Digital Revolution and the Internet of Things

The objective of the MSc programme is to provide systematic and specialized training in the design and development of intelligent environments in next-generation networks, using the Internet of things as a baseline. Overall, the programme has been planned to take the following points into consideration:

  • The Internet of things forms a new stage in digital revolution, contributing to the expansion of the Knowledge-Based Society (Information Society).
  • Many facets of the Knowledge-Based Society have been using or will use the Internet of things in order to improve existing processes or create new and innovative services (smart home, smart cities, smart industry, energy, health, etc.).
  • The design and development of intelligent environments in next-generation networks requires the combined application of knowledge that derives from different disciplines.
  • Specialized staffing needs for career development opportunities.
  • Developments in ICT and increase of the provided critical / sensitive services.
  • Developing background knowledge for PhD studies.

Graduates will:

  • have an understanding of the available resources and tools for developing an Internet of things (IoT) system, in terms of both hardware and software, network connection and data analysis.
  • set up and design systems that are based on IoT.
  • manage information and knowledge that is dispersed, in different forms, across complex and dynamic environments.
  • set up and design modern network and communication systems and interconnect them with IoT.
  • design and manage innovative, digital and interactive applications with a wide range of uses.
  • understand the place and the role of IoT in the broader ICT industry, as well as its possible future developments.
  • understand the role of hardware and sensor networks in an IoT system.
  • understand the role of big data, data mining and cloud computing in a typical IoT system.
  • understand the role of security and privacy in future Internet systems.
  • understand the capabilities of machine learning tools and techniques in implementing intelligent environments.
  • understand the limitations of wireless and local network access and the degree to which these limitations affect IoT performance.
  • design, implement and evaluate IoT systems, which may consist of sensors, processing systems of small, average and big processing power, wireless networking, interconnection with third-party platforms (e.g. social networking sites, web services, corporate systems), data analysis and display, for a wide range of uses.
  • participate in research and development projects in the field of information and communication systems, generating new areas of knowledge.
  • compare and evaluate digital goods and services based on a solid background knowledge of modern network technologies.
  • manage and supervise complex and demanding communications projects.
  • acquire new knowledge in order to adapt to complex and dynamic environments and users.

This postgraduate programme is in accordance to the clauses of Law 4485/17, in combination with Law 4009/11, and is subject to the Regulations of Studies for the postgraduate programmes of studies, effective after their validation from the University’s Special Configuration Senate . Greek Government Gazette issue for the establishment of the postgraduate programme: 2965/B/24.07.2018

Entry Requirements – Candidates Evaluation

  • Degree or diploma holders in informatics and communications, engineering, sciences, or equivalent fields of study, from Greek universities or Technical Educational Institutions, or equivalent international institutions that are officially recognized by the Greek state
  • Graduates from Greek military higher education institutions  (Article 88 of Law 3883/2010, Greek Government Gazette issue 167/24-9-2010, Α)
  • Graduates from the Officers School of the Hellenic Police Academy (Article 38 of Law 4249/2014, Greek Government Gazette issue 73 Α)
  • Students of Greek higher education institutions that are in their last year of studies, provided that they will have sent a certificate of completion of studies before the deadline date for application to the MSc programme

Candidates are evaluated according to the criteria specified in Article 8 of the Regulations of Studies for the programme of postgraduate studies (available on the website).

Syllabus

1st Semester

Compulsory Courses
Course ID: 4001 Machine Learning ECTS: 7.5
Inductive learning: supervised, unsupervised and reinforcement learning. Concept learning. Decision trees. Artificial neural networks. Bayesian learning. Instance-based learning (k-nn locally weighted regression, radial basis functions). Support vector machines (linearly separable and non-linearly separable problems, kernel methods). Ensemble learning (bagging, boosting, random forests). Genetic algorithms and genetic programming. Semi-supervised learning methods. Reinforcement learning (Q-learning, temporal difference learning). Experimental evaluation of classification methods (ROC curves, cost curves). Application examples.
Course ID: 4002 Design, Development and Performance Evaluation of Next-Generation Networks ECTS: 7.5
Presentation of the most advanced network technologies and methodologies (NAT, IP multicast, WEP, ΙΕΕΕ 802.1Χ, 802.21, etc.), architectures (MPLS, DiffServ, IntServ, etc..), protocols (RSVP, Mobile IP, IPv6, OSPF, BGP, etc..) and services (WebTV, IPTV, p2p, v2v, CDN). Topics on active services with capabilities such as self-organisation, environmental intelligence and adaptation to underlying network infrastructure, spatial position awareness and multimodal interfaces exporting for costing algorithms, protection, mobility and quality of service assurance. Methods and tools for assessing performance in modern heterogeneous systems. Architectures and Internet of things services. Integrating IoT to existing network infrastructures and ROI.
Course ID: 4003 Pervasive Computing Systems ECTS: 7.5
Introduction to pervasive computing and pervasive computing systems (PCS). Context aware systems. Design issues of PCS. Architectures, programming models and frameworks. Location tracking in pervasive computing. Processing sequential sensor data. Applications from smart objects collaboration. User interfaces in pervasive computing. End-user development of IoT applications.
Course ID: 4004 Algorithms, Combinatorial Optimization and Financial Applications ECTS: 7.5
Combinatorial optimization (CO) studies algorithms that compute the optimum solution amongst the feasible solutions of a combinatorial problem. A milestone of the theory is the understanding of linear/convex problems. Combinatorial problems capture the intrinsic complexity of the most important problems for computers. Due to this, during the last 50 years CO has played a central role in exploring the power and limitations of computers. However, new problems have arisen during the current decade, due to the power of computers and the explosion of the Internet. These problems concern the independent, rational interplay of a large number of computers in the Internet, which are motivated by greedy objectives or coordinated play. These problems lie within an interdisciplinary area of research, such as CO, computer science, game theory and economic theory. An important subject is the study of bimatrix games because these essentially capture the selfish behavior of individual players. Also important is the study of selfish network flows in large-scale networks and the computation of their steady states. It is obvious that, in many situations, users’ selfish behavior can lead the Internet/system to a suboptimal state.  This clearly shows that mechanism design is a key area of study.

2nd Semester

Υποχρεωτικά Μαθήματα
Course ID: 4005 IoT Technologies and Applications ECTS: 7.5
IoT design and architectures. Abstract information models and middleware. Distributed experimental platforms for IoT testing. TVWS, energy and mobility IoT management. IoT-based business accelerators. Digital agriculture based on IoT systems. Commercial applications for IoT agriculture (e.g. FarmBeats).
Course ID: 4006 IoT Communication Technologies ECTS: 7.5
Propagation mechanisms, propagation loss models, fadings, channel characterization and impact on communications systems. Transmission and multiple access techniques, spectrum propagation techniques, CDMA, OFDM and OFDMA. Diversity techniques (SIMO and MISO systems) and spatial multiplexing (MIMO systems). IEEE 802.11 wireless local area networks, wireless ad-hoc networks and sensor networks. Low-power and low-distance protocols (Bluetooth Low Energy, Zigbee, NFC, SigFox, NB-IoT and Low-Power Wide Area), as well as long-distance ones (LTE version 12 and 13 / LTE-M2M). Relay technologies and architectures. Device-to-device (D2D), machine-to-machine (M2M) and vehicle-to-vehicle (V2V) communications and case studies.
Course ID: 4007 Embedded Systems and IoT ECTS: 7.5
The goal of this course is to familiarize students with issues concerning hardware/software design, interfacing and interaction, practical microprocessor-based system design, practical digital hardware design for embedded systems using modern logic synthesis tools, as well as with the implementation of embedded, low-power digital systems to be used as nodes of an Internet of things (IoT) type of network. More specifically, it includes: introduction to embedded systems, hardware/software interfaces, PS/2 keyboard, serial communication, USB, Ethernet, video handling, memories and their utilization in embedded systems, microprocessors, microcontrollers, FPGAs and ASICs, programming of embedded systems with OS for network applications, microprocessor/sensor interfacing, use of messaging protocols in IoT networks.
Course ID: 3008 Future Internet Security and Privacy ECTS: 7.5
Future Internet security. Foundations of information privacy. Privacy enhancing technologies. RFID technology: security and privacy protection. Sensor networks security. Cloud computing models. Risks and vulnerabilities. New security solutions. Security and privacy protection for smart environments, implantable devices and embedded systems.

3rd Semester

Compulsory Courses
Course ID: 4008 Robotics and Computer Vision ECTS: 7.5
The course includes basic elements of robotics, while it also discusses computer vision suitably adapted for robotic systems. Simplified computational vision and image processing algorithms that can run in real time on a robotic system, given the limitations and lack of precision that often exist. Students learn to design, create, plan and evaluate robotic vision systems.
Course ID: 4009 Modern Networks and IoT Interfacing ECTS: 7.5
Managing network resources in third and fourth generation broadband wireless networks (UMTS, LTE, LTE-A). Qualitative differentiation of H2H (human-to-human) and M2M (machine-to-machine) data flows. Management of inbound network load, data transmission delay, quality of service (QoS) and data flow scheduling. Fifth-generation networks and tactile Internet. Transmitting kinaesthetic and tactile feedback, fields of application and technological challenges. Innovative network resource management techniques based on network virtualization technologies (software-defined networking – SDN, network enhancement virtualization – NFV, network slicing), and network access improvement by densifying the access points and utilizing heterogeneous network technologies seamlessly.
Course ID: 4010 Semantic Web ECTS: 7.5
Introduction to the Semantic Web, vision and principles. Technologies for structured documents, data and knowledge representation (XML, RDF, RDFS, OWL). Ontology engineering and Semantic Web applications. Ontology-based access, integration and retrieval of (large volumes) heterogeneous data and knowledge (SPARQL, OBDA). Linked (big) data. Semantic Web and Internet οf things (IoT), Semantic Web of things. Semantic interoperability in IoT. Semantic modelling of trust in IoT.
Course ID: 4011 Big Data and Data Mining ECTS: 7.5
Big data and social behaviour identification, dimensionality reduction in big data, big data from web retrieval and manipulation technologies, opinion mining and sentiment analysis: sentiment classification, aspect-based opinion mining, summary creation, argument extraction, information fusion: schema preprocessing, template matching, web mining: data collection, preprocessing, data modelling. Opinion mining: sentiment classification, opinion comparison. Wrappers: instance-based wrapper learning, DOM trees and automatic creation from trees. Web crawling: general purpose crawlers, focused crawlers, local crawlers. Link analysis: social networks mining, bibliographic references matching, information retrieval algorithms. Semi-supervised learning: expectation – maximization, transduce support vector machines, mining from positive and unlabelled examples. Unsupervised learning: geometrical methods, generalized models, visualization through integration (SOMs, multidimensional scaling, and projections), collaborative filtering. Supervised learning: random forests, adaboost/bagging/boosting, Bayesian networks. Sequential mining.

4th Semester

Course ID: 4000 Msc Thesis Compulsory ECTS: 30

1st Semester

  • Pervasive Computing Systems
  • Design, Development and Performance Evaluation of Next-Generation Networks

2nd Semester

  • IoT Communication Technologies
  • Embedded Systems and IoT

3rd Semester

  • Machine Learning
  • Algorithms, Combinatorial Optimization and Financial Applications

4th Semester

  • IoT Technologies and Applications
  • Security and Privacy in Future Internet

5th Semester

(two courses)

  • Robotics and Computer Vision
  • Modern Networks and IoT Interfacing
  • Semantic Web
  • Big Data and Data Mining

6th Semester

  • MSc Thesis

7th Semester

(two courses)

  • Robotics and Computer Vision
  • Modern Networks and IoT Interfacing
  • Semantic Web
  • Big Data and Data Mining

8th Semester

  • MSc Thesis

Staff

The MSc’s courses are taught by eleven faculty members. Their academic and research profiles are briefly listed below.

Course Semester Course Instructror Webpage /
Google Scholar
Machine Learning 1 Associate Professor Efstathios Stamatatos
WEBPAGE
 
G. Scholar
Design, Development and Performance Evaluation of Next Generation Networks 1 Professor Charalampos Skianis
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G. Scholar
Pervasive Computing Systems 1 Assistant Professor Christos Gkoumopoulos
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G. Scholar
Algorithms, Combinatorial Optimization and Financial Applications 1 Assistant Professor Alexios Kaporis
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G. Scholar
IoT Technologies and Applications 2 Associate Professor Georgios Kormentzas
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G. Scholar
Embedded Systems and IoT 2 Assistant Professor Emmanouil Kalligeros
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G. Scholar
IoT Communication Technologies 2 Associate Professor Demosthenes Vouyioukas
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G. Scholar
Security and Privacy in Future Internet 2 Assistant Professor Panagiotis Rizomyliotis
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G. Scholar
Robotics and Computer Vision 3 Associate Professor Ergina Kavallieratou
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G. Scholar
Modern Networks and IoT Interfacing 3 Assistant Professor Dimitrios Skoutas
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G. Scholar
Semantic Web 3 Assistant Professor Konstantinos Kotis
WEBPAGE
 
G. Scholar
Big Data and Data Mining 3 Associate Professor Emmanouil Maragkoudakis
WEBPAGE
 
G. Scholar

Professor Charalampos Skianis

Dr Charalampos Skianis is a professor in the Department of Information and Communication Systems Engineering of the University of the Aegean. He holds a PhD in Computer Science from the University of Bradford and a BSc in Physics from the University of Patras. His current research interests include novel Internet architectures and services, cloud computing and networking, mobile and wireless networks energy management, quality of service provisioning in heterogeneous network environments. Dr Charalampos Skianis has carried out extensive research in information and communication systems performance modeling and evaluation, introducing alternative methodologies for the approximate analysis of arbitrary queuing network models. He is also interested in traffic modeling and characterization, queuing theory and traffic control of wired and wireless telecommunication systems. He has published over 100 papers relating to these research areas in international conferences, journals and edited volumes. He is an active and senior member of international organisations like IEEE, has been president of technical committees (IEEE ComSoC – CSIM, IEEE ComSoC – TCII), conferences and seminars (IEEE Globecom, IEEE ICC, IEEE CAMAD, among others), as well as a member of the editorial boards of scientific journals (IEEE Wireless Communications, IEEE Communications Magazine, IEEE Surveys & Tutorials, Ad hoc Networks, among others). He has also served as a technical manager and project coordinator for competitive European projects (ICT FP7 VITAL++, ICT FP7 HURRICANE, ICT FP7 PASSIVE, among others).

Associate Professor Demosthenes Vouyioukas

Dr Demosthenes Vouyioukas is an associate professor and the director of the Computer and Communication Systems Laboratory in the Department of Information and Communication Systems Engineering, where he had previously worked as an adjunct lecturer (since 2004) and as an assistant professor (since 2010). He is also involved in research work in the same Department, as well as in the scientific coordination of European and national programmes. He received his first degree in Electrical and Computer Engineering and his PhD in Electrical and Computer Engineering from the National Technical University of Athens (NTUA), in 1993 and 2003 respectively. In 2006, he received an MBA in Engineering-Economic Systems from the National Technical University of Athens in collaboration with the National and Kapodistrian University of Athens and the University of Piraeus. He worked as a scientific researcher (1996-2003) and a senior researcher (2003-2005) at the Mobile Radiocommunications Laboratory of NTUA, where he was involved in several European and national research and development projects. From 2005 to 2006 he worked at the Hellenic Aerospace Industry at the Department of Satellite Communications. From 2006 to 2007 he worked as an adjunct lecturer in the Department of Computer Science and Technology, University of Peloponnese. His research interests fall within the areas of digital communications and radio channel transmission techniques, and include mobile, wireless and satellite communication systems, radio resource management and broadband systems interference, wireless sensors and broadband networks, and next-generation mobile and satellite networks. He has published over 100 papers in international scientific journals, books, book chapters and international conference proceedings. Dr D. Vouyioukas is a member of the Technical Chamber of Greece, the Information and Communications Engineers Union of Greece, the Panhellenic Society of Mechanical and Electrical Engineers,  as well as member of international organisations like IEEE, ACM and IFIP. He serves as an associate editor of the international journal Telecommunication Systems (Springer) and as a reviewer and TPC member in scientific journals and conferences of international standing. He has also been a general chair and organizer at the international summer school “Emerging Architectures and Key Technologies for 5G Networks”.

Associate Professor Ergina Kavallieratou

Ergina Kavallieratou, associate professor of image processing, was born in Kefalonia in 1973. She received her Diploma in Electrical and Computer Engineering in 1996 and her PhD in Handwritten Optical Character Recognition and Document Image processing in 2000 from the Polytechnic School of the University of Patras. From 2002 to 2004 she worked as an assistant professor of audio processing in the Department of Audio and Musical Instruments Technology in the Technological Educational Institute of Ionian Islands, Greece. From 2001 to 2013 she taught at the Hellenic Open University. She has been a faculty member of the Department of Information and Communication Systems Engineering, University of the Aegean, since September 2004. She has been a visiting scholar in the Signals, Systems and Radiocommunications Laboratory of the Department of Telecommunications Engineering of the Polytechnic School of Madrid, in the Institute of Communication Acoustics of Ruhr-Universitaet Bochum, Germany, in the research institute INAOE (Mexico), in the Department of Computer Science & Engineering, Lehigh University (USA), and others. Her research interests include image processing, computer vision and robotics.

Associate Professor Georgios Kormentzas

Dr Georgios Kormentzas was born in 1973 in Nikaia, Piraeus. He holds a degree in Electrical Engineering (1995) and a PhD in Electrical and Computer Engineering from the National Technical University of Athens (2000). He has been a faculty member of the Department of Information and Communication Systems Engineering since 2002. Dr Kormentzas has also worked in the Hellenic Ministry of Agricultural Development and Food, serving as an executive director and vice-president of Greek public organisations and agencies. Along with his academic duties, he served as president of the Strategic Planning Committee at the agricultural development company GAIA ΕΠΙΧΕΙΡΕΙΝ S.A. during the years 2014-2016. Utilizing his technical know-how on Common Agricultural Policy issues, he has been a member of a number of EU and COPA-COGECA committees and workgroups. He has published a large number of papers in journals (50 publications) and international conference proceedings (over 100 publications), while his work has achieved significant recognition by peers, with over 1,700 citations.

Associate Professor Emmanouil Maragkoudakis

Emmanouil Maragkoudakis is an associate professor of data mining at the Department of Information and Communication Systems Engineering of the University of the Aegean and a member of the Artificial Intelligence lab at the same Department. He has received his Diploma in Computer Science, University of Crete, and his PhD in Electrical and Computer Engineering , University of Patras (PhD thesis: Reasoning Under Uncertainty in Dialogue and Other Natural Language Systems Using Bayesian Network Techniques). His research interests lie in Bayes networks, data mining, privacy-preserving data mining, machine learning and user modeling. He has published 95 peer-reviewed papers in international scientific journals and conferences. He has worked in more than 10 European research programmes and more than 20 national programmes. He collaborates with a great number of research journals, serving as a member of their editorial committees, as well as a guest editor and reviewer. He has also been a TPC member of more than 50 international conferences on artificial intelligence.

Associate Professor Efstathios Stamatatos

Dr Efstathios Stamatatos holds a Diploma in Electrical Engineering (1994) and a PhD in Electrical and Computer Engineering (2000), University of Patras. He worked in the Polytechnic University of Madrid (1998) as a visiting researcher, in the Austrian Research Institute for Artificial Intelligence as a post-doc researcher (2001-2002) and in the Technical Educational Institute of Ionian Islands as an adjunct professor (2002-2004). He has been a faculty member of the Department of Information and Communication Systems Engineering of the University of the Aegean since 2004. His research interests include text mining, natural language processing, intelligent information retrieval and machine learning. He is the director of the Artificial Intelligence and the Decision Support labs of the University of the Aegean, has participated in a number of EU-funded research programmes and has co-hosted international competitions on plagiarism detection and author identification.

Tenured Assistant Professor Emmanouil Kalligeros

Dr Emmanouil Kalligeros holds a Diploma in Computer Engineering and Informatics (1999), an MSc in Computer Science and Technology (2001) and a PhD in Embedded Testing Techniques for Digital Circuits, University of Patras. From 2006 to 2008 he worked as an adjunct lecturer at the University of Patras, the University of Peloponnese and the University of the Aegean. He has been a faculty member of the Department of Information and Communication Systems Engineering of the University of the Aegean since 2008. His research interests lie in digital circuits and systems design, testing and security. He has published 39 papers in high-profile international journals and conferences, while he has also co-authored one book. Dr Kalligeros has had extensive teaching background and, in June 2015, he received the Teaching Excellency Award from the School of Sciences of the University of the Aegean. Since December 2016, he has been a fellow coordinator of the University of the Aegean’s collaborations with the computing and microelectronics departments of CERN. Dr Kalligeros is also a member of IEEE and the Technical Chamber of Greece.

Tenured Assistant Professor Alexios Kaporis

Dr Alexios Kaporis holds a degree in Mathematics and a PhD in Threshold Phenomena in Combinatorial Problems, University of Patras. His research interests lie in algorithm analysis, dynamic data structures, algorithmic game theory and bioinformatics.

Tenured Assistant Professor Panagiotis Rizomyliotis

Dr Panagiotis Rizomyliotis is a tenured assistant professor in the Department of Information and Communication Systems Engineering of the University of the Aegean and a full member of the Hellenic Authority for Communication Security and Privacy. He received a BSc in Informatics with honours in 1997 and an MSc in Radioelectrical Engineering in 1999 from the National and Kapodistrian University of Athens. He has worked as a postdoctoral researcher in the security and cryptography lab COSIC in Katholieke Universiteit Leuven, Belgium. He has written more than 50 papers on future Internet security (Internet of things, cloud computing) and cryptography, which were published in scientific journals, conferences and edited volumes. He has also participated in a great number of national and European research projects on systems security and privacy protection, serving as a technical manager or researcher.

Assistant Professor Christos Gkoumopoulos

Dr Christos Gkoumopoulos has been an assistant professor of pervasive computing systems (PCS) at the Department of Information and Communication Systems Engineering, University of the Aegean, since May 2015. He is also a member of the Artificial Intelligence and the Computers and Communication Systems laboratories at the same Department. He holds a Diploma in Computer Engineering and Informatics and a PhD in Electrical and Computer Engineering, University of Patras. He has taken part in a large number of national and European research projects (NSRF, ESPRIT, IST/FET, FP7 and H2020) since 1994, either as a scientific associate or as a project and work packages coordinator. His most recent project, for which he joined LEADERA ELTAB as a project coordinator, involved e-health applications for the welfare of vulnerable population groups. He has been a founding member and project management coordinator in the company ΛΥΣΕΙΣ S.A., a University of Patras spin-off, founded in 1998. He has also been teaching the postgraduate course Pervasive and Mobile Computing Systems at the Hellenic Open University since 2010. Dr Gkoumopoulos’s research interests include PCS architectures, PCS design and programming, programming models and frameworks, knowledge modelling and ambient assisted living systems. He has published more than 60 papers in international scientific journals and conference proceedings (IEEE, ACM, Elsevier, Springer, etc.). His work has more than 580 citations, with an h-index of 15. He has organized scientific meetings and has been a reviewer in international journals and conferences.

Assistant Professor Dimitrios Skoutas

Dr Dimitrios Skoutas holds a Diploma in Electrical and Computer Engineering from the University of Patras (2000) and a PhD in Communication Networks from the Department of Information and Communication Systems Engineering, University of the Aegean (2005). In 2006 his PhD thesis received an award from the Ericsson Awards of Excellence in Telecommunications. From 2000 to 2003 he worked as an adjunct lecturer in the Department of Information and Communication Systems Engineering, University of the Aegean, and since 2003 he has been a senior member of laboratory teaching staff at the Computer and Communication Systems Laboratory (CCSL) of the same Department. His research interests lie in optimal resource management and QoS provisioning in homogeneous and heterogeneous networks. Within this research framework, he has proposed several algorithmic and architectural optimizations, while an important part of his research has taken place within European and national research and development projects. He has published 17 papers in international scientific journals and 27 papers in international conference proceedings. Dr D. Skoutas is a member of the Technical Chamber of Greece, the Information and Communications Engineers Union of Greece, a senior member of IEEE, as well as an associate editor in three international scientific journals (Wireless Networks – Springer, EURASIP Journal on Wireless Communications and Networking – Springer, Internet Technology Letters -John Wiley & Sons, Ltd.). He also serves as a TPC member in conferences of international standing.

Fees and Funding

Successful applicants for the postgraduate studies programme are required to pay tuition fees, in accordance with Article 35 of Law 4485/2017. The tuition fees amount to €3,000 and can be paid in four installments. The tuition fees cover operational expenses of the postgraduate programme of studies, including needs in specialist teaching staff from universities in Greece or abroad.

Tuition fees payment can be made as follows: €500 within 15 days after the student’s application has been accepted, €1,000 upon the student’s admission to the 1st semester of studies (early October), €1,000 at the beginning of the second semester (February) and €500 upon the student’s admission to the 3rd semester of studies. No refunds can be given for fees or part of fees that have already been paid.

The postgraduate studies programme may offer a number of grants, conditional on academic performance, to full-time students. The amount of funding, requirements, method of funding, as well as the rights and responsibilities of grant-holders are decided by the Department’s Assembly (par. 4, Article 35 of Law 4485/2017).

Full-time/part-time study

The full-time study programme is completed in four academic semesters and combines blended and model types of learning, including: [a] a four-day intensive lecture cycle held at the Department’s premises at the beginning or the end of every academic semester (October, January, June), [b] an online learning environment that supports the learning process during the first three semesters. The fourth semester is reserved for the completion of the MSc thesis. Class attendance and participation in any educational activity, such as projects, assignments, etc., is compulsory.

The full-time study programme is completed in four academic semesters, including the writing of the thesis. The maximum permissible time for the completion of the full-time programme is eight semesters.

Working students may choose to study part-time. Working students have to prove that they work at least 25 hours per week and provide a work contract or certificate. Part-time study is also suitable for non-working students who cannot meet the demands of studying full-time, due to health or family issues, military service, or other personal reasons. Those students should send a written request to the Department’s Assembly before the start of the MSc programme. The duration of the part-time study programme must be no longer than eight academic semesters.

How to Apply

Applicants are required to fill in a candidacy application form, attaching the following documents:

  • A copy of their ID or passport
  • A CV
  • A copy of their degree/diploma or a certificate of studies completion
  • Peer-reviewed publications, if there are any
  • Certificates of professional or research activities, if there are any
  • Two references
  • A copy of the candidate’s undergraduate dissertation or its title and abstract if it has not been completed; in case the candidate was not required to write a dissertation during their undergraduate studies, they should mention so in writing
  • Proof of English language competency equivalent to or higher than B2 level (according to the Common European Framework of Reference for Languages)
  • Any other document that the candidate believes it might support their application

The application and all digital copies of documents must be submitted online on the “Nautilus” platform (https://nautilus.aegean.gr/). Hard copies can be submitted in person during admission.

Download the updated Regulations of Studies for the postgraduate programme of studies (in Greek):

Κανονισμός Σπουδών – ΠΜΣ Διαδίκτυο των Πραγμάτων

Download articles for the postgraduate programme’s interviews:

Articles – MSc Internet of Things

Course Schedule – Fall Semester

1st Semester

1st week of face-to-face courses:
Room Lydia

Monday 30/09
9:00 – 13:00: Design, Development and Performance Evaluation of Next Generation Networks (Charalampos Skianis)
14:00-18:00: Machine Learning (Efstathios Stamatatos)

Tuesday 1/10
9:00 – 13:00: Algorithms, Combinatorial Optimization and Financial Applications (Alexios Kaporis)
14:00-18:00: Pervasive Computing Systems (Christos Gkoumopoulos)

Following Weeks:

Hours: 18:00 – 20:00

Monday: Design, Development and Performance Evaluation of Next Generation Networks
Tuesday: Pervasive Computing Systems
Wednesday: Algorithms, Combinatorial Optimization and Financial Applications
Thursday: Machine Learning

3rd Semester

1st week of face-to-face courses:

Monday 30/09
9:00 – 13:00: Modern Networks and IoT Interfacing (Dimitrios Skoutas)
14:00-18:00: Robotics and Computer Vision (Ergina Kavallieratou)

Tuesday 1/10
9:00 – 13:00: Big Data and Data Mining (Emmanouil Maragkoudakis)
14:00-18:00: Semantic Web (Konstantinos Kotis)

Following Weeks:

Hours: 18:00 – 20:00

Tuesday: Robotics and Computer Vision
Wednesday: Big Data and Data Mining
Thursday: Semantic Web
Friday: Modern Networks and IoT Interfacing

Fall Semester
1 30/09-4/10/2019 Face-to-face
2 7-11/10/2019 No classes
3 14-18/10/2019
4 21-25/10/2019
5 28/10 – 1/11/2019 No classes
6 4-8/11/2019
7 11-15/11/2019
8 18-22/11/2019
9 25-29/11/2019 No classes
10 2-6/12/2019
11 9-13/12/2019
12 16-20/12/2019 No classes
13 6-10/1/2020
14 13-17/1/2020 Week of subtitutions

Fall Semester Holidays

Public holiday 28/10/2019
Public holiday 17/11/2019
Christmas Holidays 22/12/2019 – 6/1/2020
Public holiday 30/1/2020

SUCCESS STORIES

The MSc Internet of Things enabled me to broaden my horizons, acquire specialist knowledge, become familiar with future technologies and gain skills that are crucial for my personal and professional development. It has been a very important and unique experience, and four semesters filled with a lot of work and pressure, but also joy and new information. I’ve had an outstanding collaboration with the University’s academic staff, which yielded excellent results.

Nikolaos Tsourelis, Network Team Manager, Cosmote

As an adjunct scholar of the MSc programme, I had the chance to participate in teaching activities alongside the academic staff, in the organisation of high-calibre scientific conferences (IEEE CAMAD) and summer schools (AegeanNetCom), as well as in research fields that contributed to my academic development. This experience, combined with the constant support of my supervisor professors, paved the way for my active involvement as a researcher in the fields of telecommunication systems and indoor positioning, publishing four papers in esteemed scientific journals and conferences.

Eleni Mpogdani, Radio Engineer, Special Coverage & Business Customers, Victus Networks

The MSc Internet of Things provided me with the necessary scientific foundation for a broad range of A.I. fields; natural language processing and machine learning, in particular, were the fields that caught my interest. The programme’s demanding requirements regarding workload and research study boosted the development of my research skills and were the main reason I decided to further my academic studies as a research assistant in Idiap Research Institute and as a PhD candidate in École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland.

Nikos Pappas, PhD Candidate EPFL

The MSc programme helped me come into contact with new technologies and their practical applications. What was most important, however, was getting used to the fast and demanding learning pace at a truly high academic level, as well as trying my hand at doing research for the first time. The MSc studies gave me the necessary skills to meet the new challenges I was going to face as a novice engineer and researcher in an international environment.

Sokratis Vavylis, TU/e Researcher

The MSc gave me the appropriate boost and confidence to seek a better opportunity for myself and my family. The in-depth development of my skills and knowledge, made possible by the assistance and guidance of the academic staff, enabled me to set the bar high and find employment as an analyst/developer overseas. I am positive that the skills I have acquired will contribute to a continuous career development.

Vasilis Verras, Analyst / Developer

Course assignments combined originality with a theoretical and technical know-how, offering a great motivation for the best possible outcome. As soon as I started writing my thesis, I had the chance to collaborate with international research groups. Most importantly, however, the MSc programme helped me understand new technologies in depth and taught me the way to implement such technologies to solve problems and, therefore, contribute to research and creation of new knowledge.

Giorgos Santipantakis, PhD Candidate

My active involvement in large-scale research projects and the personal contact with collaborators from different European countries and different kinds of research organisations (e.g. research institutes, universities, multinational companies, small and medium-sized enterprises) gave me the chance to upgrade my job skills and, most importantly, to make the most of the knowledge I acquired in the long run.

Prodromos Makris, ICSD PhD Student

My studies at the University of the Aegean brought me closer to the latest developments in the IT sector. What is more, the research experience of the teaching staff inspired me to pursue a PhD in the ICSD Department. Summing up, my studies in Samos not only helped me build my profile as an engineer, but also provided me with invaluable partnerships for my future research and professional career.

Dr Nikos Nomikos, Research Associate, University of the Aegean