Thursday, December 10, 2020 5:00 – 7:00PM


**If you are interested in attending this event, please email Dawn Bryant for the Zoom link.**

Download the PDF Flyer

Rutgers AI and Pandemics Initiative: 3MP Competition

  • What do you want to research?
  • Why does it matter?
  • Can you articulate it in 3 minutes or less?

The COVID-19 pandemic has forced the world to critically evaluate the ways in which state-of-the-art technology, and in particular Artificial Intelligence (AI), can be leveraged to dampen the impact of current and future threats. The Rutgers AI and Pandemics Initiative is organized around a transdisciplinary group including over 30 faculty members represented from diverse fields and from units all across Rutgers. To stimulate our rich community, we are pleased to announce our inaugural Three Minute Proposal (3MP) for graduate students and postdocs, modeled after the acclaimed three-minute thesis (3MT) competition.

What is it? A time to propose your research ideas in 3 minutes (virtually) related to artificial intelligence or related tools of data science, with direct or indirect applications to this pandemic or future pandemics. All you need is an idea (i.e., you need not be a programmer to participate).

What is the topic? You should propose either a research inquiry (or innovative solution for undergraduates – described below) related to mental health, contact tracing, supply chain, disease tracking and preventing, testing, dispensing of vaccines, communication, accessibility, or other topics that can relate to AI and pandemics.

Why participate? This is a great opportunity to practice your presentation skills, and gain visibility with faculty, your department, and senior leadership at Rutgers.
But, really, why participate? Because graduate student(s) or postdoc(s) and undergraduates will be selected as winner(s) and receive a cash prize of $500. In addition, they will gain additional opportunity to work with the team to obtain supplemental seed money for their project….and of course, you can say that you are the winner of the inaugural AI and Pandemics 3MP!!

When is it? This event will be held virtually on December 10th, 2020 at 5:00PM EST.

What is the Format? There are two ways to approach this competition, and we are encouraging both types of proposals, highlighted below.

  • Research Inquiry (Track A – for undergraduates, graduate students, postdocs: ask a question and develop a research project to address it): Using AI, cognitive science, or other tools of data science, propose a research question that is important during the pandemic era. Your proposal should include an introduction to your research question and its urgency, your method in answering the research question, as well as your hypothesized results and their significance. You could discuss barriers one might face in answering your research question, with your response in overcoming those barriers. You could include particular faculty who conduct related research, although that is not required.

What success looks like: A good proposal will have a clearly defined, timely research question, with a proposed method that is grounded in reality and uses sound science. Leveraging the work of existing internal RU faculty is encouraged, although not required.

  • Innovative Solution (Track B – for Undergraduates only: propose an answer): Using AI, cognitive science or other tools of data science, propose a specific solution to a challenge that has become more salient during the pandemic era. Your proposal should include an introduction to the problem and its urgency, your plausible unique solution, and relevant tools and resources needed for its success. You could discuss barriers one might face in introducing this solution, with your response in overcoming those barriers. You can also include partners that would be leveraged, including industry and faculty. This is simply a proposed idea. Speculative ideas are welcomed.

What success looks like: A good proposal will have state a clearly defined, timely problem, with a solution that is grounded in reality. Leveraging existing internal RU assets (faculty, students, facilities) for background or resources is encouraged, although not necessary as some “solutions” may involve accessing publicly available data/information/tools.

Are you interested? If so, reply to Dawn Bryant <> or Sara Pixley <> with your title and abstract by November 20th. Spots are limited, so your title and abstract will be reviewed, and you will be notified of participation shortly after.  

Warm regards,

The AI and Pandemics Group