Dr. Fatema Nafa
Associate Teaching Professor She / Her
Natural language processing, large language models, and applied artificial intelligence.
Electrical and Computer Engineering &
Khoury College of Computer Sciences
Professional journey
I am an Associate Teaching Professor in Electrical and Computer Engineering and the Khoury College of Computer Sciences at Northeastern University. My research and teaching focus on Natural Language Processing (NLP), Large Language Models (LLMs), and Applied Artificial Intelligence. With over a decade of experience in computer science and academia, I am dedicated to empowering students with cutting-edge knowledge and real-world skills.
My work spans the development of intelligent systems for education, health, and social equity. I am deeply committed to fostering innovation, inclusivity, and excellence in research, while equipping future technologists with the tools to make ethical and impactful contributions.
Research & publications
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LearningTeaching & courses
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Research & professional interests
Natural Language Processing & Large Language Models
Text summarization, mathematical reasoning, and domain-specific language applications, including evaluation and adaptation of large language models.
Retrieval-Augmented Generation & AI for Education
Grounded, citation-supported tutoring through CourseLens / SocraticLens, combining hybrid retrieval, semantic search, course knowledge, and evaluation of learning-oriented responses.
Agentic AI & Generative AI Systems
AI workflows integrating tool use, retrieval, planning, prompt engineering, automated evaluation, and deployment.
Trustworthy AI & Hallucination Evaluation
Auditing factual consistency, grounding quality, hallucination risk, robustness, and model reliability, with a focus on explainability and responsible use.
Multimodal Learning & Biomedical AI
Machine learning pipelines that combine structured data with text, annotations, audio, and visual signals for predictive modeling and scientific applications.
Causal AI & Probabilistic Reasoning
Markov Knowledge Networks and probabilistic models for cognitive and decision modeling, causal reasoning, and interpretable AI.
AI Systems, MLOps & Distributed Computing
End-to-end model training, diagnostics, inference, and monitoring using cloud and HPC environments, vector databases, experiment tracking, and reproducible pipelines.
Semantic Computing, Human-Centered AI & Network Analysis
Knowledge representation, human-centered AI applications, and context-aware analysis of trends, summarization, and virality forecasting.
Teaching, education, and experience
My academic background and teaching appointments.
Read my CV