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PHAISE AI Research Day 2026: Call for Abstracts
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PHAISE AI Research Day 2026: Call for Abstracts

For the second year, research@BSPH and Public Health + AI Strategic Endeavors (PHAISE) invites the BSPH community to share their AI-related research! Abstract submissions are due on Monday, February 23, 2026 by 11:59pm EST. 

We invite abstract submissions of all AI-focused backgrounds to participate in our AI Research Day 2026 poster session on Monday, March 23, 2026. Outstanding abstracts will be selected to receive a $500 award and give oral presentations in conjunction with our keynote address.

We define AI research broadly to include developing cutting-edge analytic methods (e.g., new algorithms and techniques in machine learning, deep learning, and natural language processing), applying these methods to extract insights from large datasets or inform interventions, and addressing ethical issues related to AI in public health.

If you do not have a project to submit, please consider joining AI Research Day to help inform our evolving work leveraging AI for public health!

How to submit an abstract

  1. Download the Submission Form: AI Research Day Abstract Submission Form_2026.docx

  2. Add your abstract content (300 words and single figure, see detailed guidelines below).

  3. Download the submission as a single .pdf document and email it to BSPH.research@jh.edu no later than Monday, February 23, 2026, at 11:59pm EST.

Abstracts should be written to a broad audience with varied expertise in AI research. Abstracts are limited to 300 words (excluding title and author list). Abstracts may also include a single figure limited to panels which can be included along with the text on a single page with narrow margins.

Reasons to submit an abstract

  • Contribute to the growing field of AI and public health.

  • Help bolster public health and AI’s role in the social good landscape.

  • Spread awareness of your scholarly work.

  • Connect with others exploring AI tools or interventions.

Eligibility requirements

  • The project incorporates use of AI and data science approaches to address or support scientific discoveries or public health challenges.

  • Presenting author is a student, postdoc, staff or faculty member currently affiliated with BSPH.