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XPrize has selected Georgia Tech’s Veritas team for the round of 10 teams in the Digital Learning Challenge

https://www.xprize.org/challenge/digitallearning/competing-teams

The Veritas team is organized around the Virtual Ecological Research Assistant (VERA) developed by the Design & Intelligence Laboratory in Georgia Tech’s College of Computing. VERA is a virtual laboratory in which an AI research assistant enables learners to construct conceptual models of ecological phenomena and run interactive agent-based simulations of the models. It also allows access to the Smithsonian Institution’s Encyclopedia of Life. This affords learners to use large-scale domain knowledge to explore ecological systems and perform “what if” experiments to either explain an existing ecological system or predict the outcomes of changes to one. In addition, VERA enables researchers to conduct A/B experiments and supports them in analyzing the data.

The Veritas team is comprised of Georgia Tech faculty, staff, and students, including HCC Ph.D. student Sungeun An, OMSCS students Scott Bunin, Willventchy Celestine, Andrew Hornback, computing undergraduate student Stephen Buckley, Research Scientist Vrinda Nandan, and Dr. Emily Weigel in the School of Biological Sciences and Professor Ashok Goel in the School of Interactive Computing. Dr. Spencer Rugaber at Georgia Tech and Dr. Jennifer Hammock at Smithsonian Institution act as internal and external advisors, respectively. The XPrize Digital Learning Challenge started with around 300 teams and now has 10 teams left in the competition.

Ashok Goel (old bio)

Teaching
Ashok typically teaches the CS 4635/CS 7637 course on Knowledge-Based Artificial Intelligence in the fall term of each year. In the spring term, he alternates between teaching the the CS 4610/CS 7615 course on Computational Creativity, the interdisciplinary graduate course CS 6795 on Cognitive Science, and the new interdisciplinary undergraduate GT 2803 course on Invention.
Involvement
Ashok is a member of the Organizing Committee of the conference series on Advances on Cognitive Systems, and the Steering Committee of the conference series on Theory and Application of Diagrams. In 2013, we was a member of program committees of several conferences, workshops and symposia, including the Sixteenth International Conference on AI in Education (AIED 2013) in Memphis, Tennessee, the Thirty Fifth Annual Meeting of the Cognitive Science Society (CogSci 2013) in Berlin, Germany, and the Nineteenth International Conference on Engineering Design (ICED 2013) in Seoul, Korea. In 2013, he gave an invited talk to the Twenty First International Conference on Case-Based Reasoning in Saratoga Springs, New York, and was a panelist at the Biomimicry 3.8 Seventh Education Summit and Global Conference in Boston, Massachusetts. He is scheduled to give talks at the Dept. of Cognitive Science at University of California at San Diego, the San Diego Zoo’s Conference on Bioinspiration, the College of Life Sciences at Arizona State University, the AAAI 2013 Fall Symposium on Discovery Informatics, and the Second Conference on Advances in Cognitive Systems.
Ashok is an Associate Editor of IEEE Intelligent Systems, ASME Transactions: Journal of Computing and Information Science in Engineering (JCISE), Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AIEDAM), Biologically Inspired Cognitive Architectures, and Advances in Cognitive Systems. He also serves on the editorial boards of AAAI’s AI Magazine, Journal of Experimental and Theoretical Artificial Intelligence (JETAI), Advanced Engineering Informatics (AEI), and Design Creativity and Innovation.
Ashok serves on the Board of Directors of the Biomimicry 3.8 Institute, and is a member of BID Community Think Tank that publishes the Bioinspired! digital magazine. He is a life member of the Association for Advancement of Artificial Intelligence, and a member of ACM, IEEE, ASME, the Cognitive Science Society and the Design Society SIG on Design Creativity.
Books/Media
Ashok recently co-edited the first ever book on computational methods and tools for biologically inspired design. In 2011, his Design & Intelligence research laboratory developed one of the first interactive tools on the web for supporting biologically inspired design; Here is a short video describing the DANE interactive tool. Ashok’s TEDx talk in 2012 summarizes some of his research on AI for biologically inspired design and environmental sustainability.
Contact
Ashok K. GoelSchool of Interactive Computing, Georgia Institute of TechnologyTechnology Square Research Building, 85 Fifth Street NWAtlanta, Georgia 30332, USAEmail: goel@cc.gatech.edu; Phone: (404) 894-4994; Fax: (404) 894-0673
Assistant
Ms. Cynthia Bryant; cebryant@cc.gatech.edu; 404-894-3807
Travel, etc.
12/12 – Advances in Cognitive Systems Conference, Mountain View, California06/13 – Panel on Interdisciplinary Education, Biomimicry 3.8 Conference, Boston07/13 – AI in Education Conference, Memphis07/13 – Keynote Address, Case-Based Reasoning Conference, Saratoga Springs, New York07/13 – AAAI Conference and EAAI Symposium, Bellevue, Washington09/13 – Biomimicry 3.8 Meeting, Yellowstone National Park, Montana10/02-03/13 – IBM Meeting on Cognitive Systems, Yorktown Heights, New York11/05-08/13 – Talk at Dept. of Cognitive Science, University of California at San Diego, Panel on Research on Bioinspiration at San Diego Zoo’s Conference on Bioinspiration, San Diego, and Invited Talk at Arizona State University, Tempe, Arizona11/15-17/13 – AAAI Fall Symposium on Discovery Informatics, Arlington, Virginia12/12-12/13 – Advances in Cognitive Systems Conference, UMBC, Baltimore, Maryland
Personal
Ashok has two sons:
Kunal (17 years old), a senior in the Dekalb County Magnet Program for High Achievers at Chamblee Charter High School, Vice-President of the Student Government and Co-Captain of the Tennis Team; and
Gautam (19), a junior in the Honors Program at Georgia Tech with a double major in Mathematics and Computer Science, and a recipient of the 2013 Goldwater Award.

Get Involved

Date: Mar 11, 2021

Job Description: The is a full-time post-doctoral Research Scientist I position in the School of Interactive Computing at Georgia Tech. The Research Scientist will focus on designing and developing AI techniques and tools for supporting online and blended learning, and for deploying and evaluating them at scale within Georgia Tech. We are especially interested in further developing, deploying, and analyzing extant AI technologies for intelligent tutors, conversational agents, question answering,  social interactions, virtual laboratories, and virtual librarians. In particular, the Research Scientist will work with the faculty and students in Georgia Tech’s Design & Intelligence Laboratory to help develop these technologies and work with faculty and students across Georgia Tech to deploy and evaluate them.
This position requires expertise in AI as well as human learning and education. It also requires skills in software development, project management, data collection and analysis, documentation, as well as working with people. 

Contact: Professor Ashok Goel at goel@cc.gatech.edu

PAIP-Python

Python implementations of some of the classic AI programs from Peter Norvig’s fantastic textbook “Paradigms of Artificial Intelligence Programming.”

Visit the main PAIP-Python site here.

This is meant to be a learning resource for beginning AI programmers. Although PAIP is a fantastic book, it is no longer common for students to have a background in Lisp programming, as many universities have replaced Lisp with other languages in introductory programming and introductory artificial intelligence courses. It is my hope that making the programs from PAIP available in a commonly-taught language will provide a useful hands-on resource for beginning AI students.

These programs were written by Daniel Connelly at Georgia Tech as an independent project supervised by Professor Ashok Goel.

From Design Cases to Generic Mechanisms

Analogical reasoning plays an important role in design. In particular, cross-domain analogies appear to be important in innovative and creative design. However, making cross-domain analogiesis hard and often requires abstractions common to the source and target domains. Recent work in case-based design suggests that generic mechanisms are one type of abstractions useful in adapting past designs. However, one important yet unexplored issue is where these generic mechanisms come from. We hypothesize that they are acquired incrementally from design experiences in familiar domains by generalization over patterns of regularity. Three important issues in generalization from experiences are what to generalize from an experience, how far to generalize, and what methods to use. In this paper, we describe how structure-behaviorfunction models of designs in a familiar domain provide the content, and togetherwith the problem-solving context in which learning occurs, also provide the constraints for learning generic mechanismsfrom design experiences. In particular, we describe the model-based learning method with a scenario of learning of feedback mechanism.