About Me - Dr. Fatema Nafa

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.

Teaching Excellence & Mentorship

Active mentorship and curriculum innovation across data science and AI courses, encouraging collaborative, project-based learning.

Applied AI for Social Impact

Deployed models in education and health contexts with a focus on fairness, interpretability, and measurable real-world outcomes.

Research Leadership

Directing graduate-led projects in NLP, LLMs, and semantic computing, with weekly research sprints and dissemination goals.

Teaching & Education

Education

Ph.D. in Computer Science – 2011–2018
Kent State University · Kent, OH
M.S. in Computer Science – 2003–2006
Sirte University · Sirte, Libya
B.S. in Computer Science and Math – 1999–2003
Sirte University · Sirte, Libya

Teaching

Associate Teaching Professor, Northeastern University
01/2024 – Present · Boston, MA
Assistant Professor, Salem State University
09/2019 – 12/2023 · Salem, MA
Teaching Assistant, Kent State University
01/2014 – 05/2017 · Kent, OH
Assistant Lecturer, University of Benghazi
01/2007 – 05/2010 · Benghazi, Libya

Research & Professional Interests

Development, fine-tuning, and evaluation of LLMs for domain tasks; prompt engineering, RAG, and reasoning strategies.

Multi-turn strategies, prompt-chaining, and optimization for reliability, safety, and interpretability across modalities.

Multimodal systems for education, health, and social equity; transformers, diffusion, and GNNs in practice.

XAI, fairness, privacy, and reproducibility from data collection to monitoring.

Knowledge graphs, ontologies, semantic search, and alignment with human needs and cognition.

Interactive platforms, AI-powered visualization, and graph analytics for real-time decision support.