PhD Proposal by Arjun Chandrasekaran

Event Details
  • Date/Time:
    • Thursday November 29, 2018
      10:00 am - 11:30 am
  • Location: CCB 360B
  • Phone:
  • URL:
  • Email:
  • Fee(s):
    N/A
  • Extras:
Contact
No contact information submitted.
Summaries

Summary Sentence: Towards natural human-AI interactions in vision and language

Full Summary: No summary paragraph submitted.

Title: Towards natural human-AI interactions in vision and language

 

Date: Thursday, November 29 2018

Time: 10:00AM - 11:30AM (ET)

Location: CCB 360B

 

Arjun Chandrasekaran

Ph.D. Student in Computer Science

School of Interactive Computing 

Georgia Institute of Technology

http://www.prism.gatech.edu/~arjun9/

 

Committee:

Dr. Devi Parikh (Advisor, School of Interactive Computing, Georgia Institute of Technology)

Dr. Dhruv Batra (School of Interactive Computing, Georgia Institute of Technology)

Dr. Sonia Chernova (School of Interactive Computing, Georgia Institute of Technology)

Dr. Mohit Bansal (Computer Science Dept., University of North Carolina at Chapel Hill)

 

Abstract:

Inter-human interaction is a rich form of communication. Human interactions typically leverage a good theory of mind, involve pragmatics, story-telling, humor, sarcasm, empathy, sympathy, etc. Current human-AI interactions, however, lack many of these features that characterize inter-human interactions. Towards the goal of developing AI that can interact with humans naturally (similar to other humans), in this dissertation, I take steps towards studying aspects of humor, story-telling, and theory of (AI's) mind. 

Specifically, I 

1. Build computational models for humor manifested in static images, and contextual, multi-modal humor. 

2. Introduce a picture-sequencing task where a computational model learns the correct temporal order of events in a story. 

3. Evaluate different factors that influence the extent to which a lay person can predict the behavior of an AI, i.e., a person's theory of the AI's mind. 

 

In proposed work, I will evaluate the extent to which interpretable AI approaches improve the overall performance of a human-AI team in a goal-driven, cooperative task.

 

Additional Information

In Campus Calendar
No
Groups

Graduate Studies

Invited Audience
Public, Graduate students, Undergraduate students
Categories
Other/Miscellaneous
Keywords
Phd proposal
Status
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: Nov 26, 2018 - 10:36am
  • Last Updated: Nov 26, 2018 - 10:36am