2026 Francesco Mercaldo: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Rising Stars	42	575	575	9	9	302	5996
Computer Science	45	7281	7070	187	185	334	7148

Francesco Mercaldo 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 Francesco Mercaldo sits on this spectrum.

32 publications 991+

This scientist: 334 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Francesco Mercaldo 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 Francesco Mercaldo sits on this spectrum.

30 D-Index 131+

This scientist: 45 D-Index — 51st percentile

51% 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

2025 - Research.com Rising Stars Award

Overview

Francesco Mercaldo is affiliated with the University of Molise in Italy and works primarily in the fields of computer science and medicine. Their research spans a variety of subfields including artificial intelligence, signal processing, radiology, nuclear medicine, imaging, computer vision, pattern recognition, and computer networks and communications.

The scientist has contributed extensively to several main topics, notably:

Advanced Malware Detection Techniques
Network Security and Intrusion Detection
Radiomics and Machine Learning in Medical Imaging
AI in Cancer Detection
Software Testing and Debugging Techniques
Advanced Neural Network Applications
COVID-19 Diagnosis Using AI

Among the recent papers associated with Francesco Mercaldo are:

"Deep learning for image-based mobile malware detection," 2020, Journal of Computer Virology and Hacking Techniques
"Explainable Deep Learning for Pulmonary Disease and Coronavirus COVID-19 Detection from X-rays," 2020, Computer Methods and Programs in Biomedicine
"Towards an interpretable deep learning model for mobile malware detection and family identification," 2021, Computers & Security
"A ViT-AMC Network With Adaptive Model Fusion and Multiobjective Optimization for Interpretable Laryngeal Tumor Grading From Histopathological Images," 2022, IEEE Transactions on Medical Imaging
"Machine learning for coronavirus covid-19 detection from chest x-rays," 2020, Procedia Computer Science

Frequent coauthors in the scientist's body of work include:

Antonella Santone
Fabio Martinelli
Mario Cesarelli
Luca Brunese
Giacomo Iadarola

Prominent publication venues for Francesco Mercaldo include:

Procedia Computer Science
Applied Sciences
Journal of Computer Virology and Hacking Techniques
Electronics
Sensors

Francesco Mercaldo has also contributed a book titled Artificial Intelligence for Cybersecurity, published by Springer Nature in 2022.

Best Publications

Explainable Deep Learning for Pulmonary Disease and Coronavirus COVID-19 Detection from X-rays.

Luca Brunese;Francesco Mercaldo;Alfonso Reginelli;Antonella Santone

579
Citations
Android malware detection based on system call sequences and LSTM

Xi Xiao;Shaofeng Zhang;Francesco Mercaldo;Guangwu Hu

263
Citations
Classification of ransomware families with machine learning based on N-gram of opcodes

Hanqi Zhang;Hanqi Zhang;Xi Xiao;Francesco Mercaldo;Shiguang Ni

239
Citations
Diabetes Mellitus Affected Patients Classification and Diagnosis through Machine Learning Techniques

Francesco Mercaldo;Vittoria Nardone;Antonella Santone

174
Citations
Detecting Android malware using sequences of system calls

Gerardo Canfora;Eric Medvet;Francesco Mercaldo;Corrado Aaron Visaggio

154
Citations
Effectiveness of Opcode ngrams for Detection of Multi Family Android Malware

Gerardo Canfora;Andrea De Lorenzo;Eric Medvet;Francesco Mercaldo

151
Citations
Ransomware Steals Your Phone. Formal Methods Rescue It

Francesco Mercaldo;Vittoria Nardone;Antonella Santone;Corrado Aaron Visaggio

128
Citations
An ensemble learning approach for brain cancer detection exploiting radiomic features.

Luca Brunese;Francesco Mercaldo;Francesco Mercaldo;Alfonso Reginelli;Antonella Santone

123
Citations
Human behavior characterization for driving style recognition in vehicle system

Fabio Martinelli;Francesco Mercaldo;Albina Orlando;Vittoria Nardone

119
Citations
R-PackDroid: API package-based characterization and detection of mobile ransomware

Davide Maiorca;Francesco Mercaldo;Giorgio Giacinto;Corrado Aaron Visaggio

115
Citations
A ViT-AMC Network With Adaptive Model Fusion and Multiobjective Optimization for Interpretable Laryngeal Tumor Grading From Histopathological Images

Unknown

111
Citations
Car hacking identification through fuzzy logic algorithms

Fabio Martinelli;Francesco Mercaldo;Vittoria Nardone;Antonella Santone

110
Citations
Deep learning for image-based mobile malware detection

Francesco Mercaldo;Antonella Santone

108
Citations
Evaluating Convolutional Neural Network for Effective Mobile Malware Detection

Fabio Martinelli;Fiammetta Marulli;Francesco Mercaldo

102
Citations
A Classifier of Malicious Android Applications

Gerardo Canfora;Francesco Mercaldo;Corrado Aaron Visaggio

99
Citations
An HMM and structural entropy based detector for Android malware

Gerardo Canfora;Francesco Mercaldo;Corrado Aaron Visaggio

94
Citations
TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification

Unknown

93
Citations
Towards an interpretable deep learning model for mobile malware detection and family identification

Giacomo Iadarola;Fabio Martinelli;Francesco Mercaldo;Francesco Mercaldo;Antonella Santone

89
Citations
On the effectiveness of system API-related information for Android ransomware detection

Michele Scalas;Davide Maiorca;Francesco Mercaldo;Corrado Aaron Visaggio

88
Citations
Talos: no more ransomware victims with formal methods

Aniello Cimitile;Francesco Mercaldo;Vittoria Nardone;Antonella Santone

81
Citations
Machine learning for coronavirus covid-19 detection from chest x-rays

Luca Brunese;Fabio Martinelli;Francesco Mercaldo;Francesco Mercaldo;Antonella Santone

76
Citations
Ransomware Inside Out

Francesco Mercaldo;Vittoria Nardone;Antonella Santone

69
Citations
Android apps and user feedback: a dataset for software evolution and quality improvement

Giovanni Grano;Andrea Di Sorbo;Francesco Mercaldo;Corrado A. Visaggio

48
Citations

Frequent Co-Authors

Fabio Martinelli National Research Council (CNR)

Antonella Santone University of Molise

Corrado Aaron Visaggio University of Sannio

Gerardo Canfora University of Sannio

Alfredo Cuzzocrea University of Calabria

Arun Kumar Sangaiah National Yunlin University of Science and Technology

Giorgio Giacinto University of Cagliari

Giuseppe Peter Vanoli University of Molise

Huimin Lu Kyushu Institute of Technology

Sebastiano Panichella University of Zurich

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