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Behnaz Eslami

Ph.D. Student

Behnaz (Naz) Eslami is a Ph.D. student in Computer Science at Loyola University Chicago, where she works at the intersection of artificial intelligence, natural language processing, and healthcare informatics. Her research focuses on developing AI-driven methods for extracting, standardizing, and reasoning over complex clinical information from unstructured medical data, with the goal of supporting clinical decision-making and improving healthcare outcomes.

Her research interests include large language models (LLMs), generative AI, clinical natural language processing, machine learning, deep learning, biomedical informatics, and digital twins. Her work explores the application of these technologies to real-world healthcare challenges, including clinical concept extraction, assertion detection, medication management, and the interpretation of electronic health record data.

Eslami has contributed to interdisciplinary research spanning computer science, medicine, nursing, and health informatics. Her recent work includes a hybrid language framework that combines LLMs, biomedical ontologies, and NLP techniques to extract standardized clinical concepts from electronic health records. She has also investigated digital twins for medication management in intensive care settings and performance-based approaches to assertion detection in clinical narratives.

Her research has appeared in venues including the Journal of Healthcare Informatics Research, the Journal of the American Medical Informatics Association (JAMIA), and conference proceedings. She has also presented her work on clinical NLP and healthcare AI at the Applied AI Summit.

Before joining Loyola, Eslami worked in industry as a data scientist and web services specialist, with experience spanning software development, databases, data science, machine learning, and natural language processing. She also brings experience in teaching and applied data science, including workshops on cloud computing for data science and large language models.

Eslami is currently gaining additional industry research experience as a Data Scientist Intern with Regeneron, where her work includes large language models and RNA-sequencing analysis.

Major

Education

  • Ph.D. in Computer Science, Loyola University Chicago — In Progress
  • M.S. in Information Technology / E-Commerce, Islamic Azad University, Science and Research Branch
  • Additional graduate and undergraduate study in computer science, information technology, and related fields

Research Interests

Artificial Intelligence and Generative AI, Large Language Models (LLMs), Natural Language Processing (NLP), Clinical NLP and Medical Informatics, Machine Learning and Deep Learning, Healthcare AI, Biomedical Informatics, Digital Twins, Computational Biology