Dr. Lung-Chang Chien is an Associate Professor of Biostatistics in the Department of Epidemiology and Biostatistics, School of Public Health. His research focuses on investigating spatial vulnerability and geographic disparities on human health. His research topics cover socioeconomic deprivation in cancer incidence and mortality, modifying effects of location in geo-survival analysis, the impact of Asian dust storms on children’s health, geographic disparities of asthma and diabetes, spatiotemporal impacts of meteorological factors on dengue fever, and high risk areas in elderly mortality due to heat waves. Dr. Chien has also collaborated on publications in Nursing research, global health, physical therapy, and nutrition.
Jonathan Beardsley
My research interests are in category theory, algebraic topology, and homotopy theory. I am specifically interested in using homotopical or “derived” algebra, in the form of operads, spectra, and infinity categories, to understand and classify structures that naturally arise in geometry and topology. Some geometric structures that I have specifically studied in previous work or am currently interested in include: cohomological invariants of topological spaces, the stable homotopy groups of spheres, the relationships between cobordism rings as the structure group is varied, A-infinity categories.
Diana Moss
My research agenda has transitioned from understanding how children make sense of mathematics in classroom settings to investigating pre-service teachers’ learning in mathematics methods courses and mathematics content courses. This transition occurred because I wanted to do research that would make a difference in my own teaching practice. At my first milestone and dissertation, I learned to study children’s learning of mathematics, specifically algebra, in a classroom setting. My second milestone was my third-year review and reappointment at Appalachian State University where I transitioned to learning to study pre-service teachers’ learning of mathematics. My third milestone occurred when I became an assistant professor at Utah State University and reframed my research to study pre-service teachers’ learning of mathematics and methods. My fourth milestone occurred when I became a teaching assistant professor at University of Nevada, Reno in the midst of the pandemic and focused on teaching mathematics content courses in an online synchronous setting and face-to-face setting. I have actively pursued practitioner research with the intention of “providing insights into teaching in an effort to make change” (Dana & Yendol-Hoppey, 2014, p. 9). Since 2018, I have been involved in research projects to help me engage in reflective practice and bring about positive change in my teaching. The projects are separate in nature, but all strive to connect my teaching philosophy, the course learning goals, teaching activity, and evidence of student learning. The purpose of each project is to analyze and transform teaching to create new learning experiences that focus on conceptual understanding based on meaningful reflections on teaching.
Aaron Wong
My background is in analytic number theory, but I’ve mentored projects in a number of other areas including algebra and probability. I also have a background in data science and machine learning.
Ping Wang
Ping Wang is a mathematics instructor at Great Basin College (GBC). She was the former director of Academic Success and Testing Center (ASC) at GBC. Ping Wang has worked in higher education for 12 years, and has always been passionate and dedicated to promoting students’ success, both academically and professionally. Currently, Ping Wang is working on her Ph.D. degree in Education at the University of Nevada, Reno, with the emphasis of educational information and technology.
Andrey Sarantsev
I did my PhD at the University of Washington, Seattle, in the area of Stochastic Processes. After that, I worked at the University of California, Santa Barbara, as a Visiting Assistant Professor. From 2018, I worked as a permanent faculty member at the University of Nevada, Reno, Department of Mathematics & Statistics.
Tom Kozubowski
Following a graduate study of applied mathematics at the University of Warsaw, Poland, Dr. Tomasz J. Kozubowski received MS in Statistics from the University of Texas, El Paso, and Ph.D. in Statistics and Applied Probability from University of California, Santa Barbara. He is currently a Professor in the Department of Mathematics & Statistics at the University of Nevada, Reno.
Dr. Kozubowski works in the general area of stochastic modeling of natural phenomena in variety of fields, including climate research, geosciences, finance, and economics. His research interests include distribution theory, Laplace distribution and its generalizations, limit theory for random sums, heavy tailed distributions, extremes, mathematical statistics, financial and insurance mathematics, stochastic models for hydro-climatic phenomena, and fractal scaling processes. He has co-authored 120 research publications in probability and statistics, including two monographs.
Dr. Kozubowski is currently an editorial board member of several academic journals and an active reviewer, having refereed for over 100 different academic journals. With the 2016 Sentinel of Science Reward, he was recognized by Publons as one of the top researchers contributing to the peer review in the field of mathematics.
Tin-Yau Tam
Professor Tin-Yau Tam received his B.Sc. in 1982 and Ph.D. (Mathematics) in 1986, both from the University of Hong Kong in 1986. He currently serves as the Department Mathematics and Statistics Chair & Professor, and Seneca C. and Mary B. Weeks Chair of Mathematics at the University of Nevada, Reno (UNR). He was selected as Lloyd and Sandra Nix Endowed Professor (2012-2015) at Auburn University, Department of Mathematics and Statistics Chair (2012-2018), Director of Assessment and Planning (2000-2012) for the College of Sciences and Mathematics (2020-2012) before he joined UNR. Tam’s areas of specialization are Matrix Theory, Multilinear Algebra, Numerical Ranges, Differential Geometry, Lie Theory, and their applications. To date, Tam has authored or coauthored about 115 research papers (35 are single-authored papers) and a research monograph Matrix Inequalities and their Extensions to Lie Groups, CRC/Taylor & Francis Group, 2018. He serves on the editorial boards of three peer-reviewed math journals: Linear and Multilinear Algebra, Electronic Linear Algebra, and Special Matrices. He has delivered more than 250 talks and a few of them were keynote lectures and plenary talks. He has organized many international math workshops and conferences. Tam has graduated 10 Ph.D. students. He served on the Board of Director (2009-2013) and the Advisory Committee (2020-2022) of the International Linear Algebra Society. He currently serves on the Scientific Committee of the International Research Center on Tensor and Matrix Theory at Shanghai University (since 2016) and the Board of Governors of Pacific Journal of Mathematics (since 2021).
Scott Morrison
Scott has served as WNC’s Accreditation Liaison Officer with NWCCU since 2017 and as an NWCCU evaluator since 2015. Scott’s recent accomplishments include partnering with colleagues and communities on dual credit to build WNC’s Jump Start College Program, expanding cohorts to support underserved populations, revising WNC’s learning outcomes and assessment practices to align with institutional goals, and helping to lead a full revision of the Western’s strategic plan.
Sungju Moon
My research interest lies in applications of dynamical systems, more specifically, the study of nonlinear ODEs to model complex systems. Of particular interest is the Lorenz system, well-known for the so-called “butterfly effect”. Broadly, I am open to new ideas for applying dynamical systems to model real world scenarios.
My PhD project was concerned with deriving and exploring chaotic properties of new high-dimensional extensions of the Lorenz system, viewed as closer approximations of the Boussinesq fluid model for Rayleigh-Benard convection. Beyond the initial motivation for considering additional physical contexts under specific scenarios such as the presence of vertical gradient in scalar concentrations as in atmospheric aerosols or ocean water salinity, this project evolved into a quest to answer more fundamental questions about the chaotic nature of weather and fluid systems, leading to the derivation of a generalized high-dimensional Lorenz systems capable of furnishing an ODE system that represents a fluid system with arbitrarily high harmonic orders. Some interesting phenomena discovered along the way include a novel type of chaotic attractor, coexisting attractors, and synchronization of chaos, which led to some immediate applications in different fields such as image encryption technology and data assimilation in the context of numerical weather prediction. My ongoing research explores how different network configurations could change the synchronization properties, with certain configurations more prone to rare catastrophic events than others.
As a member of the Mathematics Public Health (MfPH) network at The Fields Institute, I had the opportunity to work on agent-based models for epidemic curves of a rapidly spreading infectious disease such as COVID-19. I focused on developing co-circulation models having two or more viral strains, utilizing both the traditional ODE-based approach (SIR) and the agent-based modeling (ABM) approach. My ongoing research in this area is focused on exploring how the infection network heterogeneity affects the epidemic curves and whether these effects can better be simulated using ABMs rather than ODEs.