AI-X

Cluster leads: Brian Caffo and Rama Chellappa

There is a revolution underway in science, engineering, medicine, and public health, accelerated by a rapidly growing constellation of technologies that are built on machine learning and data science.

The AI-X Cluster will build on the intersection of data science, machine learning, and the deep domain expertise at Johns Hopkins to develop scalable AI systems that will drive discovery, decision-making, and prediction in science, engineering, medicine, and public health. Cluster scholars will focus on making JHU the destination for scholarship in scalable multimodal AI systems that integrate domain knowledge to drive science, engineering, medicine, and public health.

This cluster will be recruiting 3 Bloomberg Distinguished Professors and 3 junior faculty members to collaborate together along with existing Johns Hopkins faculty in these areas of research.

Interested in this cluster? Contact us to learn more.

More Information

• Cluster fact sheet (downloadable file)

Research Goals / Scholar Background

The AI-X BDP Cluster will focus on making JHU the destination for scholarship in scalable multimodal AI systems that integrate domain knowledge to drive science, engineering, medicine, and public health.

Scholars in this cluster will have proven records in areas including:

• Integration of domain knowledge and data-driven methods
• Expertise in working/researching across disciplines including computer science, engineering, natural sciences, public health, and medicine
• Success in building AI systems that can reason and infer from heterogeneous data streams with the goals of decision making and prediction

Leveraging research strengths across Johns Hopkins

This cluster will build on the strong existing expertise at Hopkins in computer vision, language and speech processing, cognitive science, imaging, and basic biomedical sciences. It will leverage Hopkins’ competitive advantages in domain expertise and domain-specific infrastructure (examples include pathology, oncology, genetics, neuroscience, materials, physics, energy, climate, biomedical engineering, epidemiology, and environmental health). The cluster is fully aligned with the plans of the JHU AI-X initiative, which seeks to drive scholarship in the Foundations of AI and in the three application domains of Health and Medicine, Safety and Assurance, and Discovery and Inquiry.

Faculty working on AI issues are in every corner of the institution. Cluster scholars will benefit from access to AI experts in the Center for Imaging Science; the Center for Language and Speech Processing; the Institute for Data Intensive Engineering and Science; Laboratory for Computational Sensing + Robotics; Mathematical Institute for Data Science; Institute for Assured Autonomy; The Intelligent Systems Center; JHU Machine Learning Group; the Scientific Software Engineering Center; the Alliance for Cardiovascular Diagnostic and Treatment Innovation; the Berman Institute of Bioethics; the Center for Population Health Information Technology; the Hopkins Extreme Materials Institute; the Institute in Critical Quantitative; Computational, & Mixed Methodologies; the Institute for Clinical & Translational Research Informatics Core; inHealth; the Malone Center for Engineering in Healthcare; the Stavros Niarchos Foundation Agora Institute; and the Institute for Computational Medicine.