Natural Language Processing Fundamentals

• Syntax, Semantics, and Pragmatics
• Morphological and Lexical Analysis
• Discourse and Dialogue Modeling
• Computational Linguistics
• Multilingual and Cross-lingual NLP
• Low-resource Language Processing

Machine Learning and Deep Learning for NLP

• Neural Language Models and Architectures
• Large Language Models (LLMs)
• Representation Learning for Text
• Transfer Learning and Fine-tuning Strategies
• Prompt Learning and In-Context Learning
• Reinforcement Learning for NLP

Natural Language Understanding and Generation

• Text Classification and Topic Modeling
• Sentiment Analysis and Opinion Mining
• Named Entity Recognition and Relation Extraction
• Question Answering Systems
• Text Summarization
• Natural Language Generation and Text-to-Text Systems

Emerging Topics and Interdisciplinary Research

• NLP and Cognitive Science
• NLP for Scientific Discovery
• Multilingual and Multicultural AI
• Human-centered and Interactive NLP
• NLP for Robotics and Intelligent Agents

Speech and Multimodal Language Processing

• Speech Recognition and Spoken Language Understanding
• Speech-to-Text and Text-to-Speech Systems
• Multimodal NLP (Text, Speech, Vision)
• Conversational AI and Dialogue Systems
• Human–Computer Interaction with Language

Information Retrieval and Knowledge Processing

• Information Extraction and Retrieval
• Knowledge Graph Construction and Reasoning
• Semantic Search and Recommendation Systems
• Text Mining and Document Analysis
• Ontologies and Knowledge Representation

AI Ethics, Fairness, and Trustworthy NLP

• Bias, Fairness, and Transparency in NLP Models
• Explainable and Interpretable NLP
• Privacy-preserving NLP
• Responsible and Ethical AI for Language Technologies
• Robustness and Safety of Language Models

NLP Applications

• NLP for Healthcare and Biomedical Text
• NLP for Social Media and Opinion Analysis
• Financial, Legal, and Educational NLP
• NLP for Smart Cities and E-Government
• Industrial and Enterprise NLP Applications