Ilias Gialampoukidis

Ilias Gialampoukidis
The Centre for Research and Technology, Hellas · Information Technologies Institute (ITI)

PhD

About

60
Publications
7,167
Reads
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264
Citations
Introduction
I am a postdoctoral researcher at Information Technologies Institute–Centre for Research & Technology Hellas (CERTH). I received a B.Sc. in Mathematics (2009), a M.Sc. in Statistics and Modeling (2011) and a PhD in Mathematics (2014) from the Aristotle University of Thessaloniki. I have participated in several EC-funded projects and my research interests involve Machine Learning, Network analytics, Multimedia Modelling and Big Data in Earth Observation, Security, Space and Environment.
Additional affiliations
January 2015 - September 2015
The Centre for Research and Technology, Hellas
Position
  • PostDoc Position
February 2013 - June 2014
Aristotle University of Thessaloniki
Position
  • Teaching assistance
Description
  • Teaching assistance for the course "Information Theory and Chaos"
April 2011 - November 2014
Aristotle University of Thessaloniki
Position
  • PhD Student
Education
October 2009 - February 2011
Aristotle University of Thessaloniki
Field of study
  • Statistics and Modeling
January 2007 - June 2007
Lund University
Field of study
  • Mathematics

Publications

Publications (60)
Conference Paper
Monitoring terrorist groups and their suspicious activities in social media is a challenging task, given the large amounts of data involved and the need to identify the most influential users in a smart way. To this end, many efforts have focused on using centrality measures for the identification of the key players in terrorism-related social medi...
Chapter
Full-text available
Nowadays there is an important need by journalists and media monitoring companies to cluster news in large amounts of web articles, in order to ensure fast access to their topics or events of interest. Our aim in this work is to identify groups of news articles that share a common topic or event, without a priori knowledge of the number of clusters...
Conference Paper
Full-text available
Effective multimedia retrieval requires the combination of the heterogeneous media contained within multimedia objects and the features that can be extracted from them. To this end, we extend a unifying framework that integrates all well-known weighted, graph-based, and diffusion-based fusion techniques that combine two modalities (textual and visu...
Conference Paper
This paper presents VERGE interactive search engine, which is capable of browsing and searching into video content. The system integrates content-based analysis and retrieval modules such as video shot segmentation, concept detection, clustering, as well as visual similarity and object-based search.
Article
Full-text available
Flooding is one of the most destructive natural phenomena that happen worldwide, leading to the damage of property and infrastructure or even the loss of lives. The escalation in the intensity and number of flooding events as a result of the combination of climate change and anthropogenic factors motivates the need to adopt real-time solutions for...
Article
Full-text available
Manufacturing companies increasingly become “smarter” as a result of the Industry 4.0 revolution. Multiple sensors are used for industrial monitoring of machines and workers in order to detect events and consequently improve the manufacturing processes, lower the respective costs, and increase safety. Multisensor systems produce big amounts of hete...
Article
Social media play an important role in the daily life of people around the globe and users have emerged as an active part of news distribution as well as production. The threatening pandemic of COVID-19 has been the lead subject in online discussions and posts, resulting to large amounts of related social media data, which can be utilised to reinfo...
Chapter
Discovering potential concepts and events by analyzing Earth Observation (EO) data may be supported by fusing other distributed data sources such as non-EO data, for instance, in-situ citizen observations from social media. The retrieval of relevant information based on a target query or event is critical for operational purposes, for example, to m...
Chapter
Earth Observation (EO) Big Data Collections are acquired at large volumes and variety, due to their high heterogeneous nature. The multimodal character of EO Big Data requires effective combination of multiple modalities for similarity search. We propose a late fusion mechanism of multiple rankings to combine the results from several uni-modal sear...
Chapter
This paper presents VERGE, an interactive video search engine that supports efficient browsing and searching into a collection of images or videos. The framework involves a variety of retrieval approaches as well as reranking and fusion capabilities. A Web application enables users to create queries and view the results in a fast and friendly manne...
Conference Paper
Discovering potential concepts and events by analyzing Earth Observation (EO) data may be supported by fusing other distributed data sources such as non-EO data, for instance, in-situ citizen observations from social media. The retrieval of relevant information based on a target query or event is critical for operational purposes, for example, to m...
Article
Full-text available
During the last decades, massive amounts of satellite images are becoming available that can be enriched with semantic annotations for the creation of value-added Earth Observation products. One challenge is to extract knowledge from the raw satellite data in an automated way and to effectively manage the extracted information in a semantic way, to...
Article
Recent developments in remote sensing have shown that snow depth can be estimated accurately on a global scale using satellite images through cross-polarization and copolarization backscatter measurements. This method does, however, have some limitations in low-land areas with dense forest coverage and shallow snow, which are often found nearby urb...
Chapter
This paper demonstrates VERGE, an interactive video retrieval engine for browsing a collection of images or videos and searching for specific content. The engine integrates a multitude of retrieval methodologies that include visual and textual searches and further capabilities such as fusion and reranking. All search options and results appear in a...
Article
Density-based clustering is an effective clustering approach that groups together dense patterns in low- and high-dimensional vectors, especially when the number of clusters is unknown. Such vectors are obtained for example when computer scientists represent unstructured data and then groups them into clusters in an unsupervised way. Another facet...
Chapter
Towards meeting both challenges of big multimedia data such as scalability and diversity, this chapter presents the state‐of‐the‐art techniques in multimodal fusion of heterogeneous sources of data. It explores both weakly supervised and semi‐supervised approaches that minimize the complexity of the designed systems as well as maximizing their scal...
Poster
Full-text available
EOPEN (https://eopen-project.eu/) is a project which has received funding from the European Union’s Horizon 2020 research and innovation programme under the topic EO Big Data Shift in 2017 and has a duration of 3 years, starting from November 2017. In this work, we present the concept of the project, its objectives and the lessons learnt after almo...
Conference Paper
Full-text available
Artificial Intelligence (AI) technologies are getting deeper and deeper into remote sensing and satellite image processing offering value-added products and services in a real-time manner. Deep learning techniques applied on visual content are able to infer accurate decisions about concepts and events in an automatic way, based on Deep Convolutiona...
Conference Paper
Full-text available
This paper presents the algorithms that CERTH-ITI team deployed to tackle flood detection and road passability from social media and satellite data. Computer vision and deep learning techniques are combined in order to analyze social media and satellite images, while word2vec is used to analyze textual data. Multimodal fusion is also deployed in CE...
Article
Full-text available
Analysts and journalists face the problem of having to deal with very large, heterogeneous, and multilingual data volumes that need to be analyzed, understood, and aggregated. Automated and simplified editorial and authoring process could significantly reduce time, labor, and costs. Therefore, there is a need for unified access to multilingual and...
Conference Paper
Full-text available
In every disaster time is the enemy and getting accurate and helpful real-time information for supporting decision support is critical. Data sources for Risk Management Platforms are heterogeneous. This includes data coming from several resources: sensors, social media, the general public and first responders. All this data needs to be analyzed, ag...
Chapter
Full-text available
Social media are widely used by terrorist organizations and extremist groups for disseminating propaganda and recruiting new members. Given the recent pledges both by the major social media platforms and governments towards combating online terrorism, our work aims at understanding the terrorism-related content posted on social media and distinguis...
Conference Paper
Disaster monitoring based on social media posts has raised a lot of interest in the domain of computer science the last decade, mainly due to the wide area of applications in public safety and security and due to the pervasiveness not solely on daily communication but also in life-threating situations. Social media can be used as a valuable source...
Poster
The identification of flooded areas over Earth Observation (EO) satellite images has paved the way to monitor damaged areas and take effective actions. Classifying all pixels of a satellite image as a flooded area or not allows for creating maps which are then used by civil protection agencies and first responders. In this work, a method, firstly i...
Poster
Full-text available
The poster presents an overview of the EOPEN project (H2020-776019) funded by the European Commission. Details can be found on the project website: http://eopen-project.eu/
Article
Full-text available
Heterogeneous sources of information, such as images, videos, text and metadata are often used to describe different or complementary views of the same multimedia object, especially in the online news domain and in large annotated image collections. The retrieval of multimedia objects, given a multimodal query, requires the combination of several s...
Conference Paper
Large amounts of social media posts are produced on a daily basis and monitoring all of them is a challenging task. In this direction we demonstrate a topic detection and visualisation tool in Twitter data, which filters Twitter posts by topic or keyword, in two different languages; German and Turkish. The system is based on state-of-the-art news c...
Conference Paper
Nowadays, a large amount of text documents are produced on a daily basis, so we need efficient and effective access to their content. News articles, blogs and technical reports are often lengthy, so the reader needs a quick overview of the underlying content. To that end we present graph-based models for keyword extraction, in order to compare the...
Conference Paper
Full-text available
The increasing amount of image databases over the last years has highlighted our need to represent an image collection efficiently and quickly. The majority of image retrieval and image clustering approaches has been based on the construction of a visual vocabulary in the so called Bag-of-Visual-words (BoV) model, analogous to the Bag-of-Words (BoW...
Conference Paper
Full-text available
This paper presents the algorithms that CERTH team deployed in order to tackle disaster recognition tasks and more specifically Disaster Image Retrieval from Social Media (DIRSM) and Flood-Detection in Satellite images (FDSI). Visual and textual analysis, as well as late fusion of their similarity scores, were deployed in social media images, while...
Conference Paper
Full-text available
Social media are widely used among terrorists to communicate and disseminate their activities. User-to-user interaction (e.g. mentions, follows) leads to the formation of complex networks, with topology that reveals key-players and key-communities in the terrorism domain. Both the administrators of social media platforms and Law Enforcement Agencie...
Conference Paper
This paper presents VERGE interactive video retrieval engine, which is capable of browsing and searching into video content. The system integrates several content-based analysis and retrieval modules including concept detection, clustering, visual similarity search, object-based search, query analysis and multimodal and temporal fusion.
Conference Paper
Full-text available
Community detection is a valuable tool for analyzing complex networks. This work investigates the community detection problem based on the density-based algorithm DBSCAN*. This algorithm requires, though, a lower bound for the community size to be determined a priori, a challenging task. To this end, this work proposes the application of a Martinga...
Conference Paper
Full-text available
In this paper, we present a framework for topic detection in news articles. The framework receives as input the results retrieved from a query-based search and clusters them by topic. To this end, the recently introduced " DBSCAN-Martingale " method for automatically estimating the number of topics and the well-established Latent Dirichlet Allocati...
Chapter
The Time Operator and Internal Age are intrinsic features of Entropy producing Innovation Processes. The innovation spaces at each stage are the eigenspaces of the Time Operator. The internal Age is the average innovation time, analogous to lifetime computation. Time Operators were originally introduced for Quantum Systems and highly unstable Dynam...
Conference Paper
Most of the image retrieval approaches nowadays are based on the Bag-of-Words (BoW) model, which allows for representing an image efficiently and quickly. The efficiency of the BoW model is related to the efficiency of the visual vocabulary. In general, visual vocabularies are created by clustering all available visual features, formulating specifi...
Article
We extend the Time Operator and Age to Network Evolution models. Internal Age formulas and the distribution of innovations are computed for Erdős–Rényi Random Networks, for Markov Networks and Barabási–Albert preferential Attachment Networks. The innovation probabilities are found to be proportional to the quadratic entropy (which coincides with th...
Article
Full-text available
The time operator and internal age are intrinsic features of entropy producing innovation processes. The innovation spaces at each stage are the eigenspaces of the time operator. The internal age is the average innovation time, analogous to lifetime computation. Time operators were originally introduced for quantum systems and highly unstable dynam...
Article
We extend the notion of Time Operator from Kolmogorov Dynamical Systems and Bernoulli processes to Markov processes. The general methodology is presented and illustrated in the simple case of binary processes. We present a method to compute the eigenfunctions of the Time Operator. Internal Ages are related to other characteristic times of Markov ch...
Article
Based on previous work on non-equilibrium statistical mechanics, and the recent extensions of Time Operators to observations and financial processes, we construct a general Time Operator for non-stationary Bernoulli Processes. The Age and the innovation probabilities are defined and discussed in detail and a formula is presented for the special cas...

Projects

Projects (2)
Project
The project relies on (α) the infrastructures and research developed in BEYOND Center of Excellence, (β) the roadmap resulted from GEO-CRADLE in regards to the priorities concerning the gathering and channeling of information over extended geographic areas in the agriculture sector, and (c) the Copernicus DataHubs operated by the BEYOND Center of Excellence (e.g. Hellenic Mirror Site, DIASHub). The EOPEN project studies the needs of users wanting to use or include EO data in in their big data analysis problems. The EOPEN concept is directed towards making EO data easy to use by the involved stakeholders. To achieve this, the EOPEN develops an exploitation platform that supports Big Data analysis by offering: 1. A library of commonly needed EO data processing capabilities and modules for data preparation; 2. Services and the capabilities to make optimal use of existing EO data sources and processing capabilities; 3. A framework supporting the Big Data Use Case lifecycle; 4. An infrastructure to perform Big Data processing and analytics. The contribution of the NOA is to engage the stakeholder community, and provide unhindered access to the Copernicus big satellite data so as to meet requirements concerning agricultural sector and food security over vast geographic areas. NOA leverages on high resolution of Sentinel 1-2 data together with crowd data and crowdsourcing techniques. The process demonstrates innovative EO information products easily used on a world basis in EU and non-EU countries (South Korea & China) for ensuring food insecurity. The innovation here generates reliable, accurate, timely and sustained crop monitoring and yield forecasts, supporting to the local/regional agriculture. This has a direct impact on food policies and security; reducing food poverty; boosting local business and investment opportunities. A web-application is built on a user centric approach transforming needs and requirements.
Project
beAWARE proposes an integrated solution to support forecasting, early warnings, transmission and routing of the emergency data, aggregated analysis of multimodal data and management the coordination between the first responders and the authorities. beAWARE intents to rely on platforms, theories and methodologies that are already used for disaster forecasting and management and add the elements that are necessary to make them working efficiently and in harm under the same objective.