[4eyes] FW: [FACULTY] TODAY: CS Faculty Candidate Aishwarya Agrawal Thursday, January 31st HFH 1132 3:30 PM

[Matthew Turk]

Just a(nother) reminder of today's faculty candidate talk, very relevant to
the lab:
 


Faculty Candidate
Aishwarya Agrawal
Thursday, January 31, 2019
HFH 1132 3:30 PM
Host: Xifeng Yan 
 
Title: Visual Question Answering and Beyond
 
Abstract:
In this talk, I will present our work on a multi-modal AI task called Visual
Question Answering (VQA) -- given an image and a natural language question
about the image (e.g., "What kind of store is this?", "Is it safe to cross
the street?"), the machine's task is to automatically produce an accurate
natural language answer ("bakery", "yes"). Applications of VQA include --
aiding visually impaired users in understanding their surroundings, aiding
analysts in examining large quantities of surveillance data, teaching
children through interactive demos, interacting with personal AI assistants,
and making visual social media content more accessible.
 
Specifically, I will provide a brief overview of the VQA task, dataset and
baseline models, highlight some of the problems with existing VQA models,
and talk about how to fix some of these problems by proposing -- 1) a new
evaluation protocol,  2) a new model architecture, and 3) a novel objective
function.
 
Most of my past work has been towards building agents that can 'see' and
'talk'. However, for a lot of practical applications (e.g., physical agents
navigating inside our houses executing natural language commands) we need
agents that can not only 'see' and 'talk' but can also take actions. Towards
the end of the talk, I will present future directions towards generalizing
vision and language agents to be able to take actions.
 
Bio:
Aishwarya Agrawal is a fifth year Ph.D. student in the School of Interactive
Computing at Georgia Tech, working with Dhruv Batra and Devi Parikh. Her
research interests lie at the intersection of computer vision, deep learning
and natural language processing. The Visual Question Answering (VQA) work by
Aishwarya and her colleagues has witnessed tremendous interest in a short
period of time. 
 
Aishwarya is a recipient of the Facebook Fellowship 2019-2020 (declined) and
NVIDIA Graduate Fellowship 2018-2019. Aishwarya was selected for the Rising
Stars in EECS 2018. She was also a finalist of the Foley Scholars Award 2018
and Microsoft and Adobe Research Fellowships 2017-2018. As a research intern
Aishwarya has spent time at Google DeepMind, Microsoft Research and Allen
Institute for Artificial Intelligence. 
 
Aishwarya led the organization of the first VQA challenge and workshop at
CVPR 2016 and co-organized the second and the third VQA challenges and
workshops at CVPR 2017 and CVPR 2018. As a reviewer, she has served on the
program committee of various conferences (CVPR, ICCV, ECCV, NIPS, ICLR) and
a journal (IJCV). She was awarded an Outstanding Reviewer award twice (NIPS
2017 and CVPR 2017). 
 
Aishwarya received her bachelor's degree in Electrical Engineering with a
minor in Computer Science and Engineering from Indian Institute of
Technology (IIT) Gandhinagar in 2014. 
 
Webpage: https://www.cc.gatech.edu/~aagrawal307/
 
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