Vangelis Karkaletsis

Vangelis Karkaletsis
National Center for Scientific Research Demokritos | ncsr · Insititute of Informatics and Telecommunications

About

254
Publications
41,031
Reads
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3,405
Citations
Additional affiliations
May 1997 - present
Independent Researcher
Independent Researcher
Description
  • http://skel.iit.demokritos.gr/
Education
December 1991 - March 1995
National and Kapodistrian University of Athens
Field of study
  • Dept. of Informatics and Telecommunications
September 1989 - September 1990
University of London, Queen Mary & Westfield College
Field of study
  • Department of Computer Science
September 1984 - July 1989
University of Patras
Field of study
  • Department of Computer Engineering & Informatics

Publications

Publications (254)
Preprint
Full-text available
Due to the wide range of timescales that are present in macromolecular systems, hierarchical multiscale strategies are necessary for their computational study. Coarse-graining (CG) allows to establish a link between different system resolutions and provides the backbone for the development of robust multiscale simulations and analyses. The CG mappi...
Preprint
Full-text available
Coarse graining (CG) enables the investigation of molecular properties for larger systems and at longer timescales than the ones attainable at the atomistic resolution. Machine learning techniques have been recently proposed to learn CG particle interactions, i.e. develop CG force fields. Graph representations of molecules and supervised training o...
Conference Paper
Coarse graining (CG) enables the investigation of molecular properties for larger systems and at longer timescales than the ones attainable at the atomistic resolution. Machine learning techniques have been recently proposed to learn CG particle interactions, i.e. develop CG force fields. Graph representations of molecules and supervised training o...
Conference Paper
Due to the wide range of timescales that are present in macromolecular systems, hierarchical multiscale strategies are necessary for their computational study. Coarse-graining (CG) allows to establish a link between different system resolutions and provides the backbone for the development of robust multiscale simulations and analyses. The CG mappi...
Technical Report
Full-text available
HPC constitutes a strategic resource in the digital decade dominated by an increasing number of data-intensive applications and services and an ever increasing need to address our macroscopic and microscopic challenges for the benefit of citizens, businesses, researchers and public administrations around the world. Thus, increasing the usability of...
Article
Unsupervised representation learning tends to produce generic and reusable latent representations. However, these representations can often miss high-level features or semantic information, since they only observe the implicit properties of the dataset. On the other hand, supervised learning frameworks learn task-oriented latent representations tha...
Conference Paper
Full-text available
ExtremeEarth is a three-year H2020 ICT research and innovation project. Its main objective is to develop Artificial Intelligence and big data technologies that scale to the large volumes of big Copernicus data, information and knowledge, and apply these technologies in two of the European Space Agency (ESA) Thematic Exploitation Platforms (TEP): Fo...
Article
Full-text available
In recent years, science has relied more than ever on large-scale data as well as on distributed computing and human resources. Scientists and research engineers in fields such as climate science and computational seismology, constantly strive to make good use of remote and largely heterogeneous computing resources (HPC, Cloud, institutional or loc...
Article
Health care platforms rapidly shift toward the ICT-based solutions. In this context, a wide range of consumer electronics technologies come into play ranging from robotics, embedded systems, sensors, and communication infrastructures. Driven by such observations, the H2020 RADIO project set forward a service-oriented, easily expandable design parad...
Conference Paper
Full-text available
Safe and efficient Human-Robot Collaboration (HRC) requires recognizing human collaborators intention. Hand pose kinematics early on an ongoing movement can provide information for predicting future human actions. Accurate state-of-the-art methods used for human hand pose estimation are either marker-based or make use of multiple cameras set around...
Article
The recent breakthroughs in deep neural architectures across multiple machine learning fields have led to the widespread use of deep neural models. These learners are often applied as black-box models that ignore or insufficiently utilize a wealth of preexisting semantic information. In this study, we focus on the text classification task, investig...
Article
Full-text available
This White Paper aims to set out the National AI Strategic Vision for Greece and to provide an initial plan of action on how to achieve this vision. It aims to accelerate the adoption and development of AI in both the private and public sectors in Greece and increase the relevant skills and the research and development (R&D) base through the provis...
Chapter
This chapter describes the evolution of a real, multi-document, multilingual news summarization methodology and application, named NewSum, the research problems behind it, as well as the steps taken to solve these problems. The system uses the representation of n-gram graphs to perform sentence selection and redundancy removal towards summary gener...
Conference Paper
The DARE platform has been designed to help research developers deliver user-facing applications and solutions over diverse underlying e-infrastructures, data and computational contexts. The platform is Cloud-ready, and relies on the exposure of APIs, which are suitable for raising the abstraction level and hiding complexity. At its core, the platf...
Conference Paper
In this paper we introduce evidence transfer for clustering, a deep learning method that can incrementally manipulate the latent representations of an autoencoder, according to external categorical evidence, in order to improve a clustering outcome. It is deployed on a baseline solution to reduce the cross entropy between the external evidence and...
Article
Full-text available
Evidence transfer for clustering is a deep learning method that manipulates the latent representations of an autoencoder according to external categorical evidence with the effect of improving a clustering outcome. Evidence transfer's application on clustering is designed to be robust when introduced with a low quality of evidence, while increasing...
Article
Full-text available
Deep learning models, while effective and versatile, are becoming increasingly complex, often including multiple overlapping networks of arbitrary depths, multiple objectives and non-intuitive training methodologies. This makes it increasingly difficult for researchers and practitioners to design, train and understand them. In this paper we present...
Chapter
Demographic and epidemiologic transitions have brought a new health care paradigm with the presence of both growing elderly population and chronic diseases. Life expectancy is increasing as well as the need for long-term care. Institutional care for the aged population faces economical struggles with low staffing ratios and consequent quality probl...
Chapter
As smart interconnected sensing devices are becoming increasingly ubiquitous, more applications are becoming possible by re-arranging and re-connecting sensing and sensor signal analysis in different pipelines. Naturally, this is best facilitated by extremely thin services that expose minimal functionality and are extremely flexible regarding the w...
Article
Full-text available
In this article, we present a taxonomy in Robot-Assisted Training; a growing body of research in Human–Robot Interaction which focuses on how robotic agents and devices can be used to enhance user’s performance during a cognitive or physical training task. Robot-Assisted Training systems have been successfully deployed to enhance the effects of a t...
Poster
Full-text available
The DARE e-science platform (http://project-dare.eu) is designed for efficient and traceable development of complex experiments and domain-specific services on the Cloud. DARE will be validated via two scientific pilots: Working with the ENES community for climate, the first will enhance part of the data-access and pre-processing procedures of the...
Poster
Full-text available
End Users of Climate data have nowadays to struggle with accessing the data they need for their research because of the rapid increase in data volumes. The whole climate data archive is expected to reach a volume of 30 Pb in 2018 and up to 2000 Pb in 2022 (estimated). On-demand data processing solutions as close as possible to the data storage are...
Preprint
Full-text available
In this paper we introduce evidence transfer for clustering, a deep learning method that can incrementally manipulate the latent representations of an autoencoder, according to external categorical evidence, in order to improve a clustering outcome. It is deployed on a baseline solution to reduce the cross entropy between the external evidence and...
Conference Paper
Full-text available
In this paper, we present a taxonomy in Robot-Assisted Training; a growing body of research in Human-Robot Interaction which focuses on how robotic agents and devices can be used to enhance user's performance during a cognitive or physical training task. The proposed taxonomy includes a set of parameters that characterize such systems, in order to...
Conference Paper
Full-text available
Demographic and epidemiologic transitions have brought a new health care paradigm where life expectancy is increasing as well as the need for long-term care. To meet the resulting challenge, healthcare systems need to take full advantage of new opportunities offered by technical advancements in ICT. The RADIO project explores a novel approach to us...
Article
Full-text available
Emergency response applications for nuclear or radiological events can be significantly improved via deep feature learning due to the hidden complexity of the data and models involved. In this paper we present a novel methodology for rapid source estimation during radiological releases based on deep feature extraction and weather clustering. Atmosp...
Preprint
Full-text available
Speech music discrimination is a traditional task in audio analytics, useful for a wide range of applications (automatic speech recognition, radio broadcast monitoring, etc), that focuses on segmenting audio streams and classifying each segment as either speech or music. In this paper, we exploit the capabilities of convolu-tional neural networks (...
Conference Paper
Full-text available
Emergencies that involve the release of hazardous substances into the atmosphere affects life and nature for several years. The timely and reliable estimation of the expected consequences on people and the environment facilitates informed decision making and timely response. Here, we demonstrate a tool that leverages Big Data and Semantic Web techn...
Conference Paper
Full-text available
Dataset description vocabularies focus on provenance, ver-sioning, licensing, and similar metadata. VoID is a notable exception, providing some expressivity for describing subsets and their contents and can, to some extent, be used for discovering relevant resources and for optimizing querying. In this paper we describe the Sevod vocabulary, an ext...
Conference Paper
We present a method that recognizes exercising activities performed by a single human in the context of a real home environment. Towards this end, we combine sensorial information stemming from a smartphone accelerometer, with visual information from a simple web camera. Low-level features inspired from the audio analysis domain are used to represe...
Conference Paper
Full-text available
The management and analysis of large-scale datasets – described with the term Big Data – involves the three classic dimensions volume, velocity and variety. While the former two are well supported by a plethora of software components, the variety dimension is still rather neglected. We present the BDE platform – an easy-to-deploy, easy-to-use and a...
Conference Paper
This paper proposes a deep learning classification method for frame-wise recognition of human activities , using raw color (RGB) information. In particular, we present a Convolutional Neural Network (CNN) classification approach for recognising three basic motion activity classes, that cover the vast majority of human activities in the context of a...
Conference Paper
Full-text available
In this paper, we present an interactive learning and adaptation framework that facilitates the adaptation of an interactive agent to a new user. We argue that Interactive Reinforcement Learning methods can be utilized and integrated to the adaptation mechanism, enabling the agent to refine its learned policy in order to cope with different users....
Conference Paper
The rapidly increasing amount and variety of data coming from satellites and other sources is raising new issues such as the management and exploitation of extremely large and complex datasets (Big Data); the main challenge in the Space and Security domain is to improve the capacity to extract in a timely manner operational (i.e. useful and clear)...
Chapter
As smart interconnected sensing devices are becoming increasingly ubiquitous, more applications are becoming possible by re-arranging and re-connecting sensing and sensor signal analysis in different pipelines. Naturally, this is best facilitated by extremely thin services that expose minimal functionality and are extremely flexible regarding the w...
Conference Paper
The insights gained by the large-scale analysis of health-related data can have an enormous impact in public health and medical research, but access to such personal and sensitive data poses serious privacy implications for the data provider and a heavy data security and administrative burden on the data consumer. In this paper we present an archit...
Conference Paper
In this paper, we present an interactive learning and adaptation framework. The framework combines Interactive Reinforcement Learning methods to effectively adapt and refine a learned policy to cope with new users. We argue that implicit feedback provided by the primary user and guidance from a secondary user can be integrated to the adaptation mec...
Conference Paper
Demographic and epidemiologic transitions have brought forward a new health care paradigm with the presence of both growing elderly population and chronic diseases. Recent technological advances can support elderly people in their domestic environment assuming that several ethical and clinical requirements can be met. This paper presents an archite...
Article
Argument extraction is the task of identifying arguments, along with their components in text. Arguments can be usually decomposed into a claim and one or more premises justifying it. Among the novel aspects of this work is the thematic domain itself which relates to Social Media, in contrast to traditional research in the area, which concentrates...
Conference Paper
In this paper, we present a framework for physical rehabilitation , that uses a combination of video gaming and robotic technology to allow the monitoring and progress tracking of a person during physical therapy. The system, called MAGNI, uses the advanced control capabilities of the Bar-rett WAM Arm robot and a custom-made video game. The MAGNI s...
Conference Paper
Integrating robotic platforms in smart home environments can improve the monitoring quality of daily activities. In this study, we explore a scenario where a robot provides a service to the users, which in our case is delivering a cup of coffee. The users place their order via an application, which at the same time captures a short video from their...
Conference Paper
Full-text available
In this paper, we present an Adaptive Multimodal Dialogue System for Depressive and Anxiety Disorders Screening (DADS). The system interacts with the user through verbal and non-verbal communication to elicit the information needed to make referrals and recommendations for depressive and anxiety disorders while encouraging the user and keeping them...
Conference Paper
A great deal of recent research has focused on social and assistive robots that can achieve a more natural and realistic interaction between the agent and its environment. Following this direction, this paper aims to establish a computational framework that can associate objects with their uses and their basic characteristics in an automated manner...
Conference Paper
Full-text available
Demographic and epidemiologic transitions in Europe have brought a new health care paradigm where life expectancy is increasing as well as the need for long-term care. To meet the resulting challenge, European healthcare systems need to take full advantage of new opportunities offered by technical advancements in ICT. The RADIO project explores a n...
Conference Paper
Dataset description vocabularies focus on provenance, versioning, licensing, and similar metadata. VoID is a notable exception, providing some expressivity for describing subsets and their contents and can, to some extent, be used for discovering relevant resources and for optimizing querying. In this poster we describe an extension of VoID that pr...
Article
Full-text available
Reducing the possibility of ship accidents in the Aegean Sea is important to all economic, environmental, and cultural sectors of Greece. Despite the increased traffic and the related obvious risk, there are currently no national-level monitoring policies in Greece. To this end, we develop the AMINESS platform that will integrate information from m...
Conference Paper
Full-text available
The NOMAD project (Policy Formulation and Validation through non Moderated Crowd-sourcing) is a project that supports policy making, by providing rich, actionable information related to how citizens perceive different policies. NOMAD automatically analyzes citizen contributions to the informal web (e.g. forums, social networks, blogs, newsgroups an...
Article
Full-text available
Purpose – The purpose of this study is to develop a novel approach to e-participation, which is based on “passive crowdsourcing” by government agencies, exploiting the extensive political content continuously created in numerous Web 2.0 social media (e.g. political blogs and microblogs, news sharing sites and online forums) by citizens without gove...
Article
Full-text available
Modern assistive environments have the ability to collect data from various distributed sources and the need to react swiftly to changes. As information flows, in the form of simple, source events, it becomes more and more difficult to quickly analyze the collected data in an automated way and transform them into operational knowledge. Event Recogn...
Chapter
This chapter describes a real, multi-document, multilingual news summarization application, named NewSum, the research problems behind it, as well as the novel methods proposed and tested to solve these problems. The system uses the representation of n-gram graphs in a novel manner to perform sentence selection and redundancy removal for the summar...
Technical Report
Full-text available
Traditional Artificial Cognitive Systems (for example, intelligent robots) share a number of limitations. First, they are usually made up only of machine components; humans are only playing the role of user or supervisor. And yet, there are tasks in which the current state of the art of AI has much worse performance or is more expensive than humans...
Conference Paper
The interlinking, maintenance and updating of different Linked Data repositories is steadily becoming a critical issue as the amount of published data increases. Hence, the automation or the provision of substantial computational support in various phases of the management process is a particularly important topic. The present paper discusses the m...
Conference Paper
We present the application of a recently proposed probabilistic logical formalism, on the task of sensor data fusion in the USEFIL project. USEFIL seeks to extract valuable knowledge concerning the well-being of elderly people by combining information coming from low-cost, unobtrusive monitoring devices. The approach we adopt to device its data fus...
Article
It has been demonstrated that human users attribute a personality to the computer interfaces they use, regardless of whether one has been explicitly encoded in the system's design or not. In this paper, we explore a method for having explicit control over the personality that a spoken human-robot interface is perceived to exhibit by its users. Our...
Conference Paper
Summary evaluation has been a distinct domain of research for several years. Human summary evaluation appears to be a high-level cognitive process and, thus, difficult to reproduce. Even though several automatic evaluation methods correlate well to human evaluations over systems, we fail to get equivalent results when judging individual summaries....
Conference Paper
Adaptive Dialogue Systems can be seen as smart interfaces that typically use natural language (spoken or written) as a means of communication. They are being used in many applications, such as customer service, in-car interfaces, even in rehabilitation, and therefore it is essential that these systems are robust, scalable and quickly adaptable in o...
Article
This paper presents a novel approach for exploiting an ontology in an ontology-based information extraction system, which substitutes part of the extraction process with reasoning, guided by a set of automatically acquired rules.