2026 João Paulo Papa: 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	58	3602	3501	10	10	385	14878

João Paulo Papa 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 Paulo Papa sits on this spectrum.

32 publications 991+

This scientist: 385 publications — 86th percentile

86% of scientists in this discipline score the same or lower.

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

João Paulo Papa 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 Paulo Papa sits on this spectrum.

30 D-Index 131+

This scientist: 58 D-Index — 75th percentile

75% 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 Brazil Leader Award
2025 - Research.com Computer Science in Brazil Leader Award

Overview

João Paulo Papa is affiliated with Sao Paulo State University in Brazil and has contributed extensively to research within computer science, engineering, and medicine. Their publication record includes a significant focus on artificial intelligence and computer vision alongside other fields such as electrical and electronic engineering, signal processing, and neurology.

Major research topics covered by João Paulo Papa include advanced neural network applications, electricity theft detection techniques, machine learning and data classification, metaheuristic optimization algorithms research, topic modeling, natural language processing techniques, and esophageal cancer research and treatment.

Their recent publications demonstrate a range of interests and contributions across multiple domains. Notable papers include:

Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks, 2022, ACM Computing Surveys
Deep learning techniques for recommender systems based on collaborative filtering, 2020, Expert Systems
A survey on text generation using generative adversarial networks, 2021, Pattern Recognition
A fuzzy distance-based ensemble of deep models for cervical cancer detection, 2022, Computer Methods and Programs in Biomedicine
Gait Recognition Based on Deep Learning: A Survey, 2022, ACM Computing Surveys

João Paulo Papa has collaborated frequently with a number of researchers, including Leandro A. Passos, Mateus Roder, Gustavo Henrique de Rosa, Douglas Rodrigues, and Luis A. de Souza, with collaboration counts ranging from 15 to 42 joint works.

Their work has been published repeatedly in several scholarly venues, with the highest number of publications appearing in:

arXiv (Cornell University)
SSRN Electronic Journal
Applied Soft Computing
Computers in Biology and Medicine
Neurocomputing

In addition to articles, João Paulo Papa has contributed to book publications, notably a book published by Springer Science+Business Media titled "Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications" in 2021.

Best Publications

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

M. Jorge Cardoso;Tal Arbel;Gustavo Carneiro;Tanveer Syeda-Mahmood

829
Citations
BBA: A Binary Bat Algorithm for Feature Selection

R. Y. M. Nakamura;L. A. M. Pereira;K. A. Costa;D. Rodrigues

508
Citations
Supervised pattern classification based on optimum-path forest

J. P. Papa;A. X. Falcão;C. T. N. Suzuki

493
Citations
Internet of Things: A survey on machine learning-based intrusion detection approaches

Kelton A.P. da Costa;João P. Papa;Celso O. Lisboa;Roberto Munoz

488
Citations
Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks

Unknown

389
Citations
Supervised pattern classification based on optimum‐path forest

Unknown

382
Citations
FEMa: a finite element machine for fast learning

Danilo R. Pereira;Marco Antonio Piteri;André N. de Souza;João Paulo Papa

339
Citations
Efficient supervised optimum-path forest classification for large datasets

JoãO P. Papa;Alexandre X. FalcãO;Victor Hugo C. De Albuquerque;JoãO Manuel R. S. Tavares

311
Citations
A wrapper approach for feature selection based on Bat Algorithm and Optimum-Path Forest

Douglas Rodrigues;Luís A. M. Pereira;Rodrigo Y. M. Nakamura;Kelton A. P. Costa

288
Citations
Computational methods for the image segmentation of pigmented skin lesions

Roberta B. Oliveira;Mercedes E. Filho;Zhen Ma;João P. Papa

276
Citations
Deep Learning-Aided Parkinson's Disease Diagnosis from Handwritten Dynamics

Clayton R. Pereira;Silke A. T. Weber;Christian Hook;Gustavo H. Rosa

268
Citations
A genetic programming framework for content-based image retrieval

Ricardo da S. Torres;Alexandre X. Falcão;Marcos A. Gonçalves;João P. Papa

247
Citations
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support : 4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings

Danail Stoyanov;Zeike Taylor;Gustavo Carneiro;Tanveer Syeda-Mahmood

235
Citations
Computational methods for pigmented skin lesion classification in images: review and future trends

Roberta B. Oliveira;João P. Papa;Aledir S. Pereira;João Manuel Tavares

215
Citations
BCS: A Binary Cuckoo Search algorithm for feature selection

D. Rodrigues;L. A. M. Pereira;T. N. S. Almeida;J. P. Papa

213
Citations
Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification

Clayton R. Pereira;Danilo R. Pereira;Gustavo H. Rosa;Victor Hugo C. de Albuquerque

199
Citations
ECG arrhythmia classification based on optimum-path forest

Eduardo José Da S. Luz;Thiago M. Nunes;Victor Hugo C. De Albuquerque;JoãO P. Papa

199
Citations
Deep Learning and Data Labeling for Medical Applications

Gustavo Carneiro;Diana Mateus;Loïc Peter;Andrew Bradley

194
Citations
An Overview on Concept Drift Learning

Adriana Sayuri Iwashita;João Paulo Papa

188
Citations
Deep learning techniques for recommender systems based on collaborative filtering

Guilherme Brandão Martins;João Paulo Papa;Hojjat Adeli

173
Citations
A New Approach for Nontechnical Losses Detection Based on Optimum-Path Forest

C C O Ramos;A N de Sousa;J P Papa;Alexandre Xavier Falcão

159
Citations
A novel algorithm for feature selection using Harmony Search and its application for non-technical losses detection

Caio C. O. Ramos;André N. Souza;Giovani Chiachia;Alexandre X. Falcão

155
Citations
A new computer vision-based approach to aid the diagnosis of Parkinson's disease

Clayton R. Pereira;Danilo R. Pereira;Francisco A. Silva;João P. Masieiro

146
Citations
EEG-based person identification through Binary Flower Pollination Algorithm

Douglas Rodrigues;Gabriel F.A. Silva;João P. Papa;Aparecido N. Marana

142
Citations

Frequent Co-Authors

Alexandre X. Falcão State University of Campinas

Victor Hugo C. de Albuquerque Universidade Federal do Ceará

João Manuel R. S. Tavares University of Porto

Xin-She Yang Middlesex University

Gustavo Carneiro University of Surrey

Andrew P. Bradley Queensland University of Technology

Jacinto C. Nascimento Instituto Superior Técnico

Ricardo da Silva Torres Wageningen University & Research

Walter J. Scheirer University of Notre Dame

Mohammed Azmi Al-Betar Ajman University of Science and Technology

External Links

Personal website of João Paulo Papa Google Scholar page

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