Johns Hopkins engineers join partnership to advance machine learning, artificial intelligence

June 4, 2019
Rene Vidal and Vishal Patel

L-R: Rene Vidal and Vishal Patel

Rene Vidal, the Herschel L. Seder Professor in Johns Hopkins University’s Department of Biomedical Engineering and the director of JHU’s Mathematical Institute for Data Science (MINDS), and Vishal Patel, a professor of electrical and computer engineering and a member of MINDS, have joined a new interdisciplinary research consortium focused on advancing machine learning and artificial intelligence.

The research consortium, known as Research in Applications for Learning Machines (REALM), was established to foster collaboration between leading universities with strong machine learning and artificial intelligence programs.

The REALM teams’ focus is on machine learning through artificial intelligence, allowing computers to decide what information to take in from multiple sources, clean the data, integrate it, label it, and learn from it to identify where it’s needed and disseminate it to the right users.

The goal is for the computers to learn what users are looking for and, as new information comes in, anticipate what users will want and push it out to them – even before the users are aware the data exists.

“A key challenge with state-of-the-art methods is that they require large amounts of labeled data,” explains Vidal. “We are developing methods that automatically discover a very small fraction of examples that need to be labeled.”

The research team says machine learning through artificial intelligence could be used in a variety of ad hoc situations, ranging from informing police of changes in traffic patterns due to accidents to supporting various branches of the military looking for the smallest details regarding missions. In addition to online information, the machine learning system takes in data from sensors, signals or drones and “cleans” it so it can be understood by users.

As users request information, the computer fills the request. Using algorithms, the system is expected to continually learn the type of data the user wants so that in the future, as pertinent information is received, it can automatically be sent to the appropriate user without receiving a formal request.

The data will be filtered based on privacy policy and context before it is sent. Feedback is given by the user afterward so the system can determine the parameters for future data to be sent out.

The REALM consortium includes researchers from Carnegie Mellon University; Massachusetts Institute of Technology, Purdue University; and Stanford University and received support from Northrop Grumman.

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