From Tuesday 25 February to Tuesday 4 March 2025, Philadelphia will play host to the 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025). The event will feature invited talks, tutorials, workshops, and an extensive technical programme. There are also a whole host of other sessions, including a doctoral consortium, diversity and inclusion activities, posters, demos, and more. We (AIhub) will be running a science communication training session on Wednesday 26 February.
Invited talks
There are eight invited talks this year. There will also be a presidential address from current AAAI president Francesca Rossi.
Francesca Rossi – Presidential Address: AI Reasoning and System 2 Thinking
Susan Athey – Predicting Career Transitions and Estimating Wage Disparities Using Foundation Models
Andrew Ng – AI, Agents and Applications
Yuhuai (Tony) Wu – Reasoning at Scale
Christoph Schuhmann – Democratizing AI through Community Organizing
Alondra Nelson – Title to be confirmed
Subbarao Kambhampati – T(w)eaching AI in the Age of LLMs
Stuart J. Russell – Can AI Benefit Humanity?
David Chalmers – Propositional Interpretability in Humans and AI Systems
Science communication for AI researchers – an introduction
We (AIhub) will be running a short course on science communication on Wednesday 26 February. Find out more here.
Tutorial and lab forum
The tutorial and lab forum will be held at the beginning of the conference, on Tuesday 25 and Wednesday 26 February.
- TH01: Bridging Inverse Reinforcement Learning and Large Language Model Alignment: Toward Safe and Human-Centric AI SystemsTH02: Building trustworthy ML: The role of label quality and availabilityTH03: Fairness in AI/ML via Social ChoiceTH04: Foundation Models meet Embodied AgentsTH05: Multi-modal Foundation Model for Scientific Discovery: With Applications in Chemistry, Material, and BiologyTH06: Pre-trained Language Model with Limited ResourcesLH01: DAMAGeR: Deploying Automatic and Manual Approaches to GenAI Red-teamingTQ01: Advancing Offline Reinforcement Learning: Essential Theories and Techniques for Algorithm DevelopersTQ02: Unified Semi-Supervised Learning with Foundation ModelsLQ01: SOFAI Lab: A Hands-On Guide to Building Neurosymbolic Systems with Metacognitive ControlTQ03: Reinforcement Learning with Temporal Logic objectives and constraintsTH07: Concept-based Interpretable Deep LearningTH08: Evaluating Large Language Models: Challenges and MethodsTH09: Foundation Models for Time Series Analysis: A TutorialTH10: Neurosymbolic AI for EGI: Explainable, Grounded, and Instructable GenerationsTQ04: Deep Representation Learning for Tabular DataTQ05: LLMs and Copyright Risks: Benchmarks and Mitigation Approaches TQ06: Physics-Inspired Geometric Pretraining for Molecule RepresentationTQ07: From Tensor Factorizations to Circuits (and Back)TQ08: KV Cache Compression for Efficient Long Context LLM Inference: Challenges, Trade-Offs, and OpportunitiesTQ09: Supervised Algorithmic Fairness in Distribution ShiftsLQ03: Developing explainable multimodal AI models with hands-on lab on the life-cycle of rare event prediction in manufacturingTH11: (Really) Using Counterfactuals to Explain AI Systems: Fundamentals, Methods, & User Studies for XAI TH12: Advancing Brain-Computer Interfaces with Generative AI for Text, Vision, and Beyond TH13: AI for Science in the Era of Large Language Models TH14: Causal Representation Learning TH15: Graph Neural Networks: Architectures, Fundamental Properties and Applications TH16: Machine Learning for Protein Design TH17: The Lifecycle of Knowledge in Large Language Models: Memorization, Editing, and BeyondTH18: Thinking with Functors — Category Theory for A(G)I TH19: User-Driven Capability Assessment of Taskable AI SystemsTQ10: Artificial Intelligence Safety: From Reinforcement Learning to Foundation ModelsTQ11: Hallucinations in Large Multimodal ModelsTQ12: Graph Machine Learning under Distribution Shifts: Adaptation, Generalization and Extension to LLM LQ02: Continual Learning on Graphs: Challenges, Solutions, and OpportunitiesTH20: AI Data Transparency: The Past, the Present, and Beyond TH21: Data-driven Decision-making in Public Health and its Real-world Applications TH22: Decision Intelligence for Two-sided Marketplaces TH23: Inferential Machine Learning: Towards Human-collaborative Vision and Language Models TH24: Machine Learning for Solvers TH25: Model Reuse: Unlocking the Power of Pre-Trained Model ResourcesTH26: Symbolic Regression: Towards Interpretability and Automated Scientific Discovery TH27: Tutorial: Multimodal Artificial Intelligence in HealthcareTQ13: Curriculum Learning in the Era of Large Language ModelsTQ14: Hypergraph Neural Networks: An In-Depth and Step-by-Step GuideTQ15: The Quest for A Science of Language ModelsLQ04: Financial Inclusion through AI-Powered Document Understanding TQ16: When Deep Learning Meets Polyhedral Theory: A Tutorial
Find out more about the tutorials and labs here.
Bridge programme
The bridge programme is designed to bring together two or more communities from different AI disciplines to foster collaborations. There are eleven different sessions this year, and these will be held on Tuesday 25 and Wednesday 26 February.
- B1: AI for Medicine and HealthcareB2: Bridge between AI and Scientific Knowledge OrganizationB3: Bridging Cognitive Science and AI to Bridge Neuro and Symbolic AIB4: Bridging Planning and Reasoning in Natural Language with Foundational Models (PLAN-FM)B5: Collaborative AI and Modeling of HumansB6: Combining AI and ORMS for Better Trustworthy Decision MakingB7: Constraint Programming and Machine LearningB8: Continual CausalityB9: Explainable AI, Energy and Critical Infrastructure SystemsB10: Knowledge-guided Machine Learning: Bridging Scientific Knowledge and AIB11: Learning for Integrated Task and Motion Planning
Find out more about the bridge programme here.
Workshops
There are 49 workshops to choose from this year. These will take place at the end of the main conference, on Monday 3 and Tuesday 4 March.
- W1: Translational Institute for Knowledge AxiomatizationW2: Advancing Artificial Intelligence through Theory of Mind (ToM4AI): Bridging Human Cognition and Artificial IntelligenceW3: AI for Public MissionsW4: AI for Social Impact: Bridging Innovations in Finance, Social Media, and Crime PreventionW5: AI for Urban PlanningW6: AI Governance: Alignment, Morality, and LawW7: AI to Accelerate Science and Engineering (AI2ASE)W8: AI4EDU: AI for Education: Tools, Opportunities, and Risks in the Generative AI EraW9: Artificial Intelligence for Cyber Security (AICS)W10: Artificial Intelligence for MusicW11: Cooperative Multi-Agent Systems Decision-Making and Learning: Human-Multi-Agent Cognitive FusionW12: Deployable AI WorkshopW13: Economics of Modern ML: Markets, Incentives, and Generative AIW14: Preparing Good Data for Generative AI: Challenges and Approaches (Good-Data)W15: Innovation and Responsibility for AI-Supported EducationW16: MARW: Multi-Agent AI in the Real-World WorkshopW17: Planning in The Era of Large Language ModelsW18: Post-Singularity Symbiosis: Preparing for a World with SuperintelligenceW19: Preventing and Detecting LLM Generated MisinformationW20: Privacy-Preserving Artificial IntelligenceW21: Quantum Computing and Artificial Intelligence (QC+AI)W22: Web Agent Revolution: Enhancing Trust and Enterprise-Grade Adoption Through InnovationW23: Imageomics: Discovering Biological Knowledge from Images Using AIW24: Workshop on Datasets and Evaluators of AI SafetyW25: Workshop on Document Understanding and IntelligenceW26: Workshop on Multi-Agent Path FindingW27:Foundation Models for Biological Discoveries (FMs4Bio)W28: Advancing LLM-Based Multi-Agent CollaborationW29: AI Agent for Information Retrieval: Generating and RankingW30: AI4Research: Towards a Knowledge-grounded Scientific Research LifecycleW31: Artificial Intelligence for Time Series Analysis (AI4TS): Theory, Algorithms, and ApplicationsW32: Artificial Intelligence for Wireless Communications and Networking (AI4WCN)W33: Artificial Intelligence with Causal TechniquesW34: Bridging the Gap Between AI Planning and Reinforcement Learning (PRL)W35: CoLoRAI – Connecting Low-Rank Representations in AIW36: Computational Jobs MarketplaceW37: DEFACTIFY 4.0 – Workshop Series on Multimodal Fact-Checking and Hate Speech DetectionW38: FLUID: Federated Learning for Unbounded and Intelligent DecentralizationW39: Generalization in PlanningW40: Workshop and Challenge on Anomaly Detection in Scientific DomainsW41: Knowledge Graphs for Health Equity, Justice, and Social ServicesW42: Large Language Model and Generative AI for HealthW43: Machine Learning for Autonomous DrivingW44: MALTA: Multi-Agent Reinforcement Learning for Transportation AutonomyW45: Neural Reasoning and Mathematical Discovery — An Interdisciplinary Two-Way StreetW46: Open-Source AI for Mainstream UseW47: Scalable and Efficient Artificial Intelligence SystemsW48: Towards Knowledgeable Foundation ModelsW49: Workshop on Health Intelligence (W3PHIAI-25)
Find out more about the workshops here.
Links to other events and sessions
- Main technical trackDemonstration programmeDiversity and inclusion activitiesEAAI-25: The 15th Symposium on Educational Advances in Artificial IntelligenceProgramme for the Thirty-Seventh Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-25)Doctoral ConsortiumUndergraduate Consortium
