Dr. Cyril S. Ku, a Professor of Computer Science at William Paterson University, received his Ph.D. in Computer Science from Northwestern University, with a specialization in deductive databases. With over a decade of industry experience at premier institutions such as Bellcore, AT&T, and IBM, Dr. Ku brings a rich professional background to academia. He founded the Data Science Research Lab (DSRL: https://cs-cit.wpunj.edu/cs/Research/DSRL/) at William Paterson University, where he spearheads cutting-edge research in data science and its various subfields, including big data analytics, natural language processing, data and text mining, machine learning, and software engineering. His contributions to these areas have been widely recognized, with publications in prestigious journals and books, such as IEEE Transactions on Knowledge and Data Engineering, the Wiley Encyclopedia of Computer Science and Engineering, and the Journal of Systemics, Cybernetics, and Informatics, among others. Dr. Ku's DSRL collaborates closely with the Healthcare Approaches to Justice Collaborative at Montclair State University and Hackensack Meridian Health School of Medicine. This partnership fosters innovation and promotes the dissemination of knowledge across the fields of data science and artificial intelligence. Supported by the NSF ACCESS program, the lab grants researchers access to over 15 high-performance computing facilities nationwide. An active mentor, Dr. Ku engages students in hands-on data science projects, applying advanced machine-learning techniques to tackle real-world challenges. His dedication to education and research continues to impact the academic and scientific communities profoundly.
Professional Interests
Besides teaching, Dr. Ku is a Principal Investigator, Co-principal Investigator, or Consultant for several research grants which involve databases, big data analytics, natural language processing, data/text mining, machine learning, as well as software engineering research. He loves to do interdisciplinary research in data science, applying the latest machine-learning techniques to solve real-world problems. More information about his professional interests can be found on the Data Science Research Lab website.
