The National Science Foundation has selected computer science professor Rutal Mahajan as a 2026 Undergraduate Research Mentor, bringing two visiting undergraduate students to Utica University for a 10-week research project focused on quantum-enhanced natural language processing for clinical text analysis. Through the Distributed Research Experiences for Undergraduates (DREU) program, students from Pace University and Washington and Lee University will collaborate with Mahajan on developing and evaluating quantum-enhanced methods for named entity recognition in medical records.

What Is Named Entity Recognition in Clinical Text?

Named entity recognition (NER) is an NLP (natural language processing) technique that automatically identifies and categorizes important information in text. In healthcare settings, this means extracting patient names, medications, diagnoses, medical conditions, and other critical data from clinical notes. Healthcare organizations generate millions of these notes annually, but much of that textual data remains underutilized because extracting structured information from unstructured text is computationally expensive and time-consuming.

Mahajan's research explores whether quantum computing, a fundamentally different computational approach that harnesses quantum mechanics, could improve how machines extract and understand critical health information from clinical notes. The visiting students will support the development and evaluation of quantum-enhanced methods for named entity recognition, as well as analyze scalability and noise issues that arise when quantum systems process real-world medical data. The project will leverage NSF-supported National AI Research Resource (NAIRR) computing resources throughout the research period.

Why Is This Research Significant for Healthcare AI?

Mahajan was selected on the basis of her work in artificial intelligence, high-performance computing, and quantum computing. Her research specifically focuses on privacy-aware natural language processing for clinical text and quantum computing applications in healthcare data analysis, meaning the methods are designed to protect patient confidentiality while still extracting valuable insights.

This work builds on graduate research that Mahajan co-advised at the National Institute of Technology in Surat, India. Initial results were presented and published at an IEEE conference in May 2025, and the undergraduate students will have the opportunity to present their findings at IEEE Quantum Week 2026 and other national conferences, bringing academic rigor and peer review to an emerging intersection of quantum computing and healthcare NLP.

"I am really excited about this opportunity not just for the visiting students, but also for what it means for Utica University. It brings external research talent to our campus, elevates our visibility in the computing research community, and creates a wonderful opportunity for our own students to collaborate, peer mentor, and get exposure to a broader research culture," said Mahajan.

Rutal Mahajan, Computer Science Professor at Utica University

How Does This Research Advance the Field?

• Quantum Enhancement: The research explores whether quantum computing can improve the speed and accuracy of extracting structured data from unstructured clinical text, potentially addressing computational bottlenecks in healthcare NLP applications.
• Privacy-Aware Methods: The project emphasizes privacy-aware approaches, ensuring that quantum-enhanced NLP methods protect patient confidentiality while extracting valuable health insights from clinical notes.
• Scalability Analysis: Students will analyze how quantum-enhanced methods perform at scale and identify noise issues that arise when quantum systems process real-world medical data, critical for practical healthcare deployment.
• Academic Validation: Results are already being published at peer-reviewed IEEE conferences, demonstrating that the work is moving beyond theoretical exploration into demonstrable progress with measurable outcomes.

Mahajan's research credentials underscore the seriousness of this initiative. She earned her Ph.D. in Computer Science and Engineering from the National Institute of Technology in Surat, India, and her research focuses on natural language processing and low-resource language emotion analysis in multilingual text. She is also a NVIDIA GenAI LLM (Large Language Model) Certified Associate and NVIDIA Certified Trainer, bringing industrial best practices into her academic work.

The DREU program itself is highly competitive, and Mahajan's selection reflects the quality and innovation of her research agenda. The two visiting students will join Utica University's own students in a collaborative environment designed to accelerate learning and research output. This peer mentoring structure mirrors how cutting-edge research actually happens in industry and academia, where junior researchers learn by working alongside experienced mentors on real problems.