David Camacho

David Camacho
Universidad Politécnica de Madrid | UPM · Departamento de Sistemas Informáticos

PhD in Computer Science
Editor-in-Chief of Expert Systems (https://onlinelibrary.wiley.com/journal/14680394)

About

440
Publications
166,746
Reads
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7,406
Citations
Introduction
Research areas: - Evolutionary Computation: Genetic Algorithms, Genetic Programming - Data Analysis and Data Mining: Clustering. - Swarm Intelligence: ACO. - Social Mining and Graph-based Algorithms. - Multi-agent Systems, Unmanned Systems, - Video Games. - Malware
Additional affiliations
September 2005 - June 2015
Autonomous University of Madrid
Position
  • Associate Professor, Head of AIDA Group
September 2005 - June 2015
Autonomous University of Madrid
Position
  • Associate Professor, Head of AIDA Group
November 1999 - August 2005
University Carlos III de Madrid
Position
  • Lecturer

Publications

Publications (440)
Article
The unstoppable growth of Social Networks (SNs), and the huge number of connected users, have become these networks as one of the most popular and successful domains for a large number of research areas. The different possibilities, volume and variety that these SNs offer, has become them an essential tool for every-day working and social relations...
Article
Full-text available
Social Networks (SNs) have become a powerful tool for the jihadism as they serve as recruitment assets, live forums, psychological warfare as well as sharing platforms. SNs enable vulnerable individuals to reach radicalised people hence triggering their own radicalisation process. There are many vulnerability factors linked to socio-economic and de...
Article
Management and mission planning over a swarm of unmanned aerial vehicle (UAV) remains to date as a challenging research trend in what regards to this particular type of aircrafts. These vehicles are controlled by a number of ground control station (GCS), from which they are commanded to cooperatively perform different tasks in specific geographic a...
Article
An Operating Procedure (OP), also known as checklist or action plan, is a list of actions or criteria arranged in a systematic way, commonly used in areas such as aviation or healthcare to ensure the success of critical tasks and to help decrease human errors. In these areas, operators are hardly trained to follow the OP carefully, but the evaluati...
Article
Full-text available
No‐reference image quality assessment (NR‐IQA) has garnered significant attention due to its critical role in various image processing applications. This survey provides a comprehensive and systematic review of NR‐IQA methods, datasets, and challenges, offering new perspectives and insights for the field. Specifically, we propose a novel taxonomy f...
Preprint
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The Long Range Arena (LRA) benchmark was designed to evaluate the performance of Transformer improvements and alternatives in long-range dependency modeling tasks. The Transformer and its main variants performed poorly on this benchmark, and a new series of architectures such as State Space Models (SSMs) gained some traction, greatly outperforming...
Conference Paper
This work introduces the concept of Generative Astrodynamics: the application of Generative Artificial Intelligence to develop complex space trajectories from a dataset of known solutions. A Deep Learning architecture is employed to map periodic orbits and transfer trajectories in the Circular Restricted Three-Body Problem into a latent space of fe...
Article
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Advancements in deep image synthesis techniques, such as generative adversarial networks (GANs) and diffusion models (DMs), have ushered in an era of generating highly realistic images. While this technological progress has captured significant interest, it has also raised concerns about the high challenge in distinguishing real images from their s...
Preprint
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The rapid advancement in large language models (LLMs) has significantly enhanced their ability to generate coherent and contextually relevant text, raising concerns about the misuse of AI-generated content and making it critical to detect it. However, the task remains challenging, particularly in unseen domains or with unfamiliar LLMs. Leveraging L...
Article
In recent years, with the advancement of deep learning, person re-identification (Re-ID) has become increasingly significant. The existing person Re-ID methods primarily focus on optimizing network architecture to enhance Re- ID task performance. However, these methods often overlook the importance of valuable features in distinguishing Re-ID tasks...
Article
Full-text available
Time series are essential for modeling a lot of activities such as software behavior, heart rate, and business processes. The analysis of the series data can prevent errors, boost profits, and improve the understanding of behaviors. Among the many techniques available, we can find deep learning techniques and data mining techniques. In data mining,...
Article
Benefiting from the progresses of sensing and sustainable computing technologies, recent years have witnessed the dramatic progresses of artificial intelligence of things (AIoT). As a typical AIoT application, WiFi-based human activity recognition has increasing popularities in smart homes. However, WiFibased action recognition often has unstable p...
Article
Full-text available
This article introduces DisTrack, a methodology and a tool developed for tracking and analyzing misinformation within online social networks (OSNs). DisTrack is designed to combat the spread of misinformation through a combination of natural language processing (NLP) social network analysis (SNA) and graph visualization. The primary goal is to dete...
Preprint
Full-text available
Authorship has entangled style and content inside. Authors frequently write about the same topics in the same style, so when different authors write about the exact same topic the easiest way out to distinguish them is by understanding the nuances of their style. Modern neural models for authorship can pick up these features using contrastive learn...
Preprint
Full-text available
Time series are essential for modelling a lot of activities such as software behavior, heart beats per time, business processes. The analysis of the series data can prevent errors, boost profits, and improve the understanding of behaviors. Among the many techniques available, we can find Deep Learning techniques and Data Mining techniques. In Data...
Preprint
Full-text available
Visual analytics is essential for studying large time series due to its ability to reveal trends, anomalies, and insights. DeepVATS is a tool that merges Deep Learning (Deep) with Visual Analytics (VA) for the analysis of large time series data (TS). It has three interconnected modules. The Deep Learning module, developed in R, manages the load of...
Preprint
Full-text available
The Three-Body Problem has fascinated scientists for centuries and it has been crucial in the design of modern space missions. Recent developments in Generative Artificial Intelligence hold transformative promise for addressing this longstanding problem. This work investigates the use of Variational Autoencoder (VAE) and its internal representation...
Article
Water leakage recognition plays a significant role in ensuring the safety of shield tunnel lining. However, current models cannot meet the engineering requirements because the tunnel environment is complex. In this concern, a one-stage deep learning model is developed for water leakage recognition. First, we design an attention module to reduce bac...
Preprint
Introduction: This article introduces DisTrack, a methodology and a tool developed for tracking and analyzing misinformation within Online Social Networks (OSNs). DisTrack is designed to combat the spread of misinformation through a combination of Natural Language Processing (NLP) Social Network Analysis (SNA) and graph visualization. The primary g...
Conference Paper
Full-text available
The Three-Body Problem has fascinated scientists for centuries and it has been crucial in the design of modern space missions. Recent developments in Generative Artificial Intelligence hold transformative promise for addressing this longstanding problem. This work investigates the use of Variational Autoencoder (VAE) and its internal representation...
Conference Paper
Full-text available
The rapid advancement of deepfake technology hasenabled the creation of highly realistic forged face images orvideos. While deepfake technology adds entertainment to people’slives, it also poses a potential threat to social security. Deepfakedetection is a crucial technology for identifying forged images.However, existing deep learning-based models...
Article
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Ransomware is a significant security threat that poses a serious risk to the security of smartphones, and its impact on portable devices has been extensively discussed in a number of research papers. In recent times, this threat has witnessed a significant increase, causing substantial losses for both individuals and organizations. The emergence an...
Article
In this editorial, we explore the urgent challenges created by the rise of infodemics —a term used to describe the epidemic spread of fake news, misinformation, and disinformation through social networks initially associated with the COVID-19 pandemic. This issue has drawn significant attention from various academic fields, including computer scien...
Article
Full-text available
Recent advancements in deep learning generative models have raised concerns as they can create highly convincing counterfeit images and videos. This poses a threat to people's integrity and can lead to social instability. To address this issue, there is a pressing need to develop new computational models that can efficiently detect forged content a...
Article
Full-text available
Heart sound signal analysis is very important for the early identification and treatment of cardiovascular illness. With rapid advancements in science and technology, artificial intelligence technologies are providing tremendous opportunities to enhance diagnosis and clinical decision‐making. Instruments can now perform clinical diagnoses that prev...
Article
Advanced language models demonstrate remarkable capabilities but remain vulnerable to adversarial word camouflage techniques. These techniques introduce visually perceptible language manipulations while conveying intended meanings to the target audience, potentially altering a model's output. This study explores the effectiveness and limitations of...
Article
In recent years generative AI models and tools have experienced a significant increase, especially techniques to generate synthetic multimedia content, such as images or videos. These methodologies present a wide range of possibilities; however, they can also present several risks that should be taken into account. In this survey we describe in det...
Article
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In recent times, there has been active research on multi-disease classification that aim to diagnose lung diseases and respiratory conditions using respiratory data. Recorded respiratory data can be used to diagnose various chronic diseases, such as asthma and pneumonia by applying different feature extraction methods. Previous studies have primari...
Article
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This editorial summarizes and analyzes 17 articles selected for a special issue on machine learning advances for Industry 4.0 applications. The diverse articles cover fault detection, deep learning optimisation, IoT networking, vehicle control, recommendation systems and domain knowledge integration. Key methods represented include neural networks,...
Article
Each year, wildfires destroy larger areas of Spain, threatening numerous ecosystems. Humans cause 90% of them (negligence or provoked) and the behaviour of individuals is unpredictable. However, atmospheric and environmental variables affect the spread of wildfires, and they can be analysed by using deep learning. In order to mitigate the damage of...
Chapter
The Manosphere movement and its subgroups have garnered the attention of researchers seeking deeper insights into their dynamics. This study specifically focuses on a particular subgroup within the Manosphere called Pick Up Artists (PUAs). PUAs concentrate on teaching heterosexual men sexual seduction techniques to attract women, often promoting a...
Article
Generative deep learning techniques have invaded the public discourse recently. Despite the advantages, the applications to disinformation are concerning as the counter-measures advance slowly. As the manipulation of multimedia content becomes easier, faster, and more credible, developing effective forensics becomes invaluable. Other works have ide...
Chapter
With the escalation of misinformation and malicious behavior issues on social media platforms, traditional detection-based measures often fail to address the problem in time. The use of multiple accounts or the continuous creation of new accounts makes it difficult to re-detect the presence of a user who, for example, has disseminated false informa...
Article
Full-text available
The appearance of complex attention‐based language models such as BERT, RoBERTa or GPT‐3 has allowed to address highly complex tasks in a plethora of scenarios. However, when applied to specific domains, these models encounter considerable difficulties. This is the case of Social Networks such as Twitter, an ever‐changing stream of information writ...
Article
Full-text available
Many vehicles are connected to the Internet, and big data are continually created. Various studies have been conducted involving the development of artificial intelligence, machine learning technology, and big data frameworks. The analysis of smart mobility big data is essential and helps to address problems that arise as society faces increased fu...
Preprint
Full-text available
Each year, wildfires destroy larger areas of Spain, threatening numerous ecosystems. Humans cause 90% of them (negligence or provoked) and the behaviour of individuals is unpredictable. However, atmospheric and environmental variables affect the spread of wildfires, and they can be analysed by using deep learning. In order to mitigate the damage of...
Preprint
Full-text available
The field of Deep Visual Analytics (DVA) has recently arisen from the idea of developing Visual Interactive Systems supported by deep learning techniques, in order to provide them with large-scale data processing capabilities and to unify their implementation across different data modalities and domains of application. In this paper we present Deep...
Preprint
Full-text available
Content moderation is the process of screening and monitoring user-generated content online. It plays a crucial role in stopping content resulting from unacceptable behaviors such as hate speech, harassment, violence against specific groups, terrorism, racism, xenophobia, homophobia, or misogyny, to mention some few, in Online Social Platforms. The...
Chapter
Full-text available
This research focuses on the detection of false claims in Spanish through the use of machine learning techniques. Most of the current work related to automated, or semi-automated, fake news detections are carried out for the English language, however, there is still a large room for improvement in other languages such as Spanish. The detection of f...
Chapter
Full-text available
Despite the large number of approaches proposed for detecting malicious applications targeting platforms such as Android, malware continuously evolves in order to avoid its detection and reach the users. Likewise, malware detection engines are continuously improved, trying to detect the most modern malware. Most of these detection tools employ sign...
Article
Full-text available
In scientific literature and industry, semantic and context-aware Natural Language Processing-based solutions have been gaining importance in recent years. The possibilities and performance shown by these models when dealing with complex Human Language Understanding tasks are unquestionable, from conversational agents to the fight against disinform...
Article
Full-text available
This paper presents a system, namely, the abnormal-weather monitoring and curation service (AWMC), which provides people with a better understanding of abnormal weather conditions. The service can analyze a set of multivariate weather datasets (i.e., 7 meteorological datasets from 18 cities in Korea) and show (i) which dates are mostly abnormal in...
Preprint
Authors writing documents imprint identifying information within their texts: vocabulary, registry, punctuation, misspellings, or even emoji usage. Finding these details is very relevant to profile authors, relating back to their gender, occupation, age, and so on. But most importantly, repeating writing patterns can help attributing authorship to...
Article
Full-text available
Introducción: Los bulos antivacunas son un tipo de desinformación sanitaria con gran peligro, dados sus efectos tangibles en la sociedad. Existen investigaciones relevantes sobre tipología de bulos, discursos negacionistas en redes o popularidad de las vacunas, pero este estudio aporta una visión complementaria y pionera, centrada en el discurso an...
Article
Full-text available
Introducción: Los bulos antivacunas son un tipo de desinformación sanitaria con gran peligro, dados sus efectos tangibles en la sociedad. Existen investigaciones relevantes sobre tipología de bulos, discursos negacionistas en redes o popularidad de las vacunas, pero este estudio aporta una visión complementaria y pionera, centrada en el discurso an...
Article
Full-text available
Political tensions have grown throughout Europe since the beginning of the new century. The consecutive crises led to the rise of different social movements in several countries, in which the political status quo changed. These changes included an increment of the different tensions underlying politics, as has been reported after many other politic...
Article
This study relies on using a Moth–Flame Optimization (MFO) method as a search algorithm and a Decision Tree (DT) as an evaluation algorithm to generate an efficient feature subset for intrusion detection systems (IDS). The target is to find a feature subset using the minimum number of traffic network features that later obtains the maximum performa...
Preprint
Full-text available
Over the last few years, convolutional neural networks (CNNs) have dominated the field of computer vision thanks to their ability to extract features and their outstanding performance in classification problems, for example in the automatic analysis of X-rays. Unfortunately, these neural networks are considered black-box algorithms, i.e. it is impo...
Conference Paper
One possible approach to deflect the trajectory of an asteroid on a collision course with the Earth, and prevent a potentially devastating impact, is the use of a kinetic impactor. The upcoming NASA DART and ESA Hera space missions will be the first to study and demonstrate this technique, by driving a spacecraft into the moon of a binary asteroid...
Article
Full-text available
Our society produces and shares overwhelming amounts of information through Online Social Networks (OSNs). Within this environment, misinformation and disinformation have proliferated, becoming a public safety concern in most countries. Allowing the public and professionals to efficiently find reliable evidence about the factual veracity of a claim...
Article
This editorial briefly analyses, describes, and provides a short summary of a set of selected papers published in a special issue focused on deep learning methods and architectures and their application to several domains and research areas. The set of selected and published articles covers several aspects related to two basic aspects in deep learn...