Division of Mathematics, Computing, and Statistics
The Division of Mathematics, Computing, and Statistics has a long history of preparing both traditional and nontraditional women students for successful careers and for graduate school.
Empowering our students in the field
We provide an environment that empowers women in mathematics, computer science, and statistics and helps them to realize their potential in those fields. Sensitive to varied learning styles as well as to the changing workplace, we use a range of teaching methods to address students' individual needs. These include cooperative learning groups, use of computer laboratory investigations, and independent learning, as well as traditional teacher-directed learning. An important focus in our curriculum is modeling and real-world applications.
Students will learn to think critically, logically, and abstractly and gain a strong theoretical foundation on which to build their understanding of current technologies—and to imagine new innovations. Through hands-on class projects, students experiment with the design and development of websites, databases, applications, software, and other technologies. Building bridges between communication and programming, design and technical abilities, these students go on to careers in a wide range of industries.
Learn more about our full-time MCS faculty, who are leaders in their fields and mentors in the classroom.
Professor Nanette Veilleux was the recipient of the 2022 Mary Kenneth Keller Computer Science and Engineering Undergraduate Teaching Award. The award was granted for her work in "supporting young women in the STEM fields by inspiring students in the classroom and creating innovative curriculum and research opportunities at a women-centered institution." The video shown at the award presentation is available on YouTube.
Simmons Language Lab (SLANG)
Simmons Language Lab is a collaborative center for work on computational linguistics at Simmons University. Ongoing research attempts to bridge the gap between human understanding and machine processing of natural language. In SLANG, Professors of Computer Science Nanette Veilleux and Amber Stubbs conducts research on both written and spoken text, including syntactic and semantic annotations, automated text processing, and studies in speech prosody.
Computer Science majors will
- Understand the fundamental concepts and theory of computing and their application to solving real world problems.
- Express themselves and ideas orally, in writing, and the “languages” of the discipline.
- Master current and cutting edge technologies including programming languages, algorithms, databases, systems analysis, web based technologies, networks, security and hardware.
- Think abstractly, logically, clearly, and critically.
- Work in groups both as a participant and as a leader.
- Relate theory to practice.
- Be lifelong learners and able to teach themselves.
- Understand the ethical, legal, and social implications of technology.
- Become gainfully employed in technology related jobs and/or prepared for graduate study.
Student Learning Outcomes for the Mathematics Major
- Knowledge of the basic concepts and techniques in core content areas of mathematics and in elementary statistics.
- Understanding of the basic concepts and techniques in core content areas of mathematics and in elementary statistics and ability to translate that theory to other disciplines.
- Ability to apply the basic concepts and techniques in core content areas of mathematics and in elementary statistics to solve routine homework problems.
- Ability to use logical reasoning and analysis to solve more complex problems, including the ability to select from, use and interpret various mathematical approaches.
- Ability to communicate mathematical and statistical ideas clearly and precisely, including the ability to develop and write rigorous mathematical proofs.
- Ability to read and learn mathematics independently.
- Ability to program in a high level programming language.
Student Learning Outcomes for the Biostatistics Major
- Select from, use and interpret results of, descriptive statistical methods effectively.
- Demonstrate an understanding of the central concepts of modern statistical theory and their probabilistic foundation.
- Select from, use, and interpret results of, the principal methods of statistical inference and design.
- Communicate the results of statistical analyses accurately and effectively.
- Make appropriate use of statistical software.
- Read and learn new statistical procedures independently.
Computer Science Opportunities
Your source for professional, pre-professional, and internship opportunities.Access Jobline
- (617) 521-2807
- Send an email
- Send an email
- M-F, 8:30AM - 4:30PM
Simmons University has been designated a Center for Academic Excellence (CAE) in Cybersecurity Education by the National Security Agency (NSA) and the Department of Homeland Security. This prestigious designation recognizes Simmons' excellence in cybersecurity education and its commitment to advancing...
On March 17 at the Special Interest Group on Computer Science Education (SIGCSE) in Toronto, Professor of Mathematics, Computing, and Statistics Nanette Veilleux received the Computing Research Association-Education (CRA-E) Undergraduate Research Faculty Mentoring Award . This award recognizes faculty members...
CJ ’24 (Chloie Johnson) attended the American Physical Society’s Conference for Undergraduate Women in Physics (CUWiP) at Boston University in January 2023. They spoke with us about their experience at the conference and their love for science. Tell us about...
The Passionate Leaders Project (PLP) supports undergraduate students by funding research opportunities that transcend traditional coursework. Participants of the PLP develop research and critical thinking skills and bring the insights of academia to real world issues. This year’s cohort addresses mental health, neuroscience, environmental science, the foster care system, and technology.
Passionate Leaders Project: Spring 2022 Cohort The Passionate Leaders Project (PLP) supports undergraduate students by funding research opportunities that transcend traditional coursework. Participants of the PLP develop research and critical thinking skills and bring the insights of academia to real...
Professor Nanette Veilleux , from the Division of Mathematics, Computing, and Statistics, was selected by the IEEE (Institute of Electrical and Electronics Engineers) Computer Society’s Awards Committee and the Society’s Board of Governors to receive the 2022 IEEE Computer Society...
Cohort of talented faculty bring extensive scholarly and professional experience, and a wide range of diverse perspectives and backgrounds.
The Passionate Leaders Project supports undergraduate students seeking to enrich their academic and professional interests by funding learning opportunities beyond the boundaries of the traditional classroom. Learn what the Spring 2021 cohort is up to!