Neurosymbolic Systems, Energy and Manufacturing, Bioinformatics
Core Faculty
Core faculty consider AI to be their primary research area.
Network Science
Natural Language Processing
Music Information Retrieval
Computer Vision
Data-centric AI
Intelligent Neuroimaging
Speech and Audio
Computational Linguistics
Case-based Reasoning
Robotics
Music Informatics
Natural Language Processing and General Intelligence
Natural Language Processing
Human-Robot Interaction
Cybersecurity, deep learning, mental health
Non-von Neumann architectures for AI
AI for Systems, Systems for AI
Neural-level Cognitive Models
Statistics, Machine Learning
Medical imaging
Affiliated Faculty
Affiliated Faculty study or use AI in their own primary discipline.
High Performance Computing
Cognitive Science
Network science, Connectomics, Data science
Theoretical Computer Science
Computational Social Science
Human vision
Quantum and Emerging Computing
Educational Technology
Information Diffusion, Complex Networks, Computational Social Science
Digital Heritage
Quantum and Classical Machine Learning
Computer-supported collaborative learning
Bio-inspired AI, Computational Neuroethology
Nanoscale simulations for material design
Hardware Design
Health, AI-HCI, AI Ethics
Social Behavior Regulation
Security and Privacy
Cancer Biology and Immunology
Neuroimaging Statistics
Computational Social Science
Data Governance and High Performance Computing
Probabilistic Programming, Semantics
Human-Computer Interaction, Health Informatics, Social Computing, Animal-Computer Interaction
Developmental Psychology
Computational Biology
Computational Decision Making
AI- and Data-centric Security and Privacy Protection
Computational Biology
AI and Art
Integrative data science
Reverse Engineering Biological Intelligence
Computational Cognitive Development
Bioinformatics, Microbiome Research
Reinforcement theory, Distributed learning, Learning theory