Program Highlights
Undergraduate Program
We offer BA and BS programs that focus on six branches of modern applied mathematics. Undergraduate ProgramApplied Mathematics and Statistics Master’s Program
Our MSE program combines state-of-the-art knowledge with career preparation. Master’s Program in AMSFinancial Mathematics Master’s Program
Our financial mathematics MSE program focuses on quantitative challenges in the global economy and career-readiness. Financial Mathematics master’s programData Science Master’s Program
Our MSE in data science program prepares you for professional advancement and for making an impact on humanity. Data Science Master’s ProgramAMS Doctoral Program
Doctoral students are mentored by renowned scholars and collaborate on research at the frontiers of their disciplines. AMS Doctoral ProgramApply today.
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Get to know us.
Determining Bias in AI - Alexandra Stephens ’19, data scientist at the Johns Hopkins University Applied Physics Laboratory utilizes statistical hypothesis testing to examine whether a performance disparity in AI is due to bias or random chance.
Improving Financial Markets - “The machine learning courses offered at Hopkins helped me establish a wide range of knowledge including the use of models, mathematical principles, algorithms, and optimization skills,” says Yongheng Zhang ’21, a data scientist at Nasdaq’s AI Core Development team.
Numbers Game - Alumnus, Neil Gahart, an applied mathematics and statistics major has an abiding love of playing and watching the game. “Being part of baseball’s data-driven present and future has proven irresistible to” says Gahart ’18.
What Are You Worth? - In his book, “Ultimate Price,” AMS alum, statistician, data scientist, and health economist, Howard Friedman MS ’98, PhD ’99 examines all of the ways, hidden and overt, that we affix a finite value to human existence.
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Mateo Díaz, new assistant professor in the Department of Mathematics and Statistics at Johns Hopkins, discusses his background, research interests, and enthusiasm for joining the university. Originally from Colombia, Díaz's research focuses on the intersection of continuous optimization, geometry, and statistics, with applications in data science and machine learning. In this Q&A, he shares insights into his research, real-world applications, and what drew him to this field.
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Caelyn Sobie, a PhD student in applied mathematics and statistics, joins the second cohort of Vivien Thomas Scholars. This month, she and 14 other scholars will begin their PhD studies at the university as part of a $150 million initiative to advance pathways for students from HBCUs and MSIs in science, technology, engineering, and math.
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Quanta Magazine features Ben Grimmer's recent study on a traditional assumption in gradient descent, revealing that breaking the rule of small steps can lead to nearly three times faster results on optimization problems.