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Marco Piangerelli
PeerJ Editor
1,135 Points

Contributions by role

Editor 1,135

Contributions by subject area

Artificial Intelligence
Computer Education
Data Mining and Machine Learning
Bioinformatics
Computer Vision
Neural Networks
Data Science
Spatial and Geographic Information Systems
Computational Biology
Computer Networks and Communications
Algorithms and Analysis of Algorithms
Graphics
Human-Computer Interaction
World Wide Web and Web Science
Software Engineering
Optimization Theory and Computation

Marco Piangerelli

PeerJ Editor

Summary

Dr. Marco Piangerelli had his M.Sc. in Bioengineering from the University of Bologna and got his Ph.D. in Computer Science from the University of Camerino, where he is currently a Research Associate. His research interests are mainly on Unsupervised techniques for Machine Learning and Data Science in Manufacturing and Bio Science, Self-Adaptive Systems, and Topological Data Analysis. He is the author of many publications and was a PC member for many conferences and Workshops (AAAI-MAKE 2022-23-24 Spring Symposium, SACAIR 2023, DESRIST 2023, ATDA2019). He co-organized the 9th International Workshop on Engineering Energy Efficient InternetWorked Smart seNsors (E3WSN ) hosted by the 37th International Conference on Advanced Information Networking and Applications (AINA) at the Federal University of Juiz de Fora, Brazil. He has experience in Technological transfer projects and actively collaborates with international companies (INGKA, Schnell S.p.A., Sigma S.p.A., and Nuova Simonelli S.P.A.) and Italian ones (Syeew S.r.l). In 2024, he will be a Visiting Researcher at Addis Ababa University (Ethiopia) to work on topics related to his research fields.

Adaptive & Self-Organizing Systems Artificial Intelligence Brain-Computer Interface Computer Vision Data Mining & Machine Learning Data Science Natural Language & Speech Neural Networks

Editorial Board Member

PeerJ Computer Science

Past or current institution affiliations

University of Camerino

Work details

Research Associate

University of Camerino
Computer Science Division

Websites

  • Google Scholar
  • Personal Page

PeerJ Contributions

  • Edited 10

Academic Editor on

July 16, 2025
HybridFormer: a convolutional neural network-Transformer architecture for low dose computed tomography image denoising
Shanaz Sharmin Jui, Zhitao Guo, Rending Jiang, Jiale Liu, Bohua Li
https://doi.org/10.7717/peerj-cs.2952
July 8, 2025
Result Assessment Tool (RAT): empowering search engine data analysis
Sebastian Sünkler, Dirk Lewandowski, Sebastian Schultheiß, Nurce Yagci
https://doi.org/10.7717/peerj-cs.2962
June 11, 2025
Recent advances in the inverse design of silicon photonic devices and related platforms using deep generative models
Sun Jae Baek, Minhyeok Lee
https://doi.org/10.7717/peerj-cs.2895
April 29, 2025
Human pose estimation in physiotherapy fitness exercise correction using novel transfer learning approach
Aisha Naseer, Ali Raza, Hadeeqa Afzal, Aseel Smerat, Norma Latif Fitriyani, Yeonghyeon Gu, Muhammad Syafrudin
https://doi.org/10.7717/peerj-cs.2854
January 31, 2025
A quality assessment algorithm for no-reference images based on transfer learning
Yang Yang, Chang Liu, Hui Wu, Dingguo Yu
https://doi.org/10.7717/peerj-cs.2654
January 30, 2025
Testing convolutional neural network based deep learning systems: a statistical metamorphic approach
Faqeer ur Rehman, Clemente Izurieta
https://doi.org/10.7717/peerj-cs.2658
January 22, 2025
Ensemble graph auto-encoders for clustering and link prediction
Chengxin Xie, Jingui Huang, Yongjiang Shi, Hui Pang, Liting Gao, Xiumei Wen
https://doi.org/10.7717/peerj-cs.2648
November 26, 2024
Multi-angle information aggregation for inductive temporal graph embedding
Shaohan Wei
https://doi.org/10.7717/peerj-cs.2560
October 15, 2024
A bike-sharing demand prediction model based on Spatio-Temporal Graph Convolutional Networks
Chaoran Zhou, Jiahao Hu, Xin Zhang, Zerui Li, Kaicheng Yang
https://doi.org/10.7717/peerj-cs.2391
September 23, 2024
Analyzing the critical steps in deep learning-based stock forecasting: a literature review
Zinnet Duygu Akşehir, Erdal Kılıç
https://doi.org/10.7717/peerj-cs.2312