Subjects and Speakers
Each session’s topic seeks to promote an exchange of knowledge and
experiences amongst participants, and to inspire new lines of research
across borders.
The speakers are prestigious professors who have extensive teaching and
research experience and whose work has been widely published in their
respective fields. Sessions are structured around the presentation of
articles, case studies, and work of the speakers themselves, presenting
reviews of their work and the current state of issues involved.
Designs for description, prediction and causal inference
Principles of Screening. COVID-19 Application
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Building Regression Models
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Dr. Brian Healy
Associate Professor, Department of Biostatistics
Harvard
T.H. Chan School of Public Health
Associate Professor of Neurology, Brigham and Women’s Hospital |
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Machine Learning for Clinical Research
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Dr. Andrew Beam
Assistant Professor,
Department of Epidemiology
Harvard T.H. Chan School of Public Health
Biomedical Informatics, Harvard Medical School
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Introduction to Infectious Disease Models
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Dr. Yonatan Grad
Associate Professor,
Department of Immunology and Infectious Diseases
Harvard T.H. Chan School of Public Health |
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Principles of Screening. COVID-19 Application
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Causal Inference from Healthcare Databases
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Dr. Miguel Hernan
Kolokotrones Professor of Biostatistics and Epidemiology,
Department of Epidemiology, Department of Biostatistics
Harvard T.H. Chan School of Public Health |
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Modelling the COVID-19 pandemic (lab)
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Interpretation of Evidence on COVID-19 Vaccines
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Dr. Barbra Dickerman
Instructor,
Department of Epidemiology
Harvard T.H. Chan School of Public Health |
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*Information is subject to change
*Sessions are conducted in English and require active participation of all attendees. Required readings are also in English.
For more details or questions, write to: iap.symposia@uam.es
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