Senjuti Basu Roy

Senjuti Basu Roy is an Associate Professor in the Department of Computer Science at New Jersey Institute of Technology (NJIT). She specializes in data mining, machine learning, and healthcare informatics, with a focus on fairness in algorithms, optimization, and interdisciplinary applications in biotechnology and healthcare. Her work integrates AI systems with real-world challenges such as equitable resource allocation, predictive modeling for medical outcomes, and sustainable materials science.

Education:

• Ph.D. in Computer Science, University of Texas at Arlington (2011)
• M.S. in Computer Science, University of Texas at Arlington (2007)
• B.Tech. in Computer Science and Engineering, University of Calcutta (2004)

Research Interests: Dr. Basu Roy’s research spans algorithmic fairness, top-k query optimization, healthcare data analytics, and crowdsourcing systems. She develops frameworks for equitable data-driven decision-making and explores applications in biomedical engineering, environmental science, and structural safety. Her work bridges theoretical computer science with practical domains like drug discovery and infrastructure resilience.

Publications: Her recent work includes advancements in reinforcement learning, fairness-aware preference systems, and computational methods for biomedical problems. Notable contributions include frameworks for feature selection in incomplete datasets and optimization algorithms for maritime logistics.

Awards & Grants: She has secured NSF grants including “CAREER: Streamlining Task Deployment on Crowdsourcing Platforms” and “III: Small: Collaborative Research on Derived Attributes.” Her research emphasizes human-AI collaboration and equitable technology design.

Advising & Teaching: Teaches courses like Data Mining (CS 634) and Introduction to Data Science (CS 301). Advises on peer-learning methodologies and collaborative task optimization. Her lab focuses on real-world AI applications and interdisciplinary problem-solving.