[Colloquium] NOW: 3/15 Talks at TTIC: Bryan Wilder, Harvard University

[Mary Marre]

*When:*      Monday, March 15th at* 11:10 am CT*



*Where:*     Zoom Virtual Talk (*register in advance here
<https://uchicagogroup.zoom.us/webinar/register/WN_nkFWByw8QLuMDwsvjxbolQ>*)



*Who: *       Bryan Wilder, Harvard University




*Title:*        AI for Population Health: Melding Data and Algorithms on
Networks

*Abstract:  *As exemplified by the COVID-19 pandemic, our health and
wellbeing depend on a difficult-to-measure web of societal factors and
individual behaviors. My research aims to build computational methods which
can impact such social challenges. This effort requires new algorithmic and
data-driven paradigms which span the full process of gathering costly data,
learning models to understand and predict interactions, and optimizing the
use of limited resources in interventions. In response to these needs, I
will present methodological developments at the intersection of machine
learning, optimization, and social networks which are motivated by
on-the-ground collaborations on HIV prevention, tuberculosis treatment, and
the COVID-19 response. These projects have produced deployed applications
and policy impact. For example, I will present the development of an
AI-augmented intervention for HIV prevention among homeless youth. This
system was evaluated in a field test enrolling over 700 youth and found to
significantly reduce key risk behaviors for HIV.

*Bio:*  Bryan Wilder is a PhD student in Computer Science at Harvard
University, where he is advised by Milind Tambe. His research focuses on
the intersection of optimization, machine learning, and social networks,
motivated by applications to population health. His work has received or
been nominated for best paper awards at ICML and AAMAS, and also received
second place in the INFORMS Doing Good with Good OR competition. He is
supported by the Siebel Scholars program and previously received a NSF
Graduate Research Fellowship.

*Host:* *David McAlleste <mcallester at ttic.edu>r*


Mary C. Marre
Faculty Administrative Support
*Toyota Technological Institute*
*6045 S. Kenwood Avenue*
*Room 517*
*Chicago, IL  60637*
*p:(773) 834-1757*
*f: (773) 357-6970*
*mmarre at ttic.edu <mmarre at ttic.edu>*


On Mon, Mar 15, 2021 at 10:00 AM Mary Marre <mmarre at ttic.edu> wrote:

> *When:*      Monday, March 15th at* 11:10 am CT*
>
>
>
> *Where:*     Zoom Virtual Talk (*register in advance here
> <https://uchicagogroup.zoom.us/webinar/register/WN_nkFWByw8QLuMDwsvjxbolQ>*
> )
>
>
>
> *Who: *       Bryan Wilder, Harvard University
>
>
>
>
> *Title:*        AI for Population Health: Melding Data and Algorithms on
> Networks
>
> *Abstract:  *As exemplified by the COVID-19 pandemic, our health and
> wellbeing depend on a difficult-to-measure web of societal factors and
> individual behaviors. My research aims to build computational methods which
> can impact such social challenges. This effort requires new algorithmic and
> data-driven paradigms which span the full process of gathering costly data,
> learning models to understand and predict interactions, and optimizing the
> use of limited resources in interventions. In response to these needs, I
> will present methodological developments at the intersection of machine
> learning, optimization, and social networks which are motivated by
> on-the-ground collaborations on HIV prevention, tuberculosis treatment, and
> the COVID-19 response. These projects have produced deployed applications
> and policy impact. For example, I will present the development of an
> AI-augmented intervention for HIV prevention among homeless youth. This
> system was evaluated in a field test enrolling over 700 youth and found to
> significantly reduce key risk behaviors for HIV.
>
> *Bio:*  Bryan Wilder is a PhD student in Computer Science at Harvard
> University, where he is advised by Milind Tambe. His research focuses on
> the intersection of optimization, machine learning, and social networks,
> motivated by applications to population health. His work has received or
> been nominated for best paper awards at ICML and AAMAS, and also received
> second place in the INFORMS Doing Good with Good OR competition. He is
> supported by the Siebel Scholars program and previously received a NSF
> Graduate Research Fellowship.
>
> *Host:* *David McAllester* <mcallester at ttic.edu>
>
>
>
>
>
> Mary C. Marre
> Faculty Administrative Support
> *Toyota Technological Institute*
> *6045 S. Kenwood Avenue*
> *Room 517*
> *Chicago, IL  60637*
> *p:(773) 834-1757*
> *f: (773) 357-6970*
> *mmarre at ttic.edu <mmarre at ttic.edu>*
>
>
> On Sun, Mar 14, 2021 at 4:00 PM Mary Marre <mmarre at ttic.edu> wrote:
>
>> *When:*      Monday, March 15th at* 11:10 am CT*
>>
>>
>>
>> *Where:*     Zoom Virtual Talk (*register in advance here
>> <https://uchicagogroup.zoom.us/webinar/register/WN_nkFWByw8QLuMDwsvjxbolQ>*
>> )
>>
>>
>>
>> *Who: *       Bryan Wilder, Harvard University
>>
>>
>>
>>
>> *Title:*        AI for Population Health: Melding Data and Algorithms on
>> Networks
>>
>> *Abstract:  *As exemplified by the COVID-19 pandemic, our health and
>> wellbeing depend on a difficult-to-measure web of societal factors and
>> individual behaviors. My research aims to build computational methods which
>> can impact such social challenges. This effort requires new algorithmic and
>> data-driven paradigms which span the full process of gathering costly data,
>> learning models to understand and predict interactions, and optimizing the
>> use of limited resources in interventions. In response to these needs, I
>> will present methodological developments at the intersection of machine
>> learning, optimization, and social networks which are motivated by
>> on-the-ground collaborations on HIV prevention, tuberculosis treatment, and
>> the COVID-19 response. These projects have produced deployed applications
>> and policy impact. For example, I will present the development of an
>> AI-augmented intervention for HIV prevention among homeless youth. This
>> system was evaluated in a field test enrolling over 700 youth and found to
>> significantly reduce key risk behaviors for HIV.
>>
>> *Bio:*  Bryan Wilder is a PhD student in Computer Science at Harvard
>> University, where he is advised by Milind Tambe. His research focuses on
>> the intersection of optimization, machine learning, and social networks,
>> motivated by applications to population health. His work has received or
>> been nominated for best paper awards at ICML and AAMAS, and also received
>> second place in the INFORMS Doing Good with Good OR competition. He is
>> supported by the Siebel Scholars program and previously received a NSF
>> Graduate Research Fellowship.
>>
>> *Host:* *David McAllester* <mcallester at ttic.edu>
>>
>>
>>
>>
>>
>>
>>
>> Mary C. Marre
>> Faculty Administrative Support
>> *Toyota Technological Institute*
>> *6045 S. Kenwood Avenue*
>> *Room 517*
>> *Chicago, IL  60637*
>> *p:(773) 834-1757*
>> *f: (773) 357-6970*
>> *mmarre at ttic.edu <mmarre at ttic.edu>*
>>
>>
>> On Mon, Mar 8, 2021 at 10:59 PM Mary Marre <mmarre at ttic.edu> wrote:
>>
>>> *When:*      Monday, March 15th at* 11:10 am CT*
>>>
>>>
>>>
>>> *Where:*     Zoom Virtual Talk (*register in advance here
>>> <https://uchicagogroup.zoom.us/webinar/register/WN_nkFWByw8QLuMDwsvjxbolQ>*
>>> )
>>>
>>>
>>>
>>> *Who: *       Bryan Wilder, Harvard University
>>>
>>>
>>>
>>>
>>> *Title:*        AI for Population Health: Melding Data and Algorithms
>>> on Networks
>>>
>>> *Abstract:  *As exemplified by the COVID-19 pandemic, our health and
>>> wellbeing depend on a difficult-to-measure web of societal factors and
>>> individual behaviors. My research aims to build computational methods which
>>> can impact such social challenges. This effort requires new algorithmic and
>>> data-driven paradigms which span the full process of gathering costly data,
>>> learning models to understand and predict interactions, and optimizing the
>>> use of limited resources in interventions. In response to these needs, I
>>> will present methodological developments at the intersection of machine
>>> learning, optimization, and social networks which are motivated by
>>> on-the-ground collaborations on HIV prevention, tuberculosis treatment, and
>>> the COVID-19 response. These projects have produced deployed applications
>>> and policy impact. For example, I will present the development of an
>>> AI-augmented intervention for HIV prevention among homeless youth. This
>>> system was evaluated in a field test enrolling over 700 youth and found to
>>> significantly reduce key risk behaviors for HIV.
>>>
>>> *Bio:*  Bryan Wilder is a PhD student in Computer Science at Harvard
>>> University, where he is advised by Milind Tambe. His research focuses on
>>> the intersection of optimization, machine learning, and social networks,
>>> motivated by applications to population health. His work has received or
>>> been nominated for best paper awards at ICML and AAMAS, and also received
>>> second place in the INFORMS Doing Good with Good OR competition. He is
>>> supported by the Siebel Scholars program and previously received a NSF
>>> Graduate Research Fellowship.
>>>
>>> *Host:* *David McAllester* <mcallester at ttic.edu>
>>>
>>>
>>>
>>>
>>>
>>> Mary C. Marre
>>> Faculty Administrative Support
>>> *Toyota Technological Institute*
>>> *6045 S. Kenwood Avenue*
>>> *Room 517*
>>> *Chicago, IL  60637*
>>> *p:(773) 834-1757*
>>> *f: (773) 357-6970*
>>> *mmarre at ttic.edu <mmarre at ttic.edu>*
>>>
>>
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