May 13-15, 2019

Simmons Auditorium
David A. Tepper Quadrangle
Carnegie Mellon University
Pittsburgh, PA

#AIDR2019

  • Meet world leaders in AI, scientific computing, and data management
  • Join the conversation on harnessing the power of AI for scientific data discovery and reuse
  • Connect innovations in AI with research data management

EXTENDED DEADLINES:

Abstract Submission: February 22, 2019

Decision: March 8, 2019

Early Bird Registration: March 22, 2019

ABOUT

Supported by the NSF scientific data reuse initiative, AIDR (Artificial Intelligence for Data Discovery and Reuse) 2019 is a conference aiming to find innovative solutions to accelerate the dissemination and reuse of scientific data in the data revolution. The explosion in the volume of scientific data has made it increasingly challenging to find data scattered across various platforms. At the same time, increasing numbers of new data formats, greater data complexity, lack of consistent data standards across disciplines, metadata or links between data and publications makes it even more challenging to evaluate data quality, reproduce results, and reuse data for new discoveries. AIDR 2019 provides a platform for AI/ML researchers, data professionals, and scientists to come together and benefit from mutual expertise to address these data challenges and to facilitate the next breakthroughs in science and technology using the power of AI and scientific data.


Keynotes

Tom M. Mitchell

Interim Dean
E. Fredkin University Professor

School of Computer Science
Carnegie Mellon University

Glen de Vries

President and Co-founder
Medidata Solutions

Invited Speakers

Sean Davis

Senior Associate Scientist
National Cancer Institute, NIH

Casey Green

Assistant Professor of Systems Pharmacology and Translational Therapeutics
Perelman School of Medicine
University of Pennsylvania

Alex London

Clara L. West Professor of Ethics and Philosophy
Department of Philosophy
Carnegie Mellon University

Robert F. Murphy

Ray and Stephanie Lane Professor
Head of Computational Biology

School of Computer Science
Carnegie Mellon University

Fiona Nielsen

Founder and CEO
Repositive

Natasha Noy

Staff Scientist
Google AI

Lisa S. Parker

Professor and Director
Center for Bioethics & Health Law
University of Pittsburgh

PROGRAM HIGHLIGHTS

Automation in data discovery

Automation in data curation and generation

Measuring and improving data quality

Integrating datasets and enabling interoperability

Biomedical data discovery and reuse

Data privacy, security and algorithmic bias

The future of scientific data and how we work together


Program Co-chairs

Nick Nystrom

Chief Scientist,
Pittsburgh Supercomputing Center

Keith Webster

Dean,
Carnegie Mellon University Libraries

Huajin Wang

Biomedical Data Science Liaison,
Carnegie Mellon University

Paola Buitrago

Director for AI and Big Data,
Pittsburgh Supercomputing Center

Program Committee

Sayeed Choudhury

Associate Dean for Research Data Management,
Jonhs Hopkins University Libraries

Sean Davis

Senior Associate Scientist,
National Cancer Institute

Fei Fang

Assistant Professor,
School of Computer Science, Carnegie Mellon University

Andreas Pfenning

Assistant Professor,
School of Computer Science, Carnegie Mellon University

General Chair

Huajin Wang (email)

Carnegie Mellon University

Organizing Committee

Neelam Bharti

Carnegie Mellon University

Michelle Delvin

Pittsburgh Super Computing Center

Ann Marie Mesco

Carnegie Mellon University

Sarah Young

Carnegie Mellon University