Alex Rudniy, Ph.D.

Assistant Professor in Computer Science

Gildart Haase School of Computer Sciences and Engineering


Alex Rudniy received his Ph.D. in Computer Science from the New Jersey Institute of Technology, and his B.S. and M.S. degrees in Applied Mathematics from the National University of Radioelectronics, Ukraine. Before joining FDU, he held several positions related to data science and computer science. He teaches courses related to big data and database design while his research interests lie in the areas of deep learning, machine learning, data, web and text mining, and information retrieval as applied to big data analytics, bioinformatics, medical informatics, student success, online social network analysis and fraud detection.

Honors or Awards

  • NSF Collaborative Research Grant, 2015
  • IBM Impact Grant, 2015
  • Certificate for Successful Middle States Re-Accreditation, 2012

Service Activities

  • Member of FDU College Research Committee
  • NSF panel reviewer
  • Reviewer for American Medical Informatics Association
  • Reviewer for Big Data for Healthcare 2016

Selected Publications

  • D. Kelly-Riley, N. Elliot and A. Rudniy, “E-Portfolio and Digital Learning Research: Fairness and Assessment,” AAC&U 2016 Forum, Washington, D.C. January 2016.
  • A. Rudniy, “A Data Mining Approach to University Financial Aid Decision Making,” AIR Forum, Denver, CO, May 2015.
  • A. Rudniy, “BI for IR: Open-Source Business Intelligence for Institutional Research,” NJ AIR, Glassboro, NJ, May 2015.
  • A. Rudniy, P. Deess and R. Calluori. “Big Data Analytics for Institutional Effectiveness,” NJ AIR. Jersey City, NJ, May 2014.
  • A. Rudniy and P. Deess, “A New LinkedIn Tool for Alumni Research and Surveying,” AIR Forum, Orlando, FL, May 2014.
  • A. Rudniy, M. Song and J. Geller, “Improved SPED for Synonyms Identification in Bioinformatics,” Intnl. Conf. on Bioinf. and Comp. Biol., Las Vegas, NV, April 2014.
  • A. Rudniy, M. Song and J. Geller, “Mapping Biological Entities Using the Longest Approximately Common Prefix Method,” BMC Bioinformatics vol. 15, no. 187, pp. 1-9,  June 2014.

Short Abstract

Alex Rudniy received his Ph.D. in Computer Science from the New Jersey Institute of Technology, and his B.S. and M.S. degrees in Applied Mathematics from the National University of Radioelectronics, Ukraine. He teaches courses related to big data and database design while his research interests lie in the areas of machine learning, data, web and text mining, and information retrieval as applied to big data analytics, bioinformatics, medical informatics, student success, online social network analysis and fraud detection.

University College

Gildart Haase School of Computer Sciences and Engineering
Mail Stop T-BE2-01
1000 River Road
Teaneck, NJ 07666