Computers are now predicting stock market changes, detecting cancer, and translating documents – all thanks to the power of machine learning and artificial intelligence. At the forefront of this field are Hopkins engineers and computer scientists, who are building better algorithms to tackle problems once thought to be too complex for computers to solve.

One of the department’s greatest strengths is applying data science and analytics to healthcare applications. Projects include using wearables data to monitor and prevent health problems, improving diagnostics, and turning patient care into precision medicine. Notably, our researchers quickly shifted focus to contribute to the fight against COVID-19 by developing prediction models to track the pandemic and analyzing data to understand health disparities, among other projects.

Research Centers & Groups

Machine Learning Group

Our computational learning community aims to build systems that approach human intelligence, and which comb through massive datasets to answer questions that are beyond the capability of the unaided human mind.

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MINDS

The Mathematical Institute for Data Science (MINDS) at Johns Hopkins University brings together a multidisciplinary team of mathematicians, statisticians, computer scientists, and engineers to develop the fundamental mathematical, statistical, and computational principles for the analysis and interpretation of massive amounts of complex high-dimensional data.

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Institute for Data Intensive Engineering and Science

The IDIES mission is to coalesce data-intensive science efforts at Johns Hopkins into a well-focused center of activity, and to propel various fields towards new discoveries and breakthroughs.

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Malone Center for Engineering in Healthcare

The Malone Center for Engineering in Healthcare brings together engineers, clinicians, and care providers who are leveraging data analytics in novel ways, are pioneering new technologies, and are applying systems engineering principles to speed the deployment of research-based innovations that will enhance the efficiency, effectiveness, and consistency of health care.

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