School of Mathematical Sciences
School of
Mathematical Sciences
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Overview
The School of Mathematical Sciences is recognized for its contributions to research and applications of mathematical and statistical science, and it’s also known for expertise in mathematical and computational modeling, data science, and scientific inference. Since mathematics is at the root of many social, technical, medical, and environmental issues faced by society today, we equip our graduates with a deep understanding of mathematical and statistical principles, tools to apply those skills to realworld problems, and the ability to express complex ideas in everyday language. We provide our students with research and experiential learning opportunities and nurture curiosity and creativity.
1^{st}
Mathematical modeling Ph.D. program in the nation
3:1
Studenttofaculty ratio
2
NSF Funded Research Experiences for Undergraduates (REU) Programs
Latest News

September 9, 2020
RIT scientists contribute to the first discovery of an intermediatemass black hole
The LIGO Scientific Collaboration and the Virgo Collaboration recently announced the discovery of GW190521, the most massive gravitational wave binary observed to date, and Rochester Institute of Technology scientists played an important role in identifying and analyzing the event.

September 2, 2020
New mathematical method shows how climate change led to the fall of an ancient civilization
Nishant Malik, assistant professor in RIT’s School of Mathematical Sciences, has developed a mathematical method that shows how shifting monsoon patterns led to the demise of the Indus Valley Civilization, a Bronze Age civilization contemporary to Mesopotamia and ancient Egypt.

August 12, 2020
FacultyStudent Collaboration Responsible for COVID Modeling Development
Two RIT students collaborated with faculty and coauthored their first paper which contributes to the body of knowledge surrounding the COVID19 pandemic.
Research
Current research in the unit involves developing mathematical frameworks to discern properties of a system by working backward from known effects. Application areas include medicine, engineering, finance, earth science and imaging and the focus is on investigating the impact of uncertainty in data, identification of cancer in soft tissues, estimation of material properties, identification of market volatility, and developing fast and reliable methods for large scale computational optimization.
Research Active Faculty:
Current work in the unit includes research and consulting in biostatistics, machine learning, data science, predictive analytics, signals processing, statistical education, and statistical/scientific inference with applications to biology, astrophysics, and engineering.
Research Active Faculty:
Current research in the unit involves developing improved mathematical models of physiological systems; gaining new insights into mechanisms of physiological behavior; improving techniques for diagnosing and treating diseases; and devising advanced algorithms for analyzing physiological measurements.
Research Active Faculty:
Current work in the unit involves developing graphbased models of the brain to study the impact of concussions, improving and developing new graphbased algorithms for hyperspectral image analysis, applying the growing concepts of complex network analysis to domainbased scientific problems, and applying algebraic techniques and methods to problems in cybersecurity.
Research Active Faculty:
Current work in the unit involves applying mathematical techniques of nonlinear dynamical systems to problems in fluid dynamics, climate modeling, population modeling, cell signaling dynamics, and more; developing mathematical models of thin film and interfacial flows with application to biological fluids, microfluidics devices, and industrial coating processes; gaining insights that lead to better prediction of hydrodynamic instabilities, such as turbulence, liquid fuel atomization, and liquid film breakup; devising novel computational methods to simulate fluid transport phenomena; and improving the current understanding of polymer flows and viscoelastic fluids.
Research Active Faculty:
Current work in the unit includes applications of differential geometry, numerical solutions of partial differential equations, and statistical inference to problems related to general relativity and celestial mechanics. Einstein's general theory of relativity is studied as a description of the geometry of spacetime. Advanced numerical and computational techniques are used to solve the coupled, nonlinear, system of PDEs of General Relativity and MagnetoHydrodynamics. As part of the LIGO Scientific Collaboration, SMS faculty and researchers use statistical signal processing techniques to search for, identify and characterize gravitationalwave signals from astrophysical systems.
Research Active Faculty:
Current work in the unit involves developing new mathematical techniques to study problems of geophysical fluid dynamics, climate modeling, extreme weather, coastal and natural hazards, and other complex systems arising in the study of Earth and environmental systems.
Research Active Faculty:
RIT faculty conduct observational and theoretical research across a wide range of topics in multimessenger and multiwavelength astrophysics, utilizing a combination of observations spanning the electromagnetic spectrum, data from gravitational wave detectors, and supercomputer simulations. Current areas of research include numerical relativity and relativistic magnetohydrodynamics, gravitational wave data analysis, compact object binaries, accretion disks and jets, supernovae, and pulsars. RIT is a member of the Large Synoptic Survey Telescope Corporation and faculty are involved in several major collaborations including the Laser Interferometer Gravitational Wave Observatory Scientific Collaboration, the NANOGrav Pulsar Timing Array Consortium and the Laser Interferometer Space Antenna.
Research Centers:
Center for Computational Relativity and Gravitation
Research Active Faculty:
Featured Work
RIT Undergraduates Advance the Technique of Asymptotic Approximants Created by the BarlowWeinstein Group
Nathaniel Barlow
Four undergraduate students presented their research on the analytical solution to the classical FalknerSkan equation that describes boundary layer flow over a wedge.
3D Models of Math Equations
Nate Barlow and Steve Weinstein
Assistant Professor Nate Barlow and Professor Steve Weinstein made 3Dprinted models of mathematical equations to illustrate wave systems and other fluid dynamics concepts as part of their research....
Undergraduate Programs
The School of Mathematical Sciences provides a solid collegiate math education to every RIT undergraduate and offers highlevel specializations such as statistical forecasting, digital encryption, and mathematical modeling. We prepare our graduates to be successful, whether they choose immediate employment upon graduation or to attend graduate school in pursuit of advanced degrees.
An applied mathematics major focusing on problems that can be mathematically analyzed and solved, including models for perfecting global positioning systems, analyzing costeffectiveness in manufacturing processes, or improving digital encryption software.
Learn More about Applied Mathematics BSUsing calculus, statistics, algebra, and computer science, statisticians apply their knowledge of statistical methods—the collection, processing, and analysis of data and its interpretation—to a variety of areas, including biology, economics, engineering, medicine, public health, psychology, marketing, and sports.
Learn More about Applied Statistics and Actuarial Science BSThe computational mathematics degree emphasizes problem solving using mathematical models to identify solutions in business, science, engineering, and more.
Learn More about Computational Mathematics BSGraduate Programs
The School of Mathematical Sciences equips its graduates with a deep understanding of math principles, a toolbox for applying those skills to realworld problems, and the ability to easily express complex ideas. Our graduate programs introduce students to rigorous advanced applied mathematical and statistical methodology. Students realize the potential for that cuttingedge methodology as a general tool in the study of exciting problems in science, business, and industry.
A mathematics master's degree designed for you to create innovative computing solutions, mathematical models, and dynamic systems to solve problems in industries such as engineering, biology, and more.
Learn More about Applied and Computational Mathematics MSEngineers, analysts, and other professionals develop a deeper understanding of the statistical methods related to their fields.
Learn More about Applied Statistics Adv. Cert.In this statistics master's degree, you'll learn statistical analysis and apply it to a variety of industries, including insurance, marketing, government, health care, and more.
Learn More about Applied Statistics MSThe mathematical modeling Ph.D. enables you to develop mathematical models to investigate, analyze, predict, and solve the behaviors of a range of fields from medicine, engineering, and business to physics and science.
Learn More about Mathematical Modeling Ph.D.Minor and Immersions
Deepen your technical background and gain further appreciation for modern mathematical sciences and the use of statistics as an analytical tool.
Learn More about Applied Statistics ImmersionDeepen your technical background and gain further appreciation for modern mathematical sciences and the use of statistics as an analytical tool.
Learn More about Applied Statistics MinorNotes about this immersion:
Learn More about Mathematics ImmersionThe mathematics minor is designed for students who want to learn new skills and develop new ways of framing and solving problems. It offers students the opportunity to explore connections among mathematical ideas and to further develop mathematical ways of thinking.
Learn More about Mathematics Minor