[Theory] REMINDER: 2/23 Talks at TTIC: Mariya Toneva, Carnegie Mellon

[Mary Marre]

*When:*      Tuesday, February 23rd at* 11:10 am CT*



*Where:*     Zoom Virtual Talk (*register in advance here
<https://uchicagogroup.zoom.us/webinar/register/WN_aV-p8VthSFCwBpSU3XmbBA>*)


*Who: *       Mariya Toneva, Carnegie Mellon University


*Title: *Data-Driven Transfer of Insight between Brains and AI Systems

*Abstract:* Several major innovations in artificial intelligence (AI) (e.g.
convolutional neural networks, experience replay) are based on findings
about the brain. However, the underlying brain findings took many years to
first consolidate and many more to transfer to AI. Moreover, these findings
were made using invasive methods in non-human species. For cognitive
functions that are uniquely human, such as natural language processing,
there is no suitable model organism and a mechanistic understanding is that
much farther away.

In this talk, I will present my research program that circumvents these
limitations by establishing a direct connection between the human brain and
AI systems with two main goals: 1) to improve the generalization
performance of AI systems and 2) to improve our mechanistic understanding
of cognitive functions. Lastly, I will discuss future directions that build
on these approaches to investigate the role of memory in meaning
composition, both in the brain and AI. This investigation will lead to
methods that can be applied to a wide range of AI domains, in which it is
important to adapt to new data distributions, continually learn to perform
new tasks, and learn from few samples.

*Bio:* Mariya Toneva is a Ph.D. candidate in a joint program between
Machine Learning and Neural Computation at Carnegie Mellon University,
where she is advised by Tom Mitchell and Leila Wehbe. She received a B.S.
in Computer Science and Cognitive Science from Yale University. Her
research is at the intersection of Artificial Intelligence, Machine
Learning, and Neuroscience. Mariya works on bridging language in machines
with language in the brain, with a focus on building computational models
of language processing in the brain that can also improve natural language
processing systems.

*Host:* Karen Livescu <klivescu 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 Wed, Feb 17, 2021 at 2:40 PM Mary Marre <mmarre at ttic.edu> wrote:

> *When:*      Tuesday, February 23rd at* 11:10 am CT*
>
>
>
> *Where:*     Zoom Virtual Talk (*register in advance here
> <https://uchicagogroup.zoom.us/webinar/register/WN_aV-p8VthSFCwBpSU3XmbBA>*
> )
>
>
> *Who: *       Mariya Toneva, Carnegie Mellon University
>
>
> *Title: *Data-Driven Transfer of Insight between Brains and AI Systems
>
> *Abstract:* Several major innovations in artificial intelligence (AI)
> (e.g. convolutional neural networks, experience replay) are based on
> findings about the brain. However, the underlying brain findings took many
> years to first consolidate and many more to transfer to AI. Moreover, these
> findings were made using invasive methods in non-human species. For
> cognitive functions that are uniquely human, such as natural language
> processing, there is no suitable model organism and a mechanistic
> understanding is that much farther away.
>
> In this talk, I will present my research program that circumvents these
> limitations by establishing a direct connection between the human brain and
> AI systems with two main goals: 1) to improve the generalization
> performance of AI systems and 2) to improve our mechanistic understanding
> of cognitive functions. Lastly, I will discuss future directions that build
> on these approaches to investigate the role of memory in meaning
> composition, both in the brain and AI. This investigation will lead to
> methods that can be applied to a wide range of AI domains, in which it is
> important to adapt to new data distributions, continually learn to perform
> new tasks, and learn from few samples.
>
> *Bio:* Mariya Toneva is a Ph.D. candidate in a joint program between
> Machine Learning and Neural Computation at Carnegie Mellon University,
> where she is advised by Tom Mitchell and Leila Wehbe. She received a B.S.
> in Computer Science and Cognitive Science from Yale University. Her
> research is at the intersection of Artificial Intelligence, Machine
> Learning, and Neuroscience. Mariya works on bridging language in machines
> with language in the brain, with a focus on building computational models
> of language processing in the brain that can also improve natural language
> processing systems.
>
> *Host:* Karen Livescu <klivescu 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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