World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
31926
World Ranking
9922
National Ranking
4168

Research.com Recognitions

  • 2020 - IEEE Fellow For contributions to data mining and machine learning
  • 2017 - Fellow of the Indian National Academy of Engineering (INAE)
  • Member of the European Academy of Sciences and Arts
  • Member of the European Academy of Sciences and Arts
  • Member of the European Academy of Sciences and Arts

Overview

Krzysztof J. Cios is affiliated with Virginia Commonwealth University in the United States and works primarily across the fields of Computer Science, Engineering, and Neuroscience. Their research spans topics such as Advanced Memory and Neural Computing, Neural dynamics and brain function, Ferroelectric and Negative Capacitance Devices, Biometric Identification and Security, Face recognition and analysis, Neural Networks and Reservoir Computing, and Digital Media Forensic Detection.

Their recent published papers include the following:

  • FASS: Face Anti-Spoofing System Using Image Quality Features and Deep Learning, 2023, Electronics
  • UFace: An Unsupervised Deep Learning Face Verification System, 2022, Electronics
  • Combining multi-label classifiers based on projections of the output space using Evolutionary algorithms, 2020, Knowledge-Based Systems
  • CRBA: A Competitive Rate-Based Algorithm Based on Competitive Spiking Neural Networks, 2021, Frontiers in Computational Neuroscience
  • MT-SNN: Spiking Neural Network that Enables Single-Tasking of Multiple Tasks, 2022, arXiv (Cornell University)

Cited publication venues that frequently feature their work include:

  • Electronics
  • Knowledge-Based Systems
  • Frontiers in Computational Neuroscience
  • arXiv (Cornell University)
  • 2022 29th IEEE International Conference on Electronics, Circuits and Systems (ICECS)

Frequent co-authors include Sebastián Ventura, Paolo G. Cachi, Enoch Solomon, Jose M. Moyano, and Eva Gibaja. Collaborative efforts with each of these individuals have resulted in multiple publications within the same research fields.

The scientist has been recognized with several awards, including being named an IEEE Fellow in 2020 for contributions to data mining and machine learning. They were also elected Fellow of the Indian National Academy of Engineering in 2017 and hold membership in the European Academy of Sciences and Arts.

Best Publications

  • Advances in neural information processing systems 7

    Krzysztof Cios;Mark Shields

  • Data Mining: A Knowledge Discovery Approach

    Krzysztof J. Cios;Witold Pedrycz;Roman W. Swiniarski;Lukasz Andrzej Kurgan

  • Data Mining Methods for Knowledge Discovery

    K.J. Cios;W. Pedrycz;R.M. Swiniarsk

  • Uniqueness of medical data mining

    Krzysztof J. Cios;G. William Moore

  • CAIM discretization algorithm

    L.A. Kurgan;K.J. Cios

  • Impact of HbA1c Measurement on Hospital Readmission Rates: Analysis of 70,000 Clinical Database Patient Records

    Beata Strack;Jonathan P. DeShazo;Chris Gennings;Juan L. Olmo

  • Knowledge discovery approach to automated cardiac SPECT diagnosis

    Lukasz A. Kurgan;Krzysztof J. Cios;Ryszard Tadeusiewicz;Marek Ogiela

  • RNN-DBSCAN: A Density-Based Clustering Algorithm Using Reverse Nearest Neighbor Density Estimates

    Avory Bryant;Krzysztof Cios

  • Trends in Data Mining and Knowledge Discovery

    Krzysztof J. Cios;Krzysztof J. Cios;Lukasz A. Kurgan

  • Time series forecasting by combining RBF networks, certainty factors, and the Box-Jenkins model

    Donald K. Wedding;Krzysztof J. Cios

  • SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences

    Lukasz A. Kurgan;Krzysztof J. Cios;Ke Chen

  • Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome

    Clara Higuera;Katheleen J. Gardiner;Krzysztof J. Cios

  • Data Mining and Knowledge Discovery

    Krzysztof J. Cios;Witold Pedrycz;Roman W. Swiniarski

  • Review of ensembles of multi-label classifiers: Models, experimental study and prospects

    Jose M. Moyano;Eva L. Gibaja;Krzysztof J. Cios;Krzysztof J. Cios;Sebastián Ventura;Sebastián Ventura

  • A machine learning method for generation of a neural network architecture: a continuous ID3 algorithm

    K.J. Cios;N. Liu

  • From the guest editor medical data mining and knowledge discovery

    K.J. Cios

  • Improving sensitivity in shotgun proteomics using a peptide-centric database with reduced complexity: protease cleavage and SCX elution rules from data mining of MS/MS spectra.

    Chia-Yu Yen;Steve Russell;Alex M Mendoza;Karen Meyer-Arendt

  • A knowledge discovery approach to diagnosing myocardial perfusion

    K.J. Cios;A. Teresinska;S. Konieczna;J. Potocka

  • Continuous ID3 algorithm with fuzzy entropy measures

    K.J. Cios;L.M. Sztandera

  • Epileptic seizure detection.

    Ronald Schuyler;Andrew White;Kevin Staley;Krzysztof J Cios

  • Discretization Algorithm that Uses Class-Attribute Interdependence Maximization

    Krzysztof Cios

  • The handbook of brain theory and neural networks

    Krzysztof J. Cios;Mark E. Shields

  • Machine learning — Neural networks, genetic algorithms, and fuzzy systems: by Hojjat Adeli and Shin-Lin Hung, John Wiley & Sons, 1995. ISBN 0 471-01633-0, 212 pp., US$39.95

    Krzysztof Cios

Frequent Co-Authors

Lukasz Kurgan
Lukasz Kurgan Virginia Commonwealth University
Witold Pedrycz
Witold Pedrycz University of Alberta
Sebastián Ventura
Sebastián Ventura University of Córdoba
Katheleen Gardiner
Katheleen Gardiner University of Colorado Denver
Kevin J. Staley
Kevin J. Staley Harvard University
Katheryn A. Resing
Katheryn A. Resing University of Colorado Boulder
Natalie G. Ahn
Natalie G. Ahn University of Colorado Boulder
Mark W. Duncan
Mark W. Duncan University of Colorado Denver
Rob Knight
Rob Knight University of California, San Diego
Brian L. Allman
Brian L. Allman University of Western Ontario

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online study in Computer Science can open doors to diverse fields and flexible career options. Students today have access to nationally accredited online colleges that provide rigorous degree programs with the convenience of distance learning. This flexibility is ideal for balancing studies with work or personal commitments.

For those interested in specialized areas, there are programs like game design schools online that allow you to delve into game development, 3D design, and interactive storytelling—all key in today’s entertainment and tech industries. Cybersecurity is another area experiencing high demand; pursuing a cyber security masters online equips graduates for roles in IT security, risk analysis, and digital forensics.

Computer Science skills also transfer well to other industries, such as construction management. Earning a masters in construction management online can help professionals incorporate digital tools and data analysis into large-scale building projects. These related pathways show how online degrees can support and diversify your career in technology and beyond.

Best Scientists Citing Krzysztof J. Cios

Trending Scientists

Recently Published Articles