The I2DB Speakers Bureau offers a roster of expert speakers for lectures, panel discussions, workshops, and conferences on a variety of biomedical and data science topics.
I2DB serves as an academic and professional hub for research and practice in informatics, data science, and biostatistics. Our institute covers the School of Medicine and collaborates with the School of Engineering and Applied Science, Institute for Public Health, Brown School, Olin School of Business, Health Systems Innovation Lab and Center for Clinical Excellence at BJC HealthCare, and the Cortex Innovation Community.
Fill out the form below to book a speaker or contact the I2DB Speakers Bureau at OHIDS-marketing@wustl.edu.
Not sure where to start?
Let us know what topics you are interested in, and we can pair you with a speaker from WashU’s Institute for Informatics, Data Science and Biostatistics (I2DB).
Joanna Abraham
A Distinguished researcher committed to improving care coordination and ensuring patient safety.
PhD, FACMI, FAMIA
Associate Professor of Anesthesiology, Associate Professor of Medicine
Thomas G. Kannampallil
A Renowned expert in AI-based clinical decision support and patient safety innovations.
PhD
Associate Professor of Anesthesiology
Associate Professor of Computer Science and Engineering
Albert M. Lai
A Visionary leader pioneering advances in biomedical informatics.
PhD, FACMI, FAMIA
Deputy Director, Institute for Informatics, Data Science and Biostatistics (I2DB)
Chief Research Information Officer, School of Medicine
Professor of Medicine, Division of General Medicine & Geriatrics
Professor of Computer Science and Engineering, School of Engineering and Applied Science
Philip R.O. Payne
An internationally recognized leader in the fields of biomedical informatics, artificial intelligence, and data science.
PhD, FACMI, FAMIA, FAIMBE, FIAHSI
Director, Institute for Informatics, Data Science and Biostatistics (I2DB)
Janet and Bernard Becker Professor
Associate Dean for Health Information and Data Science, School of Medicine
Chief Data Scientist, School of Medicine
- Artificial Intelligence (AI)
- Artificial Intelligence and Healthcare – Applications of AI and Generative AI in healthcare
- Care transitions and AI
- Clinical decision support
- Clinical Research Informatics
- Clinical trial(s) of voice-based AI applications for depression and anxiety
- Computational phenotyping
- Data Lakes for Healthcare / Clinical Data Warehousing
- Digital transformation
- Implementation of AI – Social and Organizational issues around implementing AI in clinical settings)
- Implementing AI at the point-of-care and pragmatic challenges – How can we translate AI applications to be effectively used at the point of care
- Integrating biomedical informatics and data science competencies to prepare the healthcare research and delivery workforce
- Patient and general public perspectives on AI in surgical care
- Perioperative mental health
- Secure messaging in the clinical work environment
- Synthetic data
- Using audit logs to predict phenotypes of clinician behaviors and assessing impact on clinician workload and burnout