Ashok Goel

Last updated
Ashok Goel
Ashok1-2012.jpg
Born
New Delhi, India
Alma mater Ohio State University
Awards AAAI Fellow, Fellow of Cognitive Science Society
Scientific career
Fields Artificial Intelligence, Cognitive Science, Computer-Aided Design, Educational Technology
Institutions Ohio State University, Georgia Institute of Technology
Thesis Integrating Case-Based Reasoning and Model-Based Reasoning for Adaptive Design Problem Solving (1989)
Doctoral advisor Balakrishnan Chandrasekaran
Doctoral students Jim Davies, Eleni Stroulia
Website http://dilab.gatech.edu/ashok-k-goel/

Ashok K. Goel is a professor of computer science and human-centered computing in the School of Interactive Computing at Georgia Institute of Technology, and the chief scientist with Georgia Tech's Center for 21st Century Universities. [1] He conducts research into cognitive systems at the intersection of artificial intelligence and cognitive science with a focus on computational design and creativity. Goel is also the executive director of National Science Foundation's AI Institute for Adult Learning and Online Education [2] and an editor emeritus of AAAI's AI Magazine. [3]

Contents

Research and scholarship

Conceptual design of technical systems, in particular biologically inspired engineering, provides one context for Goel's problem-driven research into cognitive systems. He has developed a theory of Structure-Behavior-Function models for understanding conceptual designs [4] [5] and a theory of model-based analogical reasoning for understanding the processes of biologically inspired design. [6] [7] In addition to information-processing theories of conceptual design, [8] [9] he has built computational tools (such as the Design by Analogy to Nature Engine) for supporting its practice. [10] [11] His 2012 TEDx talk Does Our Future Require Us To Go Back to Nature? summarizes this research. [12] In 2014, he co-edited Biologically inspired design: Computational methods and tools [13] published by Springer-Verlag. During 2008–18, Ashok was a co-director of Georgia Tech's Center of Biologically Inspired Design, and during 2012-17 he served on the Board of Directors of The Biomimicry Institute including as the President of the Board during 2015–17.[ citation needed ]

Learning about complex systems and systems thinking provides another context for Goel's use-inspired cognitive systems research. He has used Structure-Behavior-Function modeling to develop a series of interactive environments for supporting learning about complex systems [14] [15] resulting in the recent web-based virtual experimentation research assistant (VERA). Smithsonian Institution's Encyclopedia of Life's webportal provides direct access to VERA to support learning about ecological systems and the scientific way of systems thinking. [16] Since 2015, Ashok has been a Faculty Fellow of the Brook Byers Institute for Sustainable Systems.

Teaching and scholarship

During 2012–19, Ashok was the Director of Georgia Tech's Ph.D. Program in Human-Centered Computing. Since 2019, he has been the Chief Scientist with the Georgia Tech's Center for 21st Century Universities, where he leads research on AI in education and education in AI. In 2014, Goel developed an online course on Knowledge-Based AI as part of Georgia Tech's Online Master of Science in Computer Science program. [17] In 2016, he developed Jill Watson, a virtual teaching assistant for automatically answering students’ questions in discussion forums of online classes based on the IBM Watson technology. His 2016 TEDx talk A Teaching Assistant named Jill Watson describes this experiment. [18] In 2019, he co-edited Blended learning in practice: A guide for researchers and practitioners [19] published by the MIT Press. He received AAAI's Outstanding AI Educator Award in 2019 and the University System of Georgia Regent's Award for Scholarship of Teaching and Learning in 2020.

Goel's teaching and research have been covered in The Wall Street Journal , [20] The Washington Post , [21] Wired , [22] and EdTech [23] among other media. A review article in a special issue of The Chronicle of Higher Education called virtual assistants exemplified by Jill Watson as one of the most transformative educational technologies in the digital era. [24]

Related Research Articles

Bio-inspired computing, short for biologically inspired computing, is a field of study which seeks to solve computer science problems using models of biology. It relates to connectionism, social behavior, and emergence. Within computer science, bio-inspired computing relates to artificial intelligence and machine learning. Bio-inspired computing is a major subset of natural computation.

Neuromorphic computing is an approach to computing that is inspired by the structure and function of the human brain. A neuromorphic computer/chip is any device that uses physical artificial neurons to do computations. In recent times, the term neuromorphic has been used to describe analog, digital, mixed-mode analog/digital VLSI, and software systems that implement models of neural systems. The implementation of neuromorphic computing on the hardware level can be realized by oxide-based memristors, spintronic memories, threshold switches, transistors, among others. Training software-based neuromorphic systems of spiking neural networks can be achieved using error backpropagation, e.g., using Python based frameworks such as snnTorch, or using canonical learning rules from the biological learning literature, e.g., using BindsNet.

<span class="mw-page-title-main">Association for the Advancement of Artificial Intelligence</span> International scientific society

The Association for the Advancement of Artificial Intelligence (AAAI) is an international scientific society devoted to promote research in, and responsible use of, artificial intelligence. AAAI also aims to increase public understanding of artificial intelligence (AI), improve the teaching and training of AI practitioners, and provide guidance for research planners and funders concerning the importance and potential of current AI developments and future directions.

Soar is a cognitive architecture, originally created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University.

<span class="mw-page-title-main">Conference on Neural Information Processing Systems</span> Machine-learning and computational-neuroscience conference

The Conference and Workshop on Neural Information Processing Systems is a machine learning and computational neuroscience conference held every December. The conference is currently a double-track meeting that includes invited talks as well as oral and poster presentations of refereed papers, followed by parallel-track workshops that up to 2013 were held at ski resorts.

A cognitive architecture refers to both a theory about the structure of the human mind and to a computational instantiation of such a theory used in the fields of artificial intelligence (AI) and computational cognitive science. The formalized models can be used to further refine a comprehensive theory of cognition and as a useful artificial intelligence program. Successful cognitive architectures include ACT-R and SOAR. The research on cognitive architectures as software instantiation of cognitive theories was initiated by Allen Newell in 1990.

<span class="mw-page-title-main">Jaime Carbonell</span> American computer scientist (1953–2020)

Jaime Guillermo Carbonell was a computer scientist who made seminal contributions to the development of natural language processing tools and technologies. His extensive research in machine translation resulted in the development of several state-of-the-art language translation and artificial intelligence systems. He earned his B.S. degrees in Physics and in Mathematics from MIT in 1975 and did his Ph.D. under Dr. Roger Schank at Yale University in 1979. He joined Carnegie Mellon University as an assistant professor of computer science in 1979 and lived in Pittsburgh from then. He was affiliated with the Language Technologies Institute, Computer Science Department, Machine Learning Department, and Computational Biology Department at Carnegie Mellon.

Janet Lynne Kolodner is an American cognitive scientist and learning scientist. She is a Professor of the Practice at the Lynch School of Education at Boston College and co-lead of the MA Program in Learning Engineering. She is also Regents' Professor Emerita in the School of Interactive Computing, College of Computing at the Georgia Institute of Technology. She was Founding Editor in Chief of The Journal of the Learning Sciences and served in that role for 19 years. She was Founding Executive Officer of the International Society of the Learning Sciences (ISLS). From August, 2010 through July, 2014, she was a program officer at the National Science Foundation and headed up the Cyberlearning and Future Learning Technologies program. Since finishing at NSF, she is working toward a set of projects that will integrate learning technologies coherently to support disciplinary and everyday learning, support project-based pedagogy that works, and connect to the best in curriculum for active learning. As of July, 2020, she

The School of Interactive Computing is an academic unit located within the College of Computing at the Georgia Institute of Technology. It conducts both research and teaching activities related to interactive computing at the undergraduate and graduate levels. These activities focus on computing's interaction with users and the environment, as well as how computers impact the quality of people's lives.

<span class="mw-page-title-main">Computational creativity</span> Multidisciplinary endeavour

Computational creativity is a multidisciplinary endeavour that is located at the intersection of the fields of artificial intelligence, cognitive psychology, philosophy, and the arts.

A probabilistic logic network (PLN) is a conceptual, mathematical and computational approach to uncertain inference; inspired by logic programming, but using probabilities in place of crisp (true/false) truth values, and fractional uncertainty in place of crisp known/unknown values. In order to carry out effective reasoning in real-world circumstances, artificial intelligence software must robustly handle uncertainty. However, previous approaches to uncertain inference do not have the breadth of scope required to provide an integrated treatment of the disparate forms of cognitively critical uncertainty as they manifest themselves within the various forms of pragmatic inference. Going beyond prior probabilistic approaches to uncertain inference, PLN is able to encompass within uncertain logic such ideas as induction, abduction, analogy, fuzziness and speculation, and reasoning about time and causality.

The LIDA cognitive architecture is an integrated artificial cognitive system that attempts to model a broad spectrum of cognition in biological systems, from low-level perception/action to high-level reasoning. Developed primarily by Stan Franklin and colleagues at the University of Memphis, the LIDA architecture is empirically grounded in cognitive science and cognitive neuroscience. In addition to providing hypotheses to guide further research, the architecture can support control structures for software agents and robots. Providing plausible explanations for many cognitive processes, the LIDA conceptual model is also intended as a tool with which to think about how minds work.

Jim Davies is an American/Canadian cognitive scientist, playwright, artist, and author. He received his bachelor's degree in philosophy from the State University of New York at Oswego, his masters in psychology and his Ph.D. in computer science from the Georgia Institute of Technology. He is a full professor of Cognitive Science at the Institute of Cognitive Science and the School of Computer Science at Carleton University in Ottawa, Ontario where he is the director of the Science of Imagination Laboratory. His research focuses on visual reasoning, analogy, and imagination.

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References

  1. ↑ "Home | Center for 21st Century Universities". c21u.gatech.edu. Archived from the original on 2022-04-01. Retrieved 2022-04-06.
  2. ↑ admin. "Home". National AI Institute for Adult Learning and Online Education. Archived from the original on 2022-01-26. Retrieved 2022-04-06.
  3. ↑ "Editorial Team | AI Magazine". ojs.aaai.org. Archived from the original on 2022-03-02. Retrieved 2022-04-06.
  4. ↑ Structure, behavior, and function of complex systems: The structure, behavior, and function modeling language. | Ashok Goel, Spencer Rugaber & Swaroop Vattam. | AIEDAM 23(1):23-35. | 2009.
  5. ↑ A 30-year case study and 15 principles: implications of an artificial intelligence methodology for functional modeling. | Ashok Goel. | AIEDAM 27(3):203-215 | 2013.
  6. ↑ Design, analogy, and creativity | Ashok Goel. | IEEE Expert 12(3):62-70. | 1997.
  7. ↑ "Use of design patterns in analogy-based design. | Ashok Goel & Sambasiva Bhatta.", Advanced Engineering Informatics , vol. 18, no. 2, pp. 85–94, 2004
  8. ↑ Biologically Inspired Design: Process and Products. | Michael Helms, Swaroop Vattam & Ashok Goel. | Design Studies 30(5):606-622. | 2009.
  9. ↑ A content account of creative analogies in biologically inspired design | Swaroop Vattam, Michael Helms & Ashok Goel. | AIEDAM 24(4). | 2010.
  10. ↑ Cognitive, collaborative, conceptual and creative—four characteristics of the next generation of knowledge-based CAD systems: a study in biologically inspired design. | Ashok Goel Swaroop Vattm, Bryan Wiltgen & Michael Helms. | Computer-Aided Design 44(10):879-900. | 2012.
  11. ↑ The four-box method: problem formulation and analogy evaluation in biologically inspired design. | Michael Helms & Ashok Goel. | Journal of Mechanical Design 136(11). | 2014.
  12. ↑ TEDx Talks (2012-11-12), Does Our Future Require Us To Go Back to Nature? | Ashok Goel | TEDxPeachtree
  13. ↑ Biologically inspired design: Computational methods and tools. | Ashok Goel, Daniel McAdams & Robert Stone (editors).| Springer-Verlag.
  14. ↑ Towards design learning environments—I: Exploring how devices work. | AK Goel, AG de Silva Garza, N Grué, JW Murdock, MM Recker, T. Govindraj. | Proceedings of the International conference on intelligent tutoring systems, LNCS 1086, pp. 493-501. | 1996.
  15. ↑ Understanding complex natural systems by articulating structure-behavior-function models. | SS Vattam, AK Goel, S Rugaber, CE Hmelo-Silver, R Jordan, S Gray. | Journal of Educational Technology & Society 14(1):66-81. | 2011.
  16. ↑ The Scientific Way of Thinking Using VERA., 2019-09-16, archived from the original on 2022-04-06, retrieved 2021-02-16
  17. ↑ "CS 7637: Knowledge-Based Artificial Intelligence: Cognitive Systems | OMSCS | Georgia Institute of Technology | Atlanta, GA". www.omscs.gatech.edu. Archived from the original on 2017-08-01. Retrieved 2017-08-01.
  18. ↑ TEDx Talks (2016-11-01), A teaching assistant named Jill Watson | Ashok Goel | TEDxSanFrancisco
  19. ↑ Blended learning in practice: A guide for researchers and practitioners. | Amanda Madden, Lauren Margulieux, Robert Kadel & Ashok Goel (editors). | The MIT Press.
  20. ↑ Korn, Melissa (2016-05-06), "Imagine Discovering That Your Teaching Assistant Really Is a Robot | Melissa Korn", Wall Street Journal, archived from the original on 2017-12-28, retrieved 2017-12-29
  21. ↑ What happened when a professor built a chatbot to be his teaching assistant | Matt MacFarland, 2016-05-11, archived from the original on 2021-02-02, retrieved 2021-02-15
  22. ↑ Leopold, Todd (2016-12-13), "A Secret Ops AI Aims to Save Education | Todd Lepold", Wired, archived from the original on 2021-01-17, retrieved 2021-02-15
  23. ↑ Improve Online Learning and More with Artificial Intelligence | Tommy Peterson, 2020-05-05, archived from the original on 2021-03-01, retrieved 2021-02-15
  24. ↑ The Digital Era. | Ben Myers & Erica Lusk, 2016-12-15, archived from the original on 2021-07-04, retrieved 2021-02-15
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