David C. Anastasiu

Assistant Professor, Computer Science and Engineering

Personal profile

About

Dr. David C. Anastasiu is an Assistant Professor in the Computer Science and Engineering department at Santa Clara University. He was previoiusly an Assistant Professor in the Department of Computer Engineering at San Jose State University. His research interests fall broadly at the intersection of data mining, high performance computing, information retrieval, and cloud and distributed computing. Much of his work has been focused on scalable and efficient methods for analyzing sparse data. He has developed serial and parallel methods for identifying near neighbors, methods for characterizing how user behavior changes over time, and methods for personalized and collaborative presentation of Web search results. His future research directions of interest include:
  • Knowledge discovery from Sparse Big Data.
  • Scalable quantitative methods for Data Mining.
  • Analysis of dynamic heterogeneous information networks.
  • Outlier detection in multivariate time-series.

Contact Information

Dr. David C. Anastasiu
Assistant Professor, Computer Science and Engineering Department
408-551-1941

Related documents

Education/Academic qualification

Computer Science, Ph.D., University of Minnesota - Twin Cities

… → 2016

Computer Science, M.S., Texas State University - San Marcos

… → 2011

Computer Science, Post Graduate Certificate, Texas State University - San Marcos

… → 2009

Theology, B.A., Moody Bible Institute

… → 2001

External positions

Assistant Professor, San Jose State University

Aug 1 2016Jan 1 2019

Research Assistant, University of Minnesota - Twin Cities

Sep 1 2011Aug 1 2016

Research Interests

  • Data mining
  • High performance computing
  • Information retrieval
  • Cloud and distributed computing
  • Scalable and efficient methods for analyzing sparse data
  • Knowledge discovery from Sparse Big Data
  • Scalable quantitative methods for Data Mining
  • Analysis of dynamic heterogeneous information networks
  • Outlier detection in multivariate time-series

Disciplines

  • Computer Engineering