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

[Rob Mitchum]

Slight Correction: The date in the body of the email was incorrect. The
talk is* today*, *February 21st.*

On Mon, Feb 21, 2022 at 8:23 AM Rob Mitchum <rmitchum at uchicago.edu> wrote:

> *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*
>


-- 
*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*
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.cs.uchicago.edu/pipermail/colloquium/attachments/20220221/7af56b4c/attachment.html>