In this workshop, we wanted undergraduates from mostly quantitative fields to experience the mathematical/statistical applications in climate research,” said Elvan Ceyhan, SAMSI’s Deputy Director. Ceyhan was also an organizer of the workshop.
The workshop gave students valuable experience in how modern research is conducted, while also encouraging them to enter careers in the math sciences. Because of this workshop, many students became aware of how much applied mathematical, computer science-based and statistical concepts are used environmental research.
Students listened to researchers in the fields of applied mathematics, statistics and environmental research. The researchers lectured on how applied math and statistics work in concert with scientific data to help build models for study of the factors that affect various elements of our environment, such as ocean temperature, air quality and seasonal variations in vegetation in a given region.
Students also learned some basics about R Software, which is widely used to crunch data for the purpose of building simulations, plotting variances and finding trends to predict change in a given subject.
“The ‘SAMSI 2018 May UG Workshop’ was very helpful in broadening my knowledge about not just Statistical Modeling but Machine Learning as well – I learned new things which I would not have otherwise,” said Chandini Malhorta, a statistics major at NC State University (NCSU). “The multiple R-sessions, especially the ones on Spatial Statistics by Doug [Nychka] and Andrew [Finley] were quite helpful, this was something which I would have never learned in my entire Undergraduate had I not attended their session.”
Students worked in various groups and were guided and mentored by SAMSI postdoctoral fellows and workshop leaders. The student groups presented their findings on the following topics:
The students wrapped up the week by presenting their findings to their peers and fellow mentors.
“The lecturers and post-docs really have broadened my horizon and expanded my network,” said Rice University Junior, Hongyu Mao. “This workshop connected us to many friends of the same interests and we learned from each other.”
“In a week’s time, the students showed impressive progress and had some tangible results to present at the end,” said Ceyhan.
The subjects presented challenged the students, in a group setting, to give them practical experience working together to solve problems. SAMSI hosts multiple education and outreach opportunities like this annually as a way to raise awareness for the importance of applied math and statistics. To see more of what was presented and discussed at this workshop, visit the web page: https://www.samsi.info/18-ugrad-modeling.
At the end of May, SAMSI hosted a transition workshop, bringing a close to their Program on Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applied Mathematics (QMC).
The workshop was the culminating event of the year-long QMC program and brought together more than 100 researchers from around the world to discuss a multitude of ways in which QMC methodologies could be used to improve such things as data sampling; process efficiency and troubleshooting systems; and how these concepts can be integrated into machine learning or computer-based technologies.
“The SAMSI QMC program, small but highly productive, set a perfect example of SAMSI’s mission: Mathematicians and statisticians working together to create new foundations and computational methods, with a future view towards solving challenging technological problems: making power grids more reliable by preventing break downs, and making nuclear reactors safer by tightly monitoring the nuclear reactions (criticality),” said Ilse Ipsen, program organizer and former SAMSI associate director. Ipsen is also a mathematics professor at NC State University
The QMC year began with an opening working last August, followed by mid-term workshops at Duke University and the Alan Turing Institute in the UK, and officially ending with this transition workshop.
Program participants from all over the world (Austria, Australia, Canada, Germany, the UK, and the US) reviewed the impressive accomplishments of ten productive working groups over the past year, which included:
fast methods for sampling reliably and efficiently;
validation procedures for guaranteeing that the samples are indeed representative;
robust methods for performing effective sampling under less than ideal (uncertain, noisy) conditions; and
user-friendly software for automating the complex sampling processes, and visualizing the location of the samples.
“QMC has a rich and deep theory that has found a handful of extremely suitable use cases, but I am convinced that there are more to discover,” said Art Owen, a QMC program leader and a statistics professor at Stanford University. “The SAMSI program built bridges to US based researchers, especially in engineering related applications.”
The transition workshop was an opportunity for the program researchers to reconvene and to discuss their findings from the past year in their research. It also gave the program participants a way to reconnect with colleagues and discuss future collaborations about their research.
“During the lively discussion sessions it was often hard to tell who was a mathematician and who a statistician — an indication of the close collaborations and the growing synthesis of mathematics and statistics,” said Ipsen. “The workshop participants are now looking beyond the SAMSI program, by organizing future workshops and continuing their virtual webex meetings — whatever it takes to ensure the thriving of the research community formed during the SAMSI QMC year.
“The QMC Program has fulfilled its main objective: Strengthening the community of researchers who work on Quasi-Monte Carlo methods and the related area of Probabilistic Numerics; and raising the visibility of these vital research areas in the US,” said Ipsen.
“I am personally grateful to all three of these professionals for having taken on these jobs,” said SAMSI Director, David Banks. “It is especially critical during a NSF renewal cycle, and I look forward to working with them as we advance the SAMSI mission.”
Dasmohaptra joined Duke in September 2017, where she has served as the Director of the Masters in Statistical Science Program. She had previously served at NCSU as an Associate Professor in Marketing Analytics at the Institute in Advanced Analytics. She has a well-established background in working with industry partners, government and non-profit organizations, as well as academia.
“I am very excited to join SAMSI to build and maintain a climate that fosters diversity and inclusiveness on an ongoing basis through collaborative relationships with a broad and diverse constituency,” said Dasmohaptra about beginning her new role at SAMSI.
Her research interests include: customer and marketing analytics, focused primarily on quantitative data analysis; data management; predictive modeling; and web and digital analytics, just to name a few. Sudipta hopes to continue the work in SAMSI’s diversity program that McClure began last year. Her focus as diversity director will be to further develop SAMSI’s diversity initiatives, identifying opportunities for under-represented groups to participate in SAMSI programs, workshops and special events.
Greg Forest will assume the role of Associate Director vacated by former Associate Director and Director, Richard Smith. Smith, who was the Director of SAMSI since 2010, stepped down after David Banks took over as Director in January 2018. Smith then moved to an associate director position to help facilitate the transition before going back to academic research.
Forest’s research is focused primarily on biomedical technologies and how those enhancements can improve modern medicine. He is also heavily involved in nanoparticle drug strategies for human cancer; studying the correlations between mathematics and multiple applied science challenges; gaining understanding virology and immunology and much more.
Lastly, Mansoor Haider fills out the new list of recent appointees in the directorate at SAMSI.
Haider will be replacing long-time Associate Director, Ilse Ipsen. Ipsen and Haider are both mathematics professors at NCSU. Ipsen has been an Associate Director at SAMSI since 2011.
“I am excited to join the SAMSI directorate and work with leading scientists from the triangle universities in order to advance SAMSI’s mission,” said Haider of his new appointment.
Haider is an applied mathematician who has been a member of the faculty at NCSU since 1999. His focus is on interdisciplinary research, primarily the application of mathematical and computational models to problems in the life sciences. In addition, Haider also served as Director of Graduate Programs for the Department of Mathematics from 2012-2016.
Haider, who is no stranger to SAMSI, has served as an organizer of numerous SAMSI programs and workshops. “I am looking forward to developing creative strategies for integrating SAMSI’s research programs with mathematical sciences training at all levels [postdoc, grad, undergrad],” Haider said.
Haider also serves as the current Chair of the Industrial Math/Statistical Modeling Workshop (IMSM) for Graduate Students (he has previously served as this committee’s chair in 2017 and 2004 and 2005). IMSM is a joint venture between SAMSI and NCSU that serves as an education and outreach opportunity for graduate students.
“I am particularly grateful to Ilse Ipsen and Richard Smith for their leadership in advancing the mission of our Institute,” said Banks of the outgoing directorate members.
“Ilse ensured the prominence of applied mathematics in the SAMSI portfolio through the creation and facilitation of several spectacularly successful programs, and through the recruitment and mentoring of outstanding postdoctoral fellows. Richard contributed hugely to SAMSI as well —he was the former director, and kindly agreed to stay on for an additional six months to facilitate the transition of new directorate members. Richard’s vision and stewardship ensured the survival of SAMSI, and did much to shape its current form. Both Ilse and Richard will be missed,” said Banks.
This new group of leaders will help to bring a fresh perspective on how best to advance SAMSI’s role in applied mathematics, statistics and the computational sciences. SAMSI staff welcomes these new members and looks forward to working together with them well into the future.
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 highlights trends and demographic data of women, people with disabilities and minorities from three racial and ethnic groups – African-American,
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.
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.
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.