[Theory] TODAY: 3/20 Talks at TTIC: Unnat Jain, CMU and Meta

Mary Marre mmarre at ttic.edu
Wed Mar 20 08:30:00 CDT 2024


*When:*        Wednesday, March 20, 2024 at* 11:00** a**m CT   *


*Where:       *Talk will be given *live, in-person* at

                   TTIC, 6045 S. Kenwood Avenue

                   5th Floor, Room 530


*Virtually:*   *via *Panopto (*livestream
<https://uchicago.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=217717de-08bf-4bdc-b235-b133003455b7>*
)

*                         *limited access: see info below*



*Who: *         Unnat Jain, CMU and Meta
------------------------------
*Title:*          Jump-starting Embodied Intelligence

*Abstract: *AI has revolutionized the way we interact online. Despite this,
it hasn't quite made the leap when it comes to tasks like cooking dinner or
cleaning our desks. Why has AI excelled in automating our digital
interactions but not in assisting us with physical tasks? In my talk, I
will explore the challenges of applying AI to embodied tasks—those
requiring physical interaction with the environment. To address these
challenges, I turn to the efficient pathways humans use to achieve embodied
intelligence and propose three strategies to 'jump-start' the learning
process for embodied AI agents: (1) combining learning from both teachers
and own experience, (2) leveraging external information or “hints” to
simplify learning, such as using maps to learn about physical spaces, and
(3) learning intelligent behaviors by simply observing others. These
strategies integrate insights from perception and machine learning to
bridge the gap between digital AI and embodied intelligence, ultimately
enhancing AI's usefulness and integration into our physical world.

*Bio:* Unnat Jain is a postdoctoral researcher at Carnegie Mellon
University and Fundamental AI Research (FAIR) at Meta, where he works with
Abhinav Gupta, Deepak Pathak, and Xinlei Chen. He received his PhD in
Computer Science from UIUC, working with Alexander Schwing and Svetlana
Lazebnik and collaborating with Google DeepMind and Allen Institute for AI.
His research focuses on embodied intelligence, bridging computer vision
(perception) and robot learning (action). Unnat is committed to fostering a
collaborative research community and serves as an area chair at CVPR and
NeurIPS, and has co-led workshops such as Adaptive Robotics (CoRL) and
'Scholars & Big Models: How Can Academics Adapt?' (CVPR). Unnat's
achievements have been recognized with several awards, including the Mavis
Future Faculty Fellowship, Director’s Gold Medal at IIT Kanpur, Siebel
Scholars, two best thesis awards, Microsoft and Google Fellowship
nominations, and was a finalist of the Qualcomm Fellowship. Website:
https://unnat.github.io/

*Host: **Matthew Walter* <mwalter at ttic.edu>

*Access to this livestream is limited to TTIC / UChicago (press panopto
link and sign in to your UChicago account with CNetID).




Mary C. Marre
Faculty Administrative Support
*Toyota Technological Institute*
*6045 S. Kenwood Avenue, Rm 517*
*Chicago, IL  60637*
*773-834-1757*
*mmarre at ttic.edu <mmarre at ttic.edu>*


On Tue, Mar 19, 2024 at 1:36 PM Mary Marre <mmarre at ttic.edu> wrote:

> *When:*        Wednesday, March 20, 2024 at* 11:00** a**m CT   *
>
>
> *Where:       *Talk will be given *live, in-person* at
>
>                    TTIC, 6045 S. Kenwood Avenue
>
>                    5th Floor, Room 530
>
>
> *Virtually:*   *via *Panopto (*livestream
> <https://uchicago.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=217717de-08bf-4bdc-b235-b133003455b7>*
> )
>
> *                         *limited access: see info below*
>
>
>
> *Who: *         Unnat Jain, CMU and Meta
> ------------------------------
> *Title:*          Jump-starting Embodied Intelligence
>
> *Abstract: *AI has revolutionized the way we interact online. Despite
> this, it hasn't quite made the leap when it comes to tasks like cooking
> dinner or cleaning our desks. Why has AI excelled in automating our digital
> interactions but not in assisting us with physical tasks? In my talk, I
> will explore the challenges of applying AI to embodied tasks—those
> requiring physical interaction with the environment. To address these
> challenges, I turn to the efficient pathways humans use to achieve embodied
> intelligence and propose three strategies to 'jump-start' the learning
> process for embodied AI agents: (1) combining learning from both teachers
> and own experience, (2) leveraging external information or “hints” to
> simplify learning, such as using maps to learn about physical spaces, and
> (3) learning intelligent behaviors by simply observing others. These
> strategies integrate insights from perception and machine learning to
> bridge the gap between digital AI and embodied intelligence, ultimately
> enhancing AI's usefulness and integration into our physical world.
>
> *Bio:* Unnat Jain is a postdoctoral researcher at Carnegie Mellon
> University and Fundamental AI Research (FAIR) at Meta, where he works with
> Abhinav Gupta, Deepak Pathak, and Xinlei Chen. He received his PhD in
> Computer Science from UIUC, working with Alexander Schwing and Svetlana
> Lazebnik and collaborating with Google DeepMind and Allen Institute for AI.
> His research focuses on embodied intelligence, bridging computer vision
> (perception) and robot learning (action). Unnat is committed to fostering a
> collaborative research community and serves as an area chair at CVPR and
> NeurIPS, and has co-led workshops such as Adaptive Robotics (CoRL) and
> 'Scholars & Big Models: How Can Academics Adapt?' (CVPR). Unnat's
> achievements have been recognized with several awards, including the Mavis
> Future Faculty Fellowship, Director’s Gold Medal at IIT Kanpur, Siebel
> Scholars, two best thesis awards, Microsoft and Google Fellowship
> nominations, and was a finalist of the Qualcomm Fellowship. Website:
> https://unnat.github.io/
>
> *Host: **Matthew Walter* <mwalter at ttic.edu>
>
> *Access to this livestream is limited to TTIC / UChicago (press panopto
> link and sign in to your UChicago account with CNetID).
>
>
>
> Mary C. Marre
> Faculty Administrative Support
> *Toyota Technological Institute*
> *6045 S. Kenwood Avenue, Rm 517*
> *Chicago, IL  60637*
> *773-834-1757*
> *mmarre at ttic.edu <mmarre at ttic.edu>*
>
>
> On Wed, Mar 13, 2024 at 10:18 PM Mary Marre <mmarre at ttic.edu> wrote:
>
>> *When:*        Wednesday, March 20, 2024 at* 11:00** a**m CT   *
>>
>>
>> *Where:       *Talk will be given *live, in-person* at
>>
>>                    TTIC, 6045 S. Kenwood Avenue
>>
>>                    5th Floor, Room 530
>>
>>
>> *Virtually:*   *via *Panopto (*livestream
>> <https://uchicago.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=217717de-08bf-4bdc-b235-b133003455b7>*
>> )
>>
>> *                         *limited access: see info below*
>>
>>
>>
>> *Who: *         Unnat Jain, CMU and Meta
>> ------------------------------
>> *Title:*          Jump-starting Embodied Intelligence
>>
>> *Abstract: *AI has revolutionized the way we interact online. Despite
>> this, it hasn't quite made the leap when it comes to tasks like cooking
>> dinner or cleaning our desks. Why has AI excelled in automating our digital
>> interactions but not in assisting us with physical tasks? In my talk, I
>> will explore the challenges of applying AI to embodied tasks—those
>> requiring physical interaction with the environment. To address these
>> challenges, I turn to the efficient pathways humans use to achieve embodied
>> intelligence and propose three strategies to 'jump-start' the learning
>> process for embodied AI agents: (1) combining learning from both teachers
>> and own experience, (2) leveraging external information or “hints” to
>> simplify learning, such as using maps to learn about physical spaces, and
>> (3) learning intelligent behaviors by simply observing others. These
>> strategies integrate insights from perception and machine learning to
>> bridge the gap between digital AI and embodied intelligence, ultimately
>> enhancing AI's usefulness and integration into our physical world.
>>
>> *Bio:* Unnat Jain is a postdoctoral researcher at Carnegie Mellon
>> University and Fundamental AI Research (FAIR) at Meta, where he works with
>> Abhinav Gupta, Deepak Pathak, and Xinlei Chen. He received his PhD in
>> Computer Science from UIUC, working with Alexander Schwing and Svetlana
>> Lazebnik and collaborating with Google DeepMind and Allen Institute for AI.
>> His research focuses on embodied intelligence, bridging computer vision
>> (perception) and robot learning (action). Unnat is committed to
>> fostering a collaborative research community and serves as an area chair at
>> CVPR and NeurIPS, and has co-led workshops such as Adaptive Robotics (CoRL)
>> and 'Scholars & Big Models: How Can Academics Adapt?' (CVPR). Unnat's
>> achievements have been recognized with several awards, including the Mavis
>> Future Faculty Fellowship, Director’s Gold Medal at IIT Kanpur, Siebel
>> Scholars, two best thesis awards, Microsoft and Google Fellowship
>> nominations, and was a finalist of the Qualcomm Fellowship. Website:
>> https://unnat.github.io/
>>
>> *Host: **Matthew Walter* <mwalter at ttic.edu>
>>
>> *Access to this livestream is limited to TTIC / UChicago (press panopto
>> link and sign in to your UChicago account with CNetID).
>>
>>
>>
>>
>> Mary C. Marre
>> Faculty Administrative Support
>> *Toyota Technological Institute*
>> *6045 S. Kenwood Avenue, Rm 517*
>> *Chicago, IL  60637*
>> *773-834-1757*
>> *mmarre at ttic.edu <mmarre at ttic.edu>*
>>
>
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