World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
67
Citations
14899
World Ranking
2230
National Ranking
1112

Overview

Elke A. Rundensteiner is affiliated with Worcester Polytechnic Institute in the United States. Their research spans multiple domains within computer science and psychology, with a strong focus on artificial intelligence and mental health applications.

The main fields of study in their work include:

  • Computer Science
  • Psychology

Within these areas, their research delves into specialized subfields such as:

  • Artificial Intelligence
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Applied Psychology
  • Experimental and Cognitive Psychology

The primary research topics covered include:

  • Digital Mental Health Interventions
  • Mental Health via Writing
  • Mental Health Research Topics
  • Anomaly Detection Techniques and Applications
  • Time Series Analysis and Forecasting
  • Machine Learning and Data Classification
  • Data Management and Algorithms

Frequent co-authors in their body of work are:

  • Walter Gerych
  • Emmanuel Agu
  • Luke Buquicchio
  • ML Tlachac
  • Kavin Chandrasekaran

The scientist has published extensively, with recurring appearances in key venues including:

  • arXiv (Cornell University)
  • Proceedings of the VLDB Endowment
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)
  • 2021 IEEE International Conference on Big Data (Big Data)

Some of their recent notable papers are:

  • Applying Machine Learning Approaches to Suicide Prediction Using Healthcare Data: Overview and Future Directions, 2021, Frontiers in Psychiatry
  • Moodable: On feasibility of instantaneous depression assessment using machine learning on voice samples with retrospectively harvested smartphone and social media data, 2020, Smart Health
  • Screening For Depression With Retrospectively Harvested Private Versus Public Text, 2020, IEEE Journal of Biomedical and Health Informatics
  • Rank aggregation algorithms for fair consensus, 2020, Proceedings of the VLDB Endowment
  • Ensembles of BERT for Depression Classification, 2022, 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

Best Publications

  • Hierarchical parallel coordinates for exploration of large datasets

    Ying-Huey Fua;Matthew O. Ward;Elke A. Rundensteiner

  • Clutter Reduction in Multi-Dimensional Data Visualization Using Dimension Reordering

    W. Peng;M.O. Ward;E.A. Rundensteiner

  • Multiview: A Methodology for Supporting Multiple Views in Object-Oriented Databases

    Elke A. Rundensteiner

  • Hierarchical encoded path views for path query processing: an optimal model and its performance evaluation

    N. Jing;Y.-W. Huang;E.A. Rundensteiner

  • Spatial Joins Using R-trees: Breadth-First Traversal with Global Optimizations

    Yun-Wu Huang;Ning Jing;Elke A. Rundensteiner

  • Interactive hierarchical dimension ordering, spacing and filtering for exploration of high dimensional datasets

    Jing Wang;Wei Peng;M.O. Ward;E.A. Rundensteiner

  • System and method for synchronizing and/or updating an existing relational database with supplemental XML data

    Wang-Chien Lee;Gail Anne Mitchell;Elke Angelika Rundensteiner;Xin Zhang

  • Maintaining data warehouses over changing information sources

    Elke A. Rundensteiner;Andreas Koeller;Xin Zhang

  • Runtime Semantic Query Optimization for Event Stream Processing

    Luping Ding;Songting Chen;E.A. Rundensteiner;J. Tatemura

  • InterRing: an interactive tool for visually navigating and manipulating hierarchical structures

    Jing Yang;M.O. Ward;E.A. Rundensteiner

  • Dynamic plan migration for continuous queries over data streams

    Yali Zhu;Elke A. Rundensteiner;George T. Heineman

  • Visual hierarchical dimension reduction for exploration of high dimensional datasets

    J. Yang;M. O. Ward;E. A. Rundensteiner;S. Huang

  • Automatic emotion detection in text streams by analyzing Twitter data

    Maryam Hasan;Elke A. Rundensteiner;Emmanuel Agu

  • Method and system of document transformation between a source extensible markup language (XML) schema and a target XML schema

    Hong Su;Harumi Anne Kuno;Elke Angelika Rundensteiner

  • Toward inquiry-based education through interacting software agents

    D.E. Atkins;W.P. Birmingham;E.H. Durfee;E.J. Glover

  • Automating the transformation of XML documents

    Hong Su;Harumi Kuno;Elke A. Rundensteiner

  • Method and system of valuing transformation between extensible markup language (XML) documents

    Hong Su;Harumi Anne Kuno;Elke Angelika Rundensteiner;Umeshwar Dayal

  • Mapping nominal values to numbers for effective visualization

    Geraldine E. Rosario;Elke A. Rundensteiner;David C. Brown;Matthew O. Ward

  • Neighbor-based pattern detection for windows over streaming data

    Di Yang;Elke A. Rundensteiner;Matthew O. Ward

  • Scalable distance-based outlier detection over high-volume data streams

    Lei Cao;Di Yang;Qingyang Wang;Yanwei Yu

  • A transparent schema-evolution system based on object-oriented view technology

    Young-Gook Ra;E.A. Rundensteiner

Frequent Co-Authors

Matthew O. Ward
Matthew O. Ward University of Southern Mississippi
Xiangnan Kong
Xiangnan Kong Worcester Polytechnic Institute
Elisa Bertino
Elisa Bertino Purdue University West Lafayette
Kang G. Shin
Kang G. Shin University of Michigan–Ann Arbor
Yanchun Zhang
Yanchun Zhang Victoria University
Karl Aberer
Karl Aberer École Polytechnique Fédérale de Lausanne
Wang-Chien Lee
Wang-Chien Lee Pennsylvania State University
David Maier
David Maier Portland State University
Edmund H. Durfee
Edmund H. Durfee University of Michigan–Ann Arbor

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