Stanford’s Symbolic Systems program combines computer science, linguistics, philosophy, and psychology to explore how systems—both natural and artificial—represent and process meaning. These project ideas support innovative, interdisciplinary inquiry into cognition, AI, and symbolic logic.
Ethical Frameworks for AI Decision-Making in Autonomous Vehicles
Neural Correlates of Language Processing: A Cognitive Study
Natural Language Processing Chatbot for Mental Health Support
Logic-Based Reasoning Engine for Legal Argument Generation
Cognitive Bias Modeling in Human-AI Interaction
Machine Learning to Predict User Behavior from Interaction Logs
Building a Multilingual Question Answering System Using Transformers
Comparative Analysis of Human and Machine Learning Strategies
Philosophical Analysis of Consciousness in Artificial Systems
Computational Modeling of Language Acquisition in Children
Speech Recognition System Trained on Low-Resource Languages
Cognitive Load Prediction in E-Learning Environments Using Eye Tracking
Semantic Network Construction from Open-Ended Survey Responses
Simulation of Ethical Dilemmas Using Reinforcement Learning Agents
Formal Logic Interpreter for Structured Natural Language Commands
Design of a Modular Symbolic AI Reasoning Framework
Augmented Reality Platform for Teaching Logic and Set Theory
Interdisciplinary Study of Morality in Human-Robot Interaction
Development of a Personalized Recommender System Using NLP
Analyzing the Evolution of Word Meaning Using Vector Semantics
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