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Canterbury Ballroom (Inn at The Colonnade Baltimore - A DoubleTree by Hilton Hotel)

4 West University Parkway

Baltimore, MD 21218

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The Johns Hopkins Mathematical Institute for Data Science (MINDS) is a new interdisciplinary institute at Johns Hopkins focused on developing the fundamental mathematical, statistical, and computational principles underlying the analysis and interpolation of massive amounts of complex high-dimensional data.

At this inaugural symposium, leading data science researchers from Johns Hopkins and other institutions will discuss the importance of data science in their fields and the continued need for advancement.


Featured Speakers and Sessions

Agenda subject to change.

Check-In and Registration (8:15 a.m.)

Opening Ceremony (9 to 9:25 a.m.)

  • Ed Schlesinger (Benjamin T. Rome Dean of the Whiting School of Engineering)
  • Denis Wirtz (Vice-Provost for Research at Johns Hopkins University)
  • René Vidal (Director of the Johns Hopkins Mathematical Institute for Data Science)

Session 1: Data Science Foundations and Applications in Medicine (9: 25 to 11 a.m.)

  • Michael Jordan (University of California, Berkeley) - "On Computational Thinking, Inferential Thinking and Data Science"
  • Greg Hager (Johns Hopkins University) - "The Role of Data in Achieving Precision and Value in Healthcare"
  • Alexis Battle (Johns Hopkins University) - "Machine Learning Approaches for Personal Genomics"

Coffee Break (10:35 a.m.)

Session 2: Reinforcement Learning, Representation Learning, and Applications in Vision and Speech (11 a.m. to 12:35 p.m.)

  • John Shawe-Taylor (University College of London) - "Conditional Mean Embeddings for Reinforcement Learning"
  • Stefano Soatto (Amazon Web Services & UCLA) - "Designing and Learning Representations for Visual Data in the Age of Deep Learning"
  • Sanjeev Khudanpur (Johns Hopkins University) - "Alexa, Tell Me How Kaldi and Deep Learning Revolutionized Automatic Speech Recognition!"

Lunch Break (12:35 p.m.)

Session 3: Random Matrices, Nonconvex Optimization, and Applications in Astronomy (2 to 3:30 p.m.)

  • Joel Tropp (California Institute of Technology) - "Applied Random Matrix Theory"
  • Aarti Singh (Carnegie Mellon University) - "Towards an Era of Intelligent Interactive Algorithms"
  • Alex Szalay (Johns Hopkins University) - "Data Science in Astronomy"

Coffee Break (3:35 p.m.)

Session 4: Nonconvex Optimization, Manifold Learning, and Applications in Computational Anatomy (4 to 5:30 p.m.)

  • John Wright (Columbia University) - "Nonconvex Optimzation for Low-Complexity Signal and Data Modeling"
  • Marina Meila (University of Washington) - "Is Manifold Learning for Toy Data Only?"
  • Nicholas Charon (Johns Hopkins University) - "Theoretical and Numerical Challenges in Medical Image Analysis and Computational Anatomy"

Closing Remarks (5:30 p.m.)



A block of rooms has been reserved at the Inn at the Colonnade Baltimore —a DoubleTree by Hilton Hotel. Click here to reserve your room.

Date and Time

Location

Canterbury Ballroom (Inn at The Colonnade Baltimore - A DoubleTree by Hilton Hotel)

4 West University Parkway

Baltimore, MD 21218

View Map

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