Call for Papers, Challenges, and retrospectives

Submissions Due

September 30, 2022

Notification Deadline

October 21, 2022

Camera Ready Deadline


Video Presentation Deadline


We invite researchers to submit their recent work on the topic in the intersection of Artificial Intelligence (AI) and Humanitarian Assistance and Disaster Recovery (HADR) problems to be featured at our workshop co-located with NeurIPS 2022. This year, we are opening three calls: papers, retrospectives, and demonstrations.

1. Call for Papers

We welcome methods from Machine Learning, Computer Vision, Robotics, Natural Language Processing, Information Theory, Decision Theory, Game Theory, Causal Modeling, Applied Statistics, and related fields.

We highly encourage work with clear applications to any of a variety of humanitarian and disaster response issues, including, but not limited to, search and rescue robotics, computer vision for damage assessment, motion planning in obstructed roads, response to the COVID-19 pandemic, disinformation management on social media, and much more.

Paper Submission Format

Paper submissions will be limited to five pages of content and one page of references in the NeurIPS 2021 format.  All paper submissions must include an "Application Context" section. This section should discuss why this problem is a pressing concern within the HADR domain, especially specifics as to disaster, crisis, or type of assistance, why your research is impactful in this context, partnerships with agencies or stakeholders, and explain any concepts that would not be common knowledge to a general machine learning researcher (citations from HADR literature encouraged).

Please use your best judgement for what is suitable for your submission. The intent of this section is to increase readability of papers for all workshop participants, from ML experts to domain practitioners of HADR, as well as to help us match your submission to reviewers. 

Papers may contain appendices after the sixth page to highlight additional results, figures, proofs, and other supplementary materials, but the main body of the work should be self-contained.  Other supplementary materials, such as videos or audio clips, may be submitted as supplementary materials.  Reviewers are not required to consider appendices or supplementary materials in their decisions.

Paper Submission Instructions

The deadline for submission is September 30th, 2022 at 11:59PM AoE (anywhere on Earth). Submissions must be made on the hosted CMT instance at

All submissions will undergo double-blind review; Thus, please ensure that your submission is anonymized when submitted, including removing names, affiliations, contact information, and ensuring that references to your own previous work are in the third person.

Paper Review Criteria

Paper submissions will be reviewed along the following criteria:

Each submission will be reviewed by at least one member each from the AI and HADR communities to ensure both technical merit and impact are both considered.

2. Call for Retrospectives

This year we are excited to open a call for "Retrospectives":  submissions that detail AI + HADR research that has seen prototypical or production use in the field, including their points of success and modes of failure. These perspectives are invaluable in learning from past mistakes as well as successes, and for guiding best practices for researchers looking to enter this challenging application area.

Retrospective Submission Format

In order to facilitate responses from as diverse a group as possible, we will accept submissions of multiple forms. Submissions may be in one of the following submission types (all will be submitted in pdf format):

All content must be self-contained  -- e.g. slide decks should contain all context necessary for reviewers to understand the content without a presenter.

Similar to the call for papers, retrospectives should be submitted to the CMT instance linked above.

Retrospective Review Criteria

3. Call for Demonstrations

In conjunction with the City of New Orleans Office of Homeland Security and Emergency Preparedness, we will be conducting an on-site tutorial and demo event. First responders from the City and surrounding areas will walk AI + HADR attendees through how a real disaster is prepared for, responded to, and recovered from. Additionally, attendees will receive hands-on experience with some of the workflows first responders go through in each of these stages.

Attendees, in kind, will have the unique opportunity to share with first responders their research in a meaningful, unconstrained demonstration. Ranging from demonstrating the latest and greatest progress in rescue robotics to efficiencies in edge-deployed computer vision, we ask prospective attendees to submit to us a brief abstract and video of a relevant piece of research that you would like to demonstrate in the field.

Accepted submissions will have the opportunity to plan a physical demonstration in adverse conditions in New Orleans and receive feedback from first responders.

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Demonstration Submission Format

Demo submissions should be abstracts between 250 and 500 words, not including references. A link to a short, maximum five minute video should be provided to demonstrate that the research aimed to be demonstrated is in demo-able state.

Demonstration Review Criteria

Accepted Works

Authors of accepted works will be notified on October 21st, 2022.  Upon notification, we ask that authors of accepted works deanonymize their works, make any final changes, host their work on the web (for instance, on arXiv), and then submit a link to where the work is hosted to the workshop organizers by November 20th, 2022.  The workshop website will then be updated with links to accepted papers.

Note that accepted works will not be formally published. This means that:

Some or all of accepted works will be selected for oral presentations during the workshop.  The authors will record a video of themselves giving their presentation and submit it to the program committee by TBD.  More specific video submission instructions will be provided in the near future.