[Colloquium] TODAY, 3PM: Data Science/CS Candidate Elizabeth Bondi (Harvard)

[Rob Mitchum]

*Data Science Institute/Computer Science Candidate Seminar*

*Elizabeth Bondi*
*PhD Candidate*

*Harvard University*

*Thursday, February 17th*
*3:00 p.m. - 4:00 p.m.*

*REMOTE ONLY*Watch Via Live Stream
<http://live.cs.uchicago.edu/elizabethbondi/> or Zoom
<https://uchicago.zoom.us/j/96785105495?pwd=cExjazMzZ2NmWUVrZ0hUbmdTMjFBQT09>
(full details below)

*Translating AI to Impact: Uncertainty and Human-agent Interactions in
Multi-agent Systems for Public Health and Conservation*

AI is now being applied widely in society, including to support
decision-making in important, resource-constrained efforts in conservation
and public health. Such real-world use cases introduce new challenges, like
noisy, limited data and human-in-the-loop decision-making. I show that
ignoring these challenges can lead to suboptimal results in AI for social
impact systems. For example, previous research has modeled illegal wildlife
poaching using a defender-adversary security game with signaling to better
allocate scarce conservation resources. However, this work has not
considered detection uncertainty arising from noisy, limited data. In
contrast, my work addresses uncertainty beginning in the data analysis
stage, through to the higher-level reasoning stage of defender-adversary
security games with signaling. I introduce novel techniques, such as
additional randomized signaling in the security game, to handle uncertainty
appropriately, thereby reducing losses to the defender. I show similar
reasoning is important in public health, where we would like to predict
disease prevalence with few ground truth samples in order to better inform
policy, such as optimizing resource allocation. In addition to modeling
such real-world efforts holistically, we must also work with all
stakeholders in this research, including by making our field more inclusive
through efforts like my nonprofit, Try AI.

*Bio*: Elizabeth Bondi <https://sites.google.com/view/elizabethbondi> is a
PhD candidate in Computer Science at Harvard University advised by Prof.
Milind Tambe. Her research interests include multi-agent systems, remote
sensing, computer vision, and deep learning, especially applied to
conservation and public health. Among her awards are Best Paper Runner up
at AAAI 2021, Best Application Demo Award at AAMAS 2019, Best Paper Award
at SPIE DCS 2016, and an Honorable Mention for the NSF Graduate Research
Fellowship Program in 2017.

*Host*: Ben Zhao

https://uchicago.zoom.us/j/96785105495?pwd=cExjazMzZ2NmWUVrZ0hUbmdTMjFBQT09
Meeting ID: 967 8510 5495
Password: ds2022


-- 
*Rob Mitchum*

*Associate Director of Communications for Data Science and Computing*
*University of Chicago*
*rmitchum at uchicago.edu <rmitchum at ci.uchicago.edu>*
*773-484-9890*
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