William Claster

About

Dr. William Claster is an accomplished academic and data scientist with over 20 years of experience teaching multinational students. He currently serves as the Associate Director and Associate Professor of the Master’s in Information Systems (MSIS) program at Northeastern University’s Arlington, VA campus, where he teaches courses in Data Science Engineering, Advanced Data Science Architecture, and Generative AI. Dr. Claster earned his Ph.D. in Japan from Ritsumeikan Asia Pacific University, with a dissertation that focused on developing a data classification and dependency relationship methodology using data mining algorithms. He also holds an M.A. in Mathematics from Temple University and a B.S. in Physics from Bard College, where he minored in Mathematics. Throughout his career, Dr. Claster has made significant contributions to the fields of data science and machine learning. He is the author of Mathematics and Programming for Machine Learning with R: From the Ground Up (CRC Press, 2020), a comprehensive textbook. He has also authored a book in Japanese on the introduction to data science. His research interests span machine learning, big data analytics, fintech, natural language processing, and generative AI. Dr. Claster has published over 10 peer-reviewed journal articles and several book chapters, including the co-authored chapter “Applied Intelligence for Medical Diagnosing” in the Handbook of Research on Applied Intelligence for Health and Clinical Informatics, which explores the application of AI in medical imaging and diagnostics. Dr. Claster’s academic excellence has been recognized with numerous awards, including the Ritsumeikan Asia Pacific University Award for Outstanding Research in 2014. His professional experience extends beyond academia, having worked as a data scientist and consultant for fintech and IT companies such as Paidy Finance Services, Union Bank of Switzerland, and Goldman Sachs. As an educator, Dr. Claster is known for his innovative teaching methods and his development of a comprehensive data science curriculum. His courses have equipped students with the skills to excel in various industries, with alumni securing positions at leading tech companies like Google and Facebook. With a strong commitment to interdisciplinary collaboration and academic leadership, Dr. Claster continues to shape the future of data science education and research.

Selected Publications

• Using change point analysis to determine perception accuracy in social media opinions.Using change point analysis to determine perception accuracy in social media opinions. International Journal of Computer Techniques · Apr 25, 2015
• Text Classification For Medical Informatics: A Comparison Of Models For Data Mining Radiological Medical RecordsText Classification For Medical Informatics: A Comparison Of Models For Data Mining Radiological Medical Records, Asia Pacific World: the Journal of The International Association for Asia Pacific · Dec 1, 2011
• “Assessing how quickly people forget about the disaster by Twitter tweet counts” in the wake of the Great Earthquake and Tsunami, http://tohokugeo.jp/ar · Jun 17, 2011

View All Related News