EAAI-21 Program Schedule
last updated: March 29, 2021
Saturday, February 6, 2021
9:30am - 5:15pm EST
Saturday Video Recordings of Presentations
[9:30-10:45am] Talking to the Public about AI
Michael Wooldridge - University of Oxford and Alan Turing Institute, London
Since everything went crazy in AI, around 2012, I, like many other members of our community, have frequently found myself put in the position of having to talk about our field to a non-specialist audience. I've been interviewed on TV and radio, and spoken to endless university committees, government committees, and industrial conferences. More recently, following the publication of my two popular science books (the Ladybird Expert Guide to AI [2018], and The Road to Conscious Machines [2020]), I've even begun speaking at a literary festivals (believe me, I never expected to be doing this as a PhD student studying multiagent systems back in 1989). In this talk, I will relate these experiences, the mistakes I made, and what I learned from them – how our field is perceived, what people fear, hope, and expect from it, and how best to communicate excitement about the very real progress we've made recently with a realistic understanding of where we are and where we are going.
Michael Wooldridge is the winner of this year’s Outstanding Educator award. He is a Professor of Computer Science and Head of Department of Computer Science at the University of Oxford, and a programme director for AI at the Alan Turing Institute. He is a Fellow of the ACM, the Association for the Advancement of AI (AAAI), and the European Association for AI (EurAI). From 2014-16, he was President of the European Association for AI, and from 2015-17 he was President of the International Joint Conference on AI (IJCAI). As well as more than 400 technical articles on AI, he has published two popular science introductions to the field: The Ladybird Expert Guide to AI (2018), and The Road to Conscious Machines (Pelican, 2020).
[10:45 - 11:00] Welcome
Lisa Torrey - St. Lawrence University
Michael Guerzhoy - Princeton University
[11:00 - 11:45] Main Track
- Applied Machine Learning for Games: A Graduate School Course
Yilei Zeng, Aayush Shah, Jameson Thai, Michael Zyda
https://www.aaai.org/AAAI21Papers/EAAI-16.ZengY.pdf - Designing a Hybrid AI Residency
Felipe Leno Da Silva, Silvio Stanzani, Jefferson Coelho, Jorge Mondadori, Muriel Mazzetto, Felipe Sanches Couto, Raphael Cobe
https://www.aaai.org/AAAI21Papers/EAAI-42.SilvaFLD.pdf
[11:45 - 12:45] Main Track
- AI-Infused Collaborative Inquiry in Upper Elementary School: A Game-Based Learning Approach
Seung Lee, Bradford Mott, Anne Ottenbreit-Leftwich, Adam Scribner, Sandra Taylor, Kyungjin Park, Jonathan Rowe, Krista Glazewski, Cindy Hmelo-Silver, James Lester
https://www.aaai.org/AAAI21Papers/EAAI-26.LeeS.pdf - Introduction to Machine Learning with Robots and Playful Learning
Viktoriya Olari, Kostadin Cvejoski, Øyvind Eide
https://www.aaai.org/AAAI21Papers/EAAI-51.OlariV.pdf - Learning Artificial Intelligence: Insights into How Youth Encounter and Build Understanding of AI Concepts
Eric Greenwald, Maxyn Leitner, Ning Wang
https://www.aaai.org/AAAI21Papers/EAAI-78.GreenwaldE.pdf
[12:45 - 3:00] Gin Rummy Undergraduate Research Challenge
- Extracting Learned Discard and Knocking Strategies from a Gin Rummy Bot
Benjamin Goldstein, Jean Astudillo Guerra, Emily Haigh, Bryan Cruz Ulloa, Jeremy Blum
https://www.aaai.org/AAAI21Papers/EAAI-18.GoldsteinB.pdf - A Heuristic Evaluation Function for Hand Strength Estimation in Gin Rummy
Aqib Ahmed, Joshua Leppo, Michal Lesniewski, Riken Patel, Jonathan Perez, Jeremy Blum
https://www.aaai.org/AAAI21Papers/EAAI-21.AhmedA.pdf - Estimating Card Fitness for Discard in Gin Rummy
Jacob Gallucci, Sarah Kettell, Richard Bowser, Christian Overton
https://www.aaai.org/AAAI21Papers/EAAI-25.GallucciJ.pdf - A Deterministic Neural Network Approach to Playing Gin Rummy
Viet Dung Nguyen, Dung Doan, Todd Neller
https://www.aaai.org/AAAI21Papers/EAAI-94.NguyenVD.pdf - A Data-Driven Approach for Gin Rummy Hand Evaluation
Sang Truong, Todd Neller
https://www.aaai.org/AAAI21Papers/EAAI-92.TruongS.pdf - Opponent Hand Estimation in the Game of Gin Rummy
Peter Francis, Hoang Anh Just, Todd Neller
https://www.aaai.org/AAAI21Papers/EAAI-89.FrancisP.pdf - Knocking in the Game of Gin Rummy
Ryzeson Maravich, Taylor Neller, Todd Neller
https://www.aaai.org/AAAI21Papers/EAAI-91.MaravichR.pdf
[3:00 - 3:45] Main Track
- Visualizing NLP in Undergraduate Students' Learning about Natural Language
Cecilia Ovesdotter Alm, Alex Hedges
https://www.aaai.org/AAAI21Papers/EAAI-23.AlmCO.pdf - Deep Discourse Analysis for Generating Personalized Feedback in Intelligent Tutor Systems
Matt Grenander, Robert Belfer, Ekaterina Kochmar, Iulian Serban, François St-Hilaire, Jackie Cheung
https://www.aaai.org/AAAI21Papers/EAAI-68.GrenanderM.pdf
[3:45 - 4:30] Main Track
- Educational Question Mining At Scale: Prediction, Analysis and Personalization
Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, Jose Miguel Hernandez Lobato, Simon Peyton Jones, Richard Baraniuk, Cheng Zhang
https://www.aaai.org/AAAI21Papers/EAAI-65.WangZ.pdf - Student Knowledge Prediction for Teacher-Student Interaction
Seonghun Kim, Woojin Kim, Yeonju Jang, Heeseok Jung, Seongyune Choi, Hyeoncheol Kim
https://www.aaai.org/AAAI21Papers/EAAI-85.KimS.pdf
[4:30 - 5:15] Main Track
- Why and What to Teach: AI Curriculum for Elementary School
Seonghun Kim, Yeonju Jang, Woojin Kim, Seongyune Choi, Heeseok Jung, Soohwan Kim, Hyeoncheol Kim
https://www.aaai.org/AAAI21Papers/EAAI-84.KimS.pdf - Teacher Perspectives on How To Train Your Robot: A Middle School AI and Ethics Curriculum
Randi Williams, Stephen Kaputsos, Cynthia Breazeal
https://www.aaai.org/AAAI21Papers/EAAI-43.WilliamsR.pdf
Sunday, February 7, 2021
10:00am - 6:00pm EST
Sunday Video Recordings of Presentations
[10:00 - 11:15] Teaching Online and Blended AI Courses
Ashok Goel - Georgia Institute of Technology
Ansaf Salleb-Aouissi - Columbia University
Mehran Sehami - Stanford University
This panel is composed of AI faculty with experience teaching online and blended classes. Many of us found ourselves teaching AI courses online for the first time last year, and even after COVID-19 subsides, higher education is likely to retain online components. How will we make the most of this challenge (and opportunity)? How do we engage and bond with students online? What are the best tools for AI courses? In a blended model, which components of a course can be done best online and which are best in person? Panelists will share what they’ve learned on these topics and more.
Ashok Goel is a Professor in the School of Interactive Computing at Georgia Institute of Technology and the Chief Scientist with Georgia Tech’s Center for 21st Century Universities. In 2014, he co-developed a Udacity course on Knowledge-Based AI; in 2016, his research laboratory developed Jill Watson, a virtual teaching assistant for automatically answering questions in online classes; and in 2019, he co-edited a volume on Blended Learning published by MIT Press. Ashok received AAAI’s Outstanding AI Educator Award in 2019, and the University System of Georgia’s Hall of Fame Faculty Award for Scholarship of Teaching and Learning in 2020.
Ansaf Salleb-Aouissi is a senior lecturer in computer science with specific interests in machine learning and AI applications, including education and healthcare. She has published in top quality venues including JMLR, TPAMI, AAAI, ECML, PKDD, COLT, IJCAI, ECAI, CHILL, and AISTAT. She also has a genuine interest in education and teaching, particularly on how to translate complex topics and break up abstract concepts into a form understandable and engaging to students. Recently, she has been working on building education tools for auto-grading and self-learning to provide additional support to her students in computer science and discrete mathematics. Her EdX course on Artificial Intelligence has attracted over a quarter million learners from all over the world since 2017.
Mehran Sahami is the James and Ellenor Chesebrough Professor in Engineering and Associate Chair for Education in the Computer Science department at Stanford University. He is also the Robert and Ruth Halperin University Fellow in Undergraduate Education. He served as co-chair of the ACM/IEEE-CS joint task force on Computer Science Curricula 2013, is Past Chair of the ACM Education Board, and was appointed by the Governor of California to the state's Computer Science Strategic Implementation Plan Advisory Panel.
[11:15 - 12:15] Demos, Software Tools, and Activities for Teaching AI in K-12
- Web-based Platform for K-12 AI Education in China
Chao Wu, Yan Li, Junxiang Li, Qiongdan Zhang, Fei Wu
https://www.aaai.org/AAAI21Papers/EAAI-47.WuC.pdf - PoseBlocks: A Toolkit for Creating (and Dancing) with AI
Brian Jordan, Nisha Devasia, Jenna Hong, Randi Williams, Cynthia Breazeal
https://www.aaai.org/AAAI21Papers/EAAI-71.JordanB.pdf - Teaching Tech to Talk: K-12 Conversational Artificial Intelligence Literacy Curriculum and Development Tools
Jessica Van Brummelen, Tommy Heng, Viktoriya Tabunshchyk
https://www.aaai.org/AAAI21Papers/EAAI-20.VanBrummelenJ.pdf
[12:15 - 1:15] Demos, Software Tools, and Activities for Teaching AI in K-12
- GANs Unplugged
Patrick Virtue
https://www.aaai.org/AAAI21Papers/EAAI-75.VirtueP.pdf - What are GANs?: Introducing Generative Adversarial Networks to Middle School Students
Daniella DiPaola, Safinah Ali, Cynthia Breazeal
https://www.aaai.org/AAAI21Papers/EAAI-41.AliS.pdf - The Contour to Classification game
Irene Lee, Safinah Ali
https://www.aaai.org/AAAI21Papers/EAAI-53.LeeI.pdf
[1:15 - 3:00] Gin Rummy Undergraduate Research Challenge
- Heisenbot: A Rule-Based Game Agent for Gin Rummy
Matthew Eicholtz, Savanna Moss, Matt Traino, Christian Roberson
https://www.aaai.org/AAAI21Papers/EAAI-66.EicholtzM.pdf - A Highly-Parameterized Ensemble to Play Gin Rummy
Masayuki Nagai, Kavya Shrivastava, Kien Ta, Steven Bogaerts, Chad Byers
https://www.aaai.org/AAAI21Papers/EAAI-37.NagaiM.pdf - Random Forests for Opponent Hand Estimation in Gin Rummy
Anthony Hein, May Jiang, Vydhourie Thiyageswaran, Michael Guerzhoy
https://www.aaai.org/AAAI21Papers/EAAI-6.HeinA.pdf - Evaluating Gin Rummy Hands Using Opponent Modeling and Myopic Meld Distance
Phoebe Goldman, Corey Knutson, Ryan Mahtab, Jack Maloney, Joseph Mueller, Richard Freedman
https://www.aaai.org/AAAI21Papers/EAAI-28.GoldmanP.pdf - Opponent Hand Estimation in Gin Rummy Using Deep Neural Networks and Heuristic Strategies
Bhaskar Mishra, Ashish Aggarwal
https://www.aaai.org/AAAI21Papers/EAAI-96.MishraB.pdf - Modeling Expert and Folk Knowledge in a Heuristic-Based Reflex Agent for Gin Rummy
Sarah Larkin, William Collicott, Jason Hiebel
https://www.aaai.org/AAAI21Papers/EAAI-67.LarkinS.pdf
[3:00 - 3:45] Model AI Assignments
- “Unplugged” Semantic Networks and Knowledge Representations
Duri Long, Jonathan Moon, Brian Magerko
http://modelai.gettysburg.edu/2021/semantic/ - Introducing AI Worksheet Activity
Duri Long, Jonathan Moon, Brian Magerko
http://modelai.gettysburg.edu/2021/intro/
[3:45 - 4:30] Model AI Assignments
- Rushhour: designing and comparing heuristics for a children's puzzle
John Maraist
http://modelai.gettysburg.edu/2021/rushhour/ - Using Markov Chain Text Generators to Facilitate Found Poetry Creation
Alex Leto, Toni Lefton, Tom Williams
http://modelai.gettysburg.edu/2021/poetry/
[4:30 - 5:15] Model AI Assignments
- ScalarFlow: Implementing Reverse Mode Automatic Differentiation
Nathan Sprague
http://modelai.gettysburg.edu/2021/scalarflow/ - Text Denoising Autoencoder for News Headlines
Lisa Zhang, Pouria Fewzee
http://modelai.gettysburg.edu/2021/headlines/
[5:15 - 6:00] Community Meeting
All attendees are invited to join us for an informal community meeting at the end of EAAI-21, where we'll socialize and share ideas for next year's symposium.