2026 João Gama: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	73	1558	1511	2	1	475	28152

João Gama publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where João Gama sits on this spectrum.

32 publications 991+

This scientist: 475 publications — 92nd percentile

92% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

João Gama D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where João Gama sits on this spectrum.

30 D-Index 131+

This scientist: 73 D-Index — 89th percentile

89% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

2026 - Research.com Computer Science in Portugal Leader Award
2025 - Research.com Computer Science in Portugal Leader Award
2023 - Research.com Computer Science in Portugal Leader Award
2022 - Research.com Computer Science in Portugal Leader Award
2021 - IEEE Fellow for contributions to mining data streams
2020 - Fellow of the European Association for Artificial Intelligence (EurAI)
2020 - Fellow of the European Association for Artificial Intelligence (EurAI)

Overview

João Gama is affiliated with the University of Porto in Portugal and has contributed extensively to the fields of Computer Science and Engineering. Their research spans several subfields, with a primary focus on Artificial Intelligence, followed by Control and Systems Engineering, Management Science and Operations Research, Signal Processing, and Transportation.

Their main research topics include Data Stream Mining Techniques, Anomaly Detection Techniques and Applications, Imbalanced Data Classification Techniques, Time Series Analysis and Forecasting, Machine Learning and Data Classification, Human Mobility and Location-Based Analysis, and Network Security and Intrusion Detection.

João Gama has been frequently published in several venues, including:

arXiv (Cornell University)
SSRN Electronic Journal
Data Mining and Knowledge Discovery
Annals of Telecommunications
Zenodo (CERN European Organization for Nuclear Research)

Recent papers authored or co-authored by João Gama include:

"Artificial intelligence, cyber-threats and Industry 4.0: challenges and opportunities" (2021), published in Artificial Intelligence Review
"Methods and tools for causal discovery and causal inference" (2022), published in Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
"Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods" (2020), published in Mathematics
"Host-based IDS: A review and open issues of an anomaly detection system in IoT" (2022), published in Future Generation Computer Systems
"Data stream analysis: Foundations, major tasks and tools" (2021), published in Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery

The scientist frequently collaborates with other researchers such as Bruno Veloso, Rita P. Ribeiro, Albert Bifet, Thiago Andrade, and Ana Rita Nogueira.

In addition to journal articles, João Gama has contributed to books published by Springer Science+Business Media, including titles such as:

ECML PKDD 2020 Workshops (2020)
Advances in Knowledge Discovery and Data Mining (2022)
Advances in Intelligent Data Analysis XIX (2021)
Multiple editions of Advances in Knowledge Discovery and Data Mining (2022)

Best Publications

A survey on concept drift adaptation

João Gama;Indrė Žliobaitė;Albert Bifet;Mykola Pechenizkiy

3373
Citations
Learning with Drift Detection

João Gama;Pedro Medas;Gladys Castillo;Gladys Castillo;Pedro Pereira Rodrigues

1809
Citations
Learning under Concept Drift: A Review

Jie Lu;Anjin Liu;Fan Dong;Feng Gu

1434
Citations
Ensemble learning for data stream analysis

Bartosz Krawczyk;Leandro L. Minku;Joo Gama;Jerzy Stefanowski

1205
Citations
Knowledge Discovery from Data Streams.

João Gama;Pedro Pereira Rodrigues;Eduardo Jaques Spinosa;André Carlos Ponce de Leon Ferreira de Carvalho

1081
Citations
Predicting Taxi–Passenger Demand Using Streaming Data

Luis Moreira-Matias;Joao Gama;Michel Ferreira;Joao Mendes-Moreira

812
Citations
Data stream clustering: A survey

Jonathan A. Silva;Elaine R. Faria;Rodrigo C. Barros;Eduardo R. Hruschka

653
Citations
On evaluating stream learning algorithms

João Gama;Raquel Sebastião;Pedro Pereira Rodrigues

597
Citations
Event labeling combining ensemble detectors and background knowledge

Hadi Fanaee-T;Joao Gama

486
Citations
An Overview of Concept Drift Applications

Indrė Žliobaitė;Indrė Žliobaitė;Indrė Žliobaitė;Mykola Pechenizkiy;João Gama

437
Citations
Knowledge discovery from data streams

João Gama;Auroop Ganguly;Olufemi Omitaomu;Raju Vatsavai

434
Citations
Issues in evaluation of stream learning algorithms

João Gama;Raquel Sebastião;Pedro Pereira Rodrigues

430
Citations
Cascade Generalization

João Gama;Pavel Brazdil

426
Citations
Accurate decision trees for mining high-speed data streams

João Gama;Ricardo Rocha;Pedro Medas

425
Citations
Inteligência artificial: uma abordagem de aprendizado de máquina

Katti Faceli;Ana Carolina Lorena;João Gama;André Carlos Ponce de Leon Ferreira de Carvalho

402
Citations
Functional Trees

João Gama

383
Citations
Social network analysis: An overview

Shazia Tabassum;Fabiola S. F. Pereira;Sofia Fernandes;João Gama

375
Citations
Learning model trees from evolving data streams

Elena Ikonomovska;João Gama;Sašo Džeroski

366
Citations
A review on the combination of binary classifiers in multiclass problems

Ana Carolina Lorena;André C. Carvalho;João M. Gama

342
Citations
Learning from Data Streams: Processing Techniques in Sensor Networks

Joao Gama;Mohamed Medhat Gaber

334
Citations
Knowledge discovery in databases : pkdd 2005

Alípio Mário Jorge;Luís Torgo;Pavel Brazdil;Rui Camacho

321
Citations

Frequent Co-Authors

André C. P. L. F. de Carvalho Universidade de São Paulo

Mohamed Medhat Gaber Birmingham City University

Albert Bifet University of Waikato

Annalisa Appice University of Bari Aldo Moro

Shonali Krishnaswamy Monash University

Vladimiro Miranda University of Porto

Ricardo J. Bessa University of Porto

Nitesh V. Chawla University of Notre Dame

Donato Malerba University of Bari Aldo Moro

Mykola Pechenizkiy Eindhoven University of Technology

External Links

Personal website of João Gama Google Scholar page

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

Related Online Degrees & Career Pathways

Exploring online degrees is a smart way to advance your Computer Science career, especially with flexible options now widely available. Many students consider pursuing the data science learning path for its strong job market and practical applications in tech-driven industries.

For those interested in hardware and innovation, a online bachelor’s in electrical engineering opens doors to careers in electronics, robotics, and emerging fields like IoT. These programs offer rigorous coursework with flexibility for working students.

Credentials matter—consider certifications for jobs in networking, database management, or cloud solutions. These short-term programs can quickly boost your resume and earning potential without long-term academic commitments.

If you’re aiming for an advanced role fast, explore the fastest online master’s degree options in technology. Accelerated pathways help you gain specialized knowledge and credentials in less time, supporting your career growth and adaptability.