Artificial intelligence may seem like magic, but there’s a lot of math behind every chatbot, self-driving car, image generator, and digital assistant.
As AI transforms industries from healthcare to finance to entertainment, there is a growing demand for professionals who understand the math behind the technology. USC Dornsife College of Letters, Arts and Sciences is responding to that need with the creation of a new Master of Science degree in Mathematical Data Science. This master’s degree is a graduate program designed to train students not only to use AI, but to understand and build AI.
“Data science is mathematics,” said Aaron Rauda, chair of the Department of Physical Sciences and Mathematics and professor of mathematics, physics, and astronomy. “If you want to understand AI, you have to understand the mathematics that makes it work. That’s what makes this program unique.”
The program’s unique approach puts AI into gear
Many graduate programs focus on how to apply existing algorithms, such as plugging in data, running models, and interpreting output. But those tools quickly become obsolete, Lauda says. “By the time you leave a program that only teaches applications, the algorithms you learned may already be outdated.”
This program takes a different approach. Its goal is to provide students with a mathematical foundation for implementing modern algorithms, understanding why they work, and designing future tools.
Launched this fall, the on-campus program spans three to four semesters and focuses on all pillars of modern machine learning: probability theory, optimization, linear algebra, and statistical modeling. Students also gain hands-on experience working with real-world datasets in fields such as geoscience, biology, chemistry, and physics.
“We want students to understand theory and apply it to real-world problems,” says Xiaohui Chen, co-director of the program. “That experiential learning builds a portfolio that you can present to future employers and doctoral programs.”
Chen, an associate professor of mathematics, notes that the program addresses a growing need across a myriad of industries.
“Every sector now relies on data to guide decision-making,” he said. “Unlike other programs that primarily teach how to use existing code libraries, our program trains students to create new techniques and algorithms. Our graduates will graduate with a rare combination of advanced math and statistical skills combined with practical experience.”
Students say that approach is unique. Khang Nguyen joined the university after studying data science as an undergraduate and doing research in reinforcement learning.
“I wanted a school where I could deepen my background in mathematical theory while applying it to real-world data science problems,” he said. “We solve real-world problems and work on machine learning algorithms, and…small class sizes allow us to work closely with professors on research questions.”
Additionally, USC’s location in Los Angeles offers unique benefits, including access to internships and networking with local technology companies, entertainment studios, and startups. Students also benefit from Trojan’s alumni network and career support, including industry speaker events and mentorship programs.
Real-world experience and career prospects
Sheel Ganatra, chair of the Department of Mathematics and professor of mathematics at USC Dornsife, emphasized that the program complements the university’s broader efforts, citing in particular the Institute for Computing Ethics and Trust.
“We are working across the university to ensure that AI is not only powerful, but also ethical and trustworthy, and this program plays an important role in that,” he said.
Graduates will be well-prepared for a career in artificial intelligence, as well as advanced research roles and doctoral study.
“Currently, the AI sector and its adjacent fields are growing rapidly,” said Chen, program co-director. “Market forecasts suggest that the AI technology market could reach $1.8 trillion by 2030, with salaries for skilled data scientists averaging in the six-figure range. But more importantly, students will develop the skills to adapt as the field evolves,” he added, which will help solidify the long-term outlook.
Students are already exploring ambitious research directions. Nguyen works on reinforcement learning projects focused on bandit theory and policy optimization techniques. His classmate Viraj Bansal studies how theoretical mathematics, including areas such as representation theory, can inform machine learning models.
“This program allows us to experiment and explore,” Bansal said. “We are learning to be creators and innovators, not just implementers of AI.”
Mathematics professor and program co-director Stanislav Minsker says the program is designed to foster just such a mindset.
“If you want to go beyond a traditional data science program and understand and build AI from the ground up, this is the place to do it,” he said.
