Department website: http://www.math.wvu.edu/
Degrees Offered
- Bachelor of Science
Nature of the Program
The School of Mathematical and Data Sciences provides a curriculum for:
- Students wishing to earn an undergraduate major in mathematics or minors in actuarial science, applied mathematics, and pure mathematics
- Students interested in the applications of mathematics to the fields of computer science, statistics, engineering, physical, natural and social science, and business and economics
- Non-science majors, to educate them in the ideals and objectives of mathematics, fostering quantitative reasoning and problem-solving skills
Minors
All students have the possibility of earning one or more minors; view a list of all available minors and their requirements here. Please note that students may not earn a minor in their major field. An undergraduate student majoring in mathematics may choose to minor in actuarial science, statistics or data science.
Mathematics Learning Center
The Mathematics Learning Center (MLC) is a free walk-in tutoring center open 5-days a week that employs students who are proficient in mathematics. It is located at ARM 301, and the hours are posted on the door or on the School of Mathematical and Data Sciences' webpage. The MLC tutors help with all undergraduate Mathematics courses through Calculus, except MATH 124 and MATH 150. Students in these courses can receive help at the STEM Learning Center. The MLC also employs students who are proficient in Mathematics. For more information about the center, call (304)293-2011 or contact Dr. Renee LaRue at reneelarue@math.wvu.edu.
Faculty
Director of the School of Mathematical and Data Sciences
- Jessica Deshler - Ph.D. (University of New Mexico)
Regular Graduate Faculty, Undergraduate Mathematics Education, Graduate Student Development
Associate Director of the Institute of Math Learning
- Lori Ogden - Ph.D. (West Virginia University)
Associate Graduate Faculty, Undergraduate Mathematics Education
Associate Director for Graduate Programs
- Kevin Milans - Ph.D. (University of Illinois)
Regular Graduate Faculty, Combinatorics, Graph Theory, and Partially Ordered Sets
Associate Director for Undergraduate Programs
- Charis Tsikkou - Ph.D. (Brown University)
Regular Graduate Faculty, Hyperbolic and Mixed Type Partial Differential Equations, Conservation Laws
Associate Director of the School of Mathematical and Data Sciences
- Adrian Tudorascu - Ph.D. (Carnegie Mellon University)
Regular Graduate Faculty, Partial Differential Equations, Optimal Transport
Professors
- Krzysztof Ciesielski - Ph.D. (Warsaw University)
Regular Graduate Faculty, Analysis, Topology, Set theory, MRI imaging - Marjorie Darrah - Ph.D. (West Virginia University)
Regular Graduate Faculty, Applied Mathematics, Mathematics Education - Jessica Deshler - Ph.D. (University of New Mexico)
Regular Graduate Faculty, Undergraduate Mathematics Education, Graduate Student Development - Harvey Diamond - Ph.D. (Massachusetts Institute of Technology)
Regular Graduate Faculty, Approximation theory, Applied mathematics - Harry Gingold - D.Sc. (Israel Institute of Technology)
Regular Graduate Faculty, Discrete Finite Difference systems of Equations, Factorization of Power Series, Foundation (Geometry), Mathematical Cryptography, Optimization, Compactification, Ordinary Differential Systems of Equations, Asymptotics, Approximations, Turning point theory, Celestial Mechanics - Erin Goodykoontz - Ed.D. (West Virginia University)
Introductory Concepts of Mathematics - Ádám M. Halász - Ph.D. (State University of New York at Stony Brook)
Regular Graduate Faculty, Molecular systems biology, Monte Carlo methods, Mathematical Physics - Rong Luo - Ph.D. (West Virginia University)
Regular Graduate Faculty, Graph Theory, Discrete Math - David Miller - Ph.D. (Oklahoma State University)
Regular Graduate Faculty, Undergraduate Math Education, Cognitive Science, STEM Education - Robert Mnatsakanov - Ph.D. (Moscow Institute of Electronics and Mathematics)
Regular Graduate Faculty, Applied probability, Approximation of functions from moments, Risk models - Laura Pyzdrowski - Ed.D. (West Virginia University)
Regular Graduate Faculty, Undergraduate Math Education, STEM Education, K-12 Outreach, Distance Learning, Instructional Technology - Kenneth Ryan - Ph.D. (Iowa State University)
Regular Graduate Faculty, Semi-supervised learning and design of experiments - Adrian Tudorascu - Ph.D. (Carnegie Mellon University)
Regular Graduate Faculty, Partial Differential Equations, Optimal Transport - Jerzy Wojciechowski - Ph.D. (University of Cambridge)
Regular Graduate Faculty, Combinatorics, Graph theory
Associate Professors
- Olgur Celikbas - Ph.D. (University of Nebraska)
Regular Graduate Faculty, Commutative Algebra, Homologic Algebra - Vito D'Orazio - Ph.D. (Pennsylvania State University)
Regular Graduate Faculty, Data Sciences - Renee LaRue - Ph.D. (West Virginia University)
Associate Graduate Faculty, Undergraduate Mathematics Education - Kevin Milans - Ph.D. (University of Illinois)
Regular Graduate Faculty, Combinatorics, Graph Theory, and Partially Ordered Sets - Lori Ogden - Ph.D. (West Virginia University)
Associate Graduate Faculty, Undergraduate Mathematics Education, Associate Director for the Institute for Math Learning - Casian Pantea - Ph.D. (University of Wisconsin-Madison)
Regular Graduate Faculty, Mathematical biology, dynamical systems - Vicki Sealey - Ph.D. (Arizona State University)
Regular Graduate Faculty, Calculus Coordinator, Undergraduate Math Education, Calculus Student Learning - Charis Tsikkou - Ph.D. (Brown University)
Regular Graduate Faculty, Hyperbolic and Mixed Type Partial Differential Equations, Conservation Laws
Assistant Professors
- Krista Bresock - Ph.D. (West Virginia University)
Undergraduate Mathematics Education - Ela Celikbas - Ph.D. (University of Nebraska)
Regular Graduate Faculty, Commutative Algebra, Representation Theory - Srinjoy Das - Ph.D. (University of California, San Diego)
Regular Graduate Faculty, Data Sciences - Ryan Hansen - Ph.D. (West Virginia University)
Combinatorics - Cody Hood - Ph.D. (West Virginia University)
Undergraduate Mathematics Education - Josh Karr - Ph.D. (West Virginia University)
Mathematics Education - Jennifer Kearns - M.S. (West Virginia University)
Undergraduate Mathematics Education - Mihyun Kim - Ph.D. (Colorado State University)
Regular Graduate Faculty, Functional Data Analysis, Extreme Value Analysis, and Time Series Analysis - Clark Metz - Ph.D. (West Virginia University)
Higher Education - Matthew Schraeder - Ph.D. (West Virginia University)
Undergraduate Mathematics Education - Ignacio Segovia Dominguez - Ph.D. (Center for Research in Mathematics, A.C.)
Regular Graduate Faculty, Applied Mathematics, Statistical Modeling and Computer Science - Youngseok Song - Ph.D. (Colorado State University)
Regular Graduate Faculty, High-dimensional Statistic, Graphical Model, Large-scale Inferences, Network Analysis - Iwona Wojciechowska - Ph.D. (West Virginia University)
Instructors
- Joelleen Bidwell - M.A. (West Virginia University)
- Gabriel Tapia - M.S. (West Virginia University)
- Galyna Voitiuk - Ph.D. (West Virginia University)
- Sylvanus Waibogha - M.S. (West Virginia University)
Professors Emeriti
- Anthony A. Billings - M.S. (West Virginia University, A.B.D. (Carnegie Mellon University))
Statistical Computing, Statistical Modeling, Robust Estimation, Nonlinear Dynamic Systems, Statistical Education - Gary Ganser - Ph.D. (Rensselaer Polytechnic Institute)
Modeling, Data Analysis - John Goldwasser - Ph.D. (University of Wisconsin-Madison)
Combinatorics, Graph Theory - Jack T. Goodykoontz Jr. - Ph.D. (University of Kentucky)
Topology - Henry W. Gould - M. A. (University of Virginia)
Number Theory, Combinatorics, Special Functions - Erdogan Gunel - Ph.D. (State University of New York at Buffalo)
Bayesian Inference, Biostatistics, Categorical Data Analysis - Harumi Hattori - Ph.D. (Rensselaer Polytechnic Institute)
Differential Equations, Continuum Mechanics - Gerald R. Hobbs - Ph.D. (Kansas State University)
Biostatistics, Nonparametric Statistics, Regression Analysis - Hong-Jian Lai - Ph.D. (Wayne State University)
Graph Theory, Matroid Theory - Dening Li - Ph.D. (Fudan University)
Partial Differential Equations - Michael E. Mays - Ph.D. (Pennsylvania State University)
Number Theory - James E. Miller - Ph.D. (University of Kentucky)
Complex Analysis - Sherman D. Riemenschneider - Ph.D. (Syracuse University)
Approximation Theory, Wavelets, Signal Processing - Cun-Quan Zhang - Ph.D. (Simon Fraser University)
Graph theory, Combinatorics, Algorithms, Bioinformatics, Data Mining
Admissions for 2026-2027
- First Time Freshmen are admitted directly to the major. For the timely completion of the degree, it is recommended that students have a minimum MATH ACT of 22, a MATH SAT of 540, or an ALEKS score of 45.
- Students transferring from another WVU major or from another institution with fewer than 24 credits and at least a 2.0 overall GPA are admitted directly to the major. For the timely completion of the degree, it is recommended that students have a minimum MATH ACT of 22, a MATH SAT of 540, or an ALEKS score of 45.
- Students transferring from another WVU major or from another institution with 24 credits or more and at least a 2.0 overall GPA must meet the following requirement prior to being admitted to the major: completion of MATH 155 with C-.
Major Code: 1457
General Education Foundations
Please use this link to view a list of courses that meet each GEF requirement.
NOTE: Some major requirements will fulfill specific GEF requirements. Please see the curriculum requirements listed below for details on which GEFs you will need to select.
| Code | Title | Hours |
|---|---|---|
| General Education Foundations | ||
| F1 - Composition & Rhetoric | 3-6 | |
| Introduction to Composition and Rhetoric and Composition, Rhetoric, and Research | ||
or ENGL 103 | Accelerated Academic Writing | |
| F2A/F2B - Science & Technology | 4-6 | |
| F3 - Math & Quantitative Reasoning | 3-4 | |
| F4 - Society & Connections | 3 | |
| F5 - Human Inquiry & the Past | 3 | |
| F6 - The Arts & Creativity | 3 | |
| F7 - Global Studies & Diversity | 3 | |
| F8 - Focus (may be satisfied by completion of a minor, double major, or dual degree) | 9 | |
| Total Hours | 31-37 | |
Please note that not all of the GEF courses are offered at all campuses. Students should consult with their advisor or academic department regarding the GEF course offerings available at their campus.
Degree Requirements
Students must complete WVU General Education Foundations requirements, Eberly Edge requirements, major requirements, and electives to total a minimum of 120 hours.
Departmental Requirements for the B.S. in Mathematics
- Calculation of the GPA in the Major: A minimum GPA of 2.0 is required in all classes applied to the major requirements. If a class is repeated, all attempts will be included in the calculation of the GPA unless the course is eligible for a D/F repeat.
- Writing and Communication Skills Requirement: Mathematics Bachelor of Science students fulfill the Writing and Communication Skills requirement by completing ENGL 101 and ENGL 102 (or ENGL 103), and three additional SpeakWrite Certified CoursesTM: MATH 303 and MATH 480 and MATH 481 or STAT 480 and STAT 481.
- Capstone Requirement: The university requires the successful completion of a Capstone course. Mathematics majors must complete MATH 480 and MATH 481, or STAT 480 and STAT 481.
Curriculum Requirements
| Code | Title | Hours |
|---|---|---|
| University Requirements | 45 | |
| Eberly Edge Requirements | 15 | |
| Mathematics Major Requirements | 60 | |
| Total Hours | 120 | |
University Requirements
| Code | Title | Hours |
|---|---|---|
| General Education Foundations (GEF) 1, 2, 3, 4, 5, 6, 7, and 8 (31-37 Credits) | ||
| Outstanding GEF Requirements 1, 4, 5, 6, and 7 | 18 | |
| MATH 191 | First-Year Seminar | 1 |
| General Electives | 26 | |
| Total Hours | 45 | |
Eberly Edge Program Requirements
| Code | Title | Hours |
|---|---|---|
| EDG 1: Data and Society | 3 | |
| EDG 2: Effective and Civil Communication | 3 | |
| EDG 3: Ethics and Civil Responsibility | 3 | |
| EDG 4: Global and Regional Perspectives | 3 | |
| EDG 5: Practicing Arts & Sciences | 3 | |
| EDG 6: High Impact Experience (MATH 480 & MATH 481 or STAT 480 & STAT 481) | ||
| Total Hours | 15 | |
Mathematics Major Requirements
| Code | Title | Hours |
|---|---|---|
| STEM FOUNDATIONS * | 12 | |
| Calculus 1 | ||
| Select 1 pair of science courses below: | ||
| Principles of Biology and Principles of Biology Laboratory and Introductory Physiology and Introductory Physiology Laboratory | ||
| Survey of General, Organic, and Biological Chemistry 1 and Survey of Chemistry 1 Laboratory and Survey of General Organic Biological Chemistry 2 and Survey of Chemistry 2 Laboratory | ||
| Fundamentals of Chemistry 1 and Fundamentals of Chemistry 1 Laboratory and Fundamentals of Chemistry 2 and Fundamentals of Chemistry 2 Laboratory | ||
| Introductory Physics 1 and Introductory Physics 1 Laboratory and Introductory Physics 2 and Introductory Physics 2 Laboratory | ||
| General Physics 1 and General Physics 1 Laboratory and General Physics 2 and General Physics 2 Laboratory | ||
| Sustainable Earth and Sustainable Earth Laboratory and Earth System Science and Earth System Science Laboratory | ||
| Sustainable Earth and Sustainable Earth Laboratory and Climate System Science and Climate System Science Laboratory | ||
| CORE COURSES | 30 | |
| Calculus 2 | ||
| Multivariable Calculus | ||
| Elementary Differential Equations | ||
| Introduction to the Concepts of Mathematics | ||
| Introduction to Programming and Computational Mathematics | ||
| Introduction to Linear Algebra | ||
or MATH 441 | Applied Linear Algebra | |
| Introduction to Algebraic Structures | ||
| Introduction to Real Analysis 1 | ||
| Introduction to Probability and Statistics | ||
| ELECTIVES | 15 | |
| Select five of the following: | ||
| Discrete Mathematics | ||
| Introduction to Analysis and Topology | ||
| Numerical Analysis 1 | ||
| Advanced Algebraic Structures | ||
| Introduction to Real Analysis 2 | ||
| Complex Variables | ||
| Introduction to Dynamical Systems and Applications | ||
| Mathematical Modeling | ||
| Partial Differential Equations | ||
| Introduction to Probability Theory | ||
| Theoretical Introduction to Statistical Inference | ||
| CAPSTONE EXPERIENCE | 3 | |
| Select one of the following pairs: | ||
| Capstone Design and Capstone Experience | ||
| Capstone Design and Capstone Experience | ||
| Total Hours | 60 | |
- *
-
STEM foundation courses are common to most STEM majors and excluded from the calculation of the percentage of upper-division course.
Suggested Plan of Study
| First Year | |||
|---|---|---|---|
| Fall | Hours | Spring | Hours |
| MATH 191 | 1 | MATH 156 (GEF 8 course 1) | 4 |
| MATH 155 (GEF 3) | 4 | ENGL 101 (GEF 1) | 3 |
| Science Course pair 1 (GEF 2) | 4 | EDG 1: Data and Society | 3 |
| GEF 4 | 3 | Science course pair 1 (GEF 8 course 2) | 4 |
| GEF 5 | 3 | General Elective | 1 |
| 15 | 15 | ||
| Second Year | |||
| Fall | Hours | Spring | Hours |
| MATH 251 | 4 | MATH 261 | 4 |
| MATH 343 or 441 | 3 | MATH 303 | 3 |
| STAT 215 (GEF 8 course 3) | 3 | MATH 322 | 3 |
| EDG 2: Effective and Civil Communication | 3 | EDG 3: Ethics and Civic Responsibilities | 3 |
| General Elective | 2 | General Elective | 2 |
| 15 | 15 | ||
| Third Year | |||
| Fall | Hours | Spring | Hours |
| MATH 341 | 3 | ARSC 380 (EDG 5) | 3 |
| Advanced Mathematics 1st course | 3 | Advanced Mathematics 2nd course | 3 |
| ENGL 102 | 3 | Advanced Mathematics 3rd course | 3 |
| EDG 4: Global and Regional Perspectives | 3 | General Elective | 3 |
| General Elective | 3 | General Elective | 3 |
| 15 | 15 | ||
| Fourth Year | |||
| Fall | Hours | Spring | Hours |
| MATH 451 | 3 | MATH 481 or STAT 481 (EDG 6: High Impact experience) | 2 |
| MATH 480 or STAT 480 (EDG 6: High Impact Experience) | 1 | Advanced Mathematics 5th course | 3 |
| Advanced Mathematics 4th course | 3 | GEF 7 | 3 |
| GEF 6 | 3 | General Elective | 4 |
| General Elective | 3 | General Elective | 3 |
| General Elective | 2 | ||
| 15 | 15 | ||
| Total credit hours: 120 | |||
Degree Progress
- By the end of their second semester (excluding summer) in the major, at minimum, students must have completed MATH 126 with a minimum grade of C-.
- By their 5th semester in the major, students should have completed calculus courses through MATH 261 with a minimum grade of C- and have satisfactorily completed or be enrolled in MATH 303.
- A minimum cumulative and major GPA of a 2.0 must be maintained. Students who do not meet this benchmark will be removed from the major.
- All majors must meet with a department advisor working in mathematics or statistics each semester.
Major Learning Outcomes
Mathematics
Upon successful completion of the B.S. degree, Mathematics majors will demonstrate the following competencies:
- Demonstrate a comprehensive understanding of rigorous mathematical proofs by constructing clear, well-organized, logical-mathematical arguments, accurately replicating essential assumptions, definitions, examples, and statements of important theorems, and describing the logical structure of standard proof formats.
- Recognize valid arguments, identify logical gaps and flaws, break down complex problems into simpler components, use existing techniques and known results to solve each component, and construct original proofs.
- Identify, formulate, and abstract mathematical problems using critical thinking skills in key mathematical areas, including calculus, algebra, applied analysis, differential equations, optimization, numerical analysis, and probability.
- Utilize various advanced mathematical techniques to solve problems and construct effective models. Apply these methods to devise practical solutions and develop strategies for real-world applications across diverse fields such as biology, physics, social sciences, and engineering in both public and private sectors.
- Ask pertinent questions and perform suitable quantitative analysis, demonstrating basic proficiency in fundamental computer programming techniques and algorithmic thinking necessary for quantitative analysis, validation, and mathematical modeling.
- Perform numerical and symbolic calculations, simplify expressions, and effectively communicate complex mathematical concepts through written, oral, visual, and symbolic forms.
- Engage in self-directed learning by independently exploring and mastering new mathematical concepts, techniques, or tools, demonstrating initiative and adaptability in unfamiliar contexts.