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What’s coming up at #AAAI2023?

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03 February 2023



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The 37th AAAI Conference on Artificial Intelligence (AAAI2023) starts on Tuesday 7 February and runs until Tuesday 14 February. Find out about some of the main events that are taking place throughout the conference, this year to be held in Washington DC.

Presidential address

Francesca Rossi will deliver her presidential address on Thursday morning (9 February), following the official opening of the conference.

Invited speakers

AAAI have announced the following distinguished invited speakers at this year’s conference.

  • Sebastian Bubeck – Physics of AI — some first steps
  • Josh Tenenbaum – Learning to see the human way
  • Susan Murphy – We used reinforcement learning; but did it work?
  • Sami Haddadin – Robots with a sense of touch: self-replicating the machine and learning the self
  • Sheila McIlraith – (Formal) languages help AI agents learn and reason
  • Isabelle Augenstein – Beyond fact checking — modelling information change in scientific communication
  • Vincent Conitzer – New design decisions for modern AI agents
  • Anima Anandkuma – AI accelerating science: neural operators for learning on function spaces
  • Ayanna Howard – Socially interactive robots for supporting early interventions for children with special needs
  • Manuela Veloso – AI in robotics & AI in finance

Diversity and inclusion events

The diversity and inclusion events take place throughout the conference. Click on the links below to find out more details about each event.

Workshops

There are 32 different workshops and these will take place on 13 and 14 February. Click on the workshop titles below to find out more information.

Tutorial and lab forum

The tutorial and lab forum will take place on 7 and 8 February. The events comprise half-day or quarter-day sessions. The topics covered are listed below, and you can find out more here. Note: the AIhub tutorial on science communication for AI researchers will take place as part of the tutorial programme. You can find out more here.

  • Cooperative Multi-Agent Learning: A Review of Progress and Challenges
  • Introducing Neuronal Diversity into Deep Learning
  • Hands-On with the BLACK Satisfiability Checker
  • KGTK: User-Friendly Toolkit for Manipulation of Large Knowledge Graphs
  • Trustworthy and Responsible AI: Fairness, Interpretability, Transparency and Their Interactions
  • The Polynomial Nets in Deep Learning Architecture
  • Machine Learning for Causal Inference
  • AI Fairness through Robustness
  • Advances in Neuro Symbolic Reasoning
  • Specification-Guided Reinforcement Learning
  • Time Series Anomaly Detection Tool: Hands-on Lab
  • Pervasive AI
  • Bi-level Optimization in Machine Learning: Foundations and Applications
  • Risk-Sensitive Reinforcement Learning via Policy Gradient Search
  • On Explainable AI: From Theory to Motivation, Industrial Applications, XAI Coding & Engineering Practices
  • Everything You Need to Know about Transformers: Architectures, Optimization, Applications, and Interpretation
  • Large-Scale Deep Learning Optimization Techniques
  • Inductive Logic Programming: An Introduction and Recent Advances
  • Generalizable Commonsense Reasoning
  • Graph Neural Networks: Foundation, Frontiers and Applications
  • The Economics of Data and Machine Learning
  • Never-Ending Learning, Lifelong Learning and Continual Learning: Systems, Models, Current Challenges and Applications
  • Science communication for AI researchers
  • Subset Selection in Machine Learning: Hands-On Application with CORDS, DISTIL, SUBMODLIB, and TRUST
  • Automated AI For Decision Optimization with Reinforcement Learning
  • Colossal-AI: Scaling AI Models in Big Model Era
  • Building Approachable, Hands-On Embedded Machine Learning Curriculum Using Edge Impulse and Arduino
  • OpenMMLab: A Foundational Platform for Computer Vision Research and Production
  • Data Compression with Machine Learning
  • Towards Causal Foundations of Safe AI
  • Hyperbolic Neural Networks: Theory, Architectures and Applications
  • AI for Data-Centric Epidemic Forecasting
  • Recent Advances in Bayesian Optimization
  • Teaching Computing and Technology Ethics: Engaging Through Science Fiction
  • Knowledge-Driven Vision-Language Pretraining
  • Optimization with Constraint Learning
  • Automated Machine Learning & Tuning with FLAML
  • Innovative Uses of Synthetic Data

Bridge programme

The bridge programme brings together different communities to explore new opportunities and perspectives. The events will take place on 7 and 8 February, and are as follows:

Technical programme

The pdf of the technical programme can be found here.

IAAI-23

The 35th annual conference on innovative applications of artificial intelligence
(IAAI-23) will take place from 9-11 February. View the program here.

EAAI-23

The 13th symposium on educational advances in artificial intelligence (EAAI-23) with take place on 11-12 February. View the program here.



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Lucy Smith , Managing Editor for AIhub.
Lucy Smith , Managing Editor for AIhub.




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