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Demetris Trihinas

Full-Time Lecturer
Department of Computer Science, University of Nicosia

Senior Researcher
Department of Computer Science, University of Cyprus



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Hello World

I’m currently a Full-Time Lecturer at the Department of Computer Science, University of Nicosia and senior member of the Artificial Intelligence Lab.

Previously, I was a Postdoctoral Fellow at the Department of Computer Science, University of Cyprus and Senior Researcher at the Laboratory for Internet Computing.

My research interests include Data-Intensive Computing with particular focus in Geo-Distributed Big Data Management, Data Visualization and Data Mining over Cloud, IoT and Edge Computing topologies.

My PhD dissertation targeted developing low-cost probabilistic and adaptive learning models for approximate monitoring in order to improve energy- efficiency and reduce both the volume and velocity of data generated and consumed by IoT services. For the research conducted during my doctoral studies, I was selected by the Heidelberg Laureate Forum as one of the 100 young promising researchers in Computer Science for 2015.

I am currently the Project Coordinator of the FlockAI project. FlockAI aims to deliver a framework capable of enabling Machine Learning and its applications to drone technology for handling time-critical missions. Specifically, FlockAI will advance the current research plain by developing innovative AI-enabled self-adaptive algorithms to ease energy consumption and improve data delivery timeliness in drone swarms.

I am also contributing as a Work Package Leader (Data Management for Fog Services) to the RAINBOW H2020 EU co-funded project. RAINBOW aims to develop an open and trusted fog computing platform that facilitates the deployment of scalable and heterogeneous IoT services by pushing orchestration and data management intelligence to the network “edge” while also ensuring security and privacy primitives across the device- fog-cloud-application stack.

I've also worked on other cool projects which you can take at look at here.

News

With Dr. Lauritz Thamsen (University of Glasgow) and Dr. David Bermbach (Technical University of Berlin), we are looking for papers for a special issue of Wiley's SPE journal on Benchmarking, Experimentation Tools, and Reproducible Practices for Data-Intensive Systems from Edge to Cloud. Submissions are due February 28.

Best Paper award at IEEE ISCC 2022 for our paper entitled "BenchPilot: Repeatable and Reproducible Benchmarking for Edge Micro-DCs".

Best Paper award at IEEE/ACM IoTDi 2022 for out paper entitled "5g-slicer: An emulator for mobile iot applications deployed over 5g network slices"

About Me

  • Demetris Trihinas
  • July 05, 1987
  • trihinas.d{at}unic.ac.cy
  • +357 22841792
  • B114

Positions

Open job posting for a Researcher in the area of Big Data processing for geo-distributed environments (Ref: CSAI11/22). For more information please contact me.

Open job posting for a Reasearcher in the area of Machine Learning for Drone Swarms (Ref: CSAI06/20). For more information, see the detailed job posting here.

Open job posting for a Reasearcher in the area of Machine Learning for Smart Cities (Ref: CSAI11/19). For more information, see the detailed job posting here.

The ailab is currently searching for motivated PhD candidates to work on Data Science, AI and Big Data Management projects. We also have a wide gamma of BSc/MSc projects. For more information, contact me.

Code Repos

profile for dtrihinas at Stack Overflow, Q&A for professional and enthusiast programmers

Education

  • PhD in Computer Science 2015 - 2017
    University of Cyprus

    Qualification: PhD

    Doctoral Thesis is entitled Low-Cost Approximate and Adaptive Monitoring Techniques

    Thesis Advisor: Dr. George Pallis and Dr. Marios D. Dikaiakos

  • MSc in Computer Science and Internet Computing 2013 - 2014
    University of Cyprus

    Qualification: MSc

    Graduated top of my class

    Master Thesis is entitled "Monitoring Elastically Adaptive Cloud Services"
    Thesis Advisor: Dr. George Pallis and Dr. Marios D. Dikaiakos

  • Dipl.-Ing. in Electrical and Computer Engineering2007 - 2012
    National Technical University of Athens (NTUA)

    Qualification: Dipl.-Ing. (5-year-degree, MEng equiv.)

    Grade: 8/10

    Diploma Thesis is entitled "Research and Development of a Web Service for Monitoring Storage Clouds", grade 10/10
    Thesis Advisor: Dr. Theodora Varvarigou



Academic Employment

  • Full-Time Faculty (Rank Lecturer)Sep. 2018 - current date
    Department of Computer Science - University of Nicosia
    Specialization: Big Data Management and Processing
    Senior member of the Artificial Intelligence Lab.

  • Postdoctoral ResearcherNov. 2017 - current date
    Laboratory for Internet Computing - University of Cyprus

  • Visiting Teaching Staff (Adjunct Lecturer)Jan. 2018 - Jun. 2018
    Department of Computer Science - University of Cyprus

  • ResearcherNov. 2012 - Oct. 2017
    Department of Computer Science - University of Cyprus

  • ResearcherJun. 2011 - Apr. 2012
    Distributed Knowledge and Media Systems Group - National Technical University of Athens (NTUA)

Honors and Awards

  • Best Paper Award at IEEE ISCC 20222022
    BenchPilot: Repeatable & Reproducible Benchmarking for Edge Micro-DCs

  • Best Paper Award at IEEE/ACM IoTDi 20222022
    5G-Slicer: An emulator for mobile IoT applications deployed over 5G network slices

  • Best Demo Award at IEEE/ACM SEC 20202020
    Emulating Geo-Distributed Fog Services

  • First Place - People’s Award for Research at the Fourth Innovation and Entrepreneurship Forum Cyprus (IEF 2019) 2019
    “StreamSight, a query-driven framework for modelling and extracting analytic insights from IoT services”.

  • NSF Student Travel Grant AwardNov 2015
    Selected among top PhD researchers for a travel grant for the IEEE Big Data Conference 2015

  • Heidelberg Laureate ForumAug 2015
    Selected as one of the top 100 young researchers in the field Computer Science: “Adaptive Learning Models for Heterogeneous Cloud and IoT Services”.

  • Best Post-Graduate Student AwardJan 2013 - Jun 2015
    School of Pure and Applied Sciences, University of Cyprus.

  • Best Paper Award2014
    For the paper entitled “ADVISE – a Framework for Evaluating Cloud Service Elasticity Behavior" at the 12th International Conference on Service Oriented Computing (ICSOC 2014), full paper acceptance rate 15%.

  • UNICA Oct 2014
    Selected as a delegate to represent the University of Cyprus at the Unica Student Conference 2014

Download My Resume (Aug 2019)

Publications from Demetris Trihinas

Several papers are available for download. By following these links you agree to respect the copyrights of the papers.

The papers obtained from this Web page are included by the contributing authors as a means to ensure timely dissemination of scholarly and technical work on a non-commercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Oct. 2020 - To Date

FlockAI: An AI Enabled Framework to Boost Drone Swarm Autonomy

The aim of the FlockAI project is to deliver a framework capable of enabling Machine Learning and its applications to drone technology for handling time-critical missions (e.g., search and rescue missions). Specifically, FlockAI will advance the current research plain by developing innovative AI-enabled self-adaptive algorithms to ease energy consumption and improve data delivery timeliness in drone swarms. To achieve these goals, the FlockAI project will explore the use of various power-efficient machine learning models for dynamically adjusting, in place, the data sensing and routing of data over drone swarms while maintaining mission requirements. The methods delivered by the project will be placed in a modular and reusable framework for drone swarm operation.

Read more →

Jan. 2020 - To Date

Fogify: A Fog Computing Emulator Framework

Fogify is an emulation Framework easing the modeling, deployment and experimentation of fog testbeds. Fogify provides a toolset to: model complex fog topologies comprised of heterogeneous resources, network capabilities and QoS criteria; deploy the modelled configuration and services using popular containerized infrastructure-as-code descriptions to a cloud or local environment; experiment, measure and evaluate the deployment by injecting faults and adapting the configuration at runtime to test different "what-if" scenarios that reveal the limitations of a service before introduced to the public.

Read more →

Jan. 2020 - Dec. 2022

RAINBOW - an open and trusted fog computing platform

The vision of RAINBOW is to design and develop an open and trusted fog computing platform that facilitates the deployment and management of scalable, heterogeneous and secure IoT services and cross-cloud applications (i.e., microservices). RAINBOW falls within the bigger vision of delivering a platform enabling users to remotely control the infrastructure that is running, potentially, on hundreds of edge devices (e.g., wearables), thousands of fog nodes in a factory building or flying in the sky (e.g., drones), and millions of vehicles travelling in a certain area or across Europe. RAINBOW aspires to enable fog computing to reach its true potential by providing the deployment, orchestration, network fabric and data management for scalable and secure edge applications, addressing the need to timely process the ever-increasing amount of data continuously gathered from heterogeneous IoT devices and appliances. Our solution will provide significant benefits for popular cloud platforms, fog middleware, and distributed data management engines, and will extend the open-source ecosystem by pushing intelligence to the network edge while also ensuring security and privacy primitives across the device-fog-cloud-application stack. To evaluate its wide applicability, RAINBOW will be demonstrated in various real world and demanding scenarios, such as automated manufacturing (Industry 4.0), connected vehicles and critical infrastructure surveillance with drones. These application areas are safety-critical and demanding; requiring guaranteed extra-functional properties, including real-time responsiveness, availability, data freshness, efficient data protection and management, energy-efficiency and industry-specific security standards.

Read more →

Jan. 2017 - Dec. 2019

Unicorn - secure and elastic –by design– multi-cloud micro-services

Unicorn aims to simplify the design, deployment and management of secure and elastic –by design– multi-cloud services. This will be achieved by enabling continuous orchestration and automatic optimization of portable and dynamic cloud services running on virtual instances or micro-execution containers for increased security, data protection privacy and vast resource (de)-allocation.

Read more →

Oct. 2016 - Dec. 2018

AdaM - The Adaptive Monitoring Framework

A monitoring framework that reduces data volume and battery consumption of your IoT devices. AdaM uses re-enforcement and probabilistic learning to follow the evolution of the collected monitoring stream in order to adapt the rate at which monitoring metrics are collected.

Read more →

Nov. 2014 - Oct. 2017

PaaSport - A Semantically-enhanced Marketplace of Interoperable Platform-as-a-Service offerings

The vision of the PaaSport project is to resolve the application portability issues that exist in the Cloud PaaS market through a flexible and efficient deployment and migration approach. To this end, PaaSport will combine Cloud PaaS technologies with lightweight semantics in order to specify and deliver a thin, non-intrusive Cloud-broker (in the form of a Cloud PaaS Marketplace), to implement the enabling tools and technologies, and to deploy fully operational prototypes and large-scale demonstrators.

Read more →

Oct. 2012 - Sep. 2015

CELAR - Cloud ELasticity pRovisioning

Auto Scaling Resources is one of the top obstacles and opportunities for cloud computing: consumers can minimize the execution time of their tasks without exceeding a given budget. Cloud providers maximise their financial gain while keeping their customers satisfied and minimizing administrative costs. Many systems claim to offer adaptive elasticity, yet the “throttling” is usually performed manually, requiring the user to figure out the proper scaling conditions. In order to harvest the benefits of elastic provisioning, it is imperative that it be performed in an automated, fully customizable manner. CELAR delivers a fully automated and highly customisable system for elastic provisioning of resources in cloud computing platforms.

Read more →

January 2014

JCatascopia Cloud Monitoring System

JCatascopia is a fully automated, multi-layer, interoperable Cloud Monitoring System suitable for monitoring elastically adaptive Cloud applications. JCatascopia can be utilized to collect monitoring metrics from multiple level of the underlying Cloud infrastructure as well as performance metrics from Cloud applications and subsequently distribute them to subscribed users and platform operators. JCatascopia is enhanced with a metric subscription rule mechanism where application developers can subscribe to aggregated metrics and also compose high-level metrics from low-level metrics. Users and platform operators can monitor the performance of their applications and the underlying platform by accessing metrics through the JCatascopia RESTful API or via the JCatascopia web interface which generates for each metric real-time graphs.

Read more →

CELAR - Cloud ELasticity pRovisioning

Auto Scaling Resources is one of the top obstacles and opportunities for cloud computing: consumers can minimize the execution time of their tasks without exceeding a given budget. Cloud providers maximise their financial gain while keeping their customers satisfied and minimizing administrative costs. Many systems claim to offer adaptive elasticity, yet the “throttling” is usually performed manually, requiring the user to figure out the proper scaling conditions. In order to harvest the benefits of elastic provisioning, it is imperative that it be performed in an automated, fully customizable manner. CELAR delivers a fully automated and highly customisable system for elastic provisioning of resources in cloud computing platforms.

#CELAR #elasticity #Cloud

October 2012

→ ← ← All Posts

JCatascopia Cloud Monitoring System

JCatascopia is a fully automated, multi-layer, interoperable Cloud Monitoring System suitable for monitoring elastically adaptive Cloud applications. JCatascopia can be utilized to collect monitoring metrics from multiple level of the underlying Cloud infrastructure as well as performance metrics from Cloud applications and subsequently distribute them to subscribed users and platform operators. JCatascopia is enhanced with a metric subscription rule mechanism where application developers can subscribe to aggregated metrics and also compose high-level metrics from low-level metrics. Users and platform operators can monitor the performance of their applications and the underlying platform by accessing metrics through the JCatascopia RESTful API or via the JCatascopia web interface which generates for each metric real-time graphs.

#Cloud Monitoring #JCatascopia #Elasticity

January 2014

→ ← ← All Posts

Courses Taught: Academic Year 2022-2023

Fall Semester

COMP-116: Software Development Lab I, BSc in Computer Science, since 2018
COMP-140: Introduction to Data Science, BSc in Data Science, since 2020
COMP-240: Data Programming, BSc in Data Science, since 2021

Spring Semester

COMP-140: Introduction to Data Science, BSc in Data Science, since 2020
COMP-340, Big Data, BSc in Data Science/BSc in Computer Science (elective), new course!!!
COMP-370: Algorithms, BSc in Computer Science, since 2019

DL Mode

COMP-543DL: Managing and Visualizing Data, MSc in Data Science, since 2021
COMP-548DL: Big Data Management and Processing, MSc in Data Science, since 2021

Note: COMP-543DL and COMP-548DL are supported by the Google Cloud Platform (GCP) by graciously offering it’s Students with free credits, interactive labs and online teaching resources.

Taught in the Past

COMP-111: Programming Principles I, BSc in Computer Science, 2018-2020

Contact Info

  • Department of Computer Science School of Sciences and Engineering 46 Makedonitissas Avenue, CY-2417 P.O.Box 24005, CY-1700, Nicosia, Cyprus
  • M118D
  • trihinas.d{at}unic.ac.cy
  • +357 2284-1792
  • dtrihinas

Keep In Touch

On The Map

Introduction

Hello! Here, you'll understand how we projected this theme. Read all the text to know any details about Metroid vCard Template. It's a powerfull personal page to start your web life, because it's simple, fast, animated, beautiful, colorful and it brings many possibilities!

Exclusive Grid System

.col .c1

.col .c2-1 .first

.col .c2-1

.col .c3-1 .first

.col .c3-1

.col .c3-1

.col .c3-1 .first

.col .c3-2

Creating new pages

Is it easy to do?

A: Yes, simply add a <section class="content"> into the <div id="page"></div> and create a tag link with the (class="menu").

See the example:
<a href="#blog" id="blog" class="menu">Blog Link</a>

<div id="page">
  <section id="blog-page" class="content">
    <div class="inner">
      ...page content
    </div>
  </section>
</div>

Changing the content

Metroid was designed to be simple to use and customize. Here's how easy it is to use it.

How to change the text of my site?

A: Everything that is displayed on the screen, whether text, form boxes, portfolio or progress bars, are written in a single file named "index.html". The screen changes are simulated by script calls, so our theme is considered Onepage.

How to change profile picture?

A: Go to the folder "img/profile/" and replace the file "photo.jpg". We recommend that you use a square photo with 245x245 pixels.

Note : We recommend that you use the same sizes as the profile pictures and blog to keep the layout is appropriate in all resolutions (screen, tablet and mobile).

Icons | Credits: Font Awesome (https://fortawesome.github.io/Font-Awesome/)

Changing the style

The Metroid comes with predefined CSS files with 10 different colors in different color tones. In addition, we selected 20 patterns to choose as background.
Patterns | Credits: Subtle Patterns (https://subtlepatterns.com/)

How to do?

A: Just choose the color and pattern you want and change the CSS call into index.html file on line 32. To configure the desired pattern go to the folder "img/bg/" and see the numbering pattern to set the line 54 into index.html.

See the example:
Line 32: <link rel="stylesheet" type="text/css" href="css/colors/color-name.css" id="color" />
Change to name of color.

Line 54: <body class="bg01">
Change from '01' to '20'.

Can I set up my colors in the theme?

A: Yes, simply access the file "custom.css", include your colors there, comment out the line 32 and uncomment line 33.

Typography

Metroid used fonts from Google Fonts. There are amazing font styles in Google Font that you can choose. So, you can choose the better font to you, and apply in your new website. We are using the font "Ubuntu" in all Metroid's pages. Enjoy and customize!

Use simple tags to create your headers, texts and lists.

Headers

<h1>Title<h1>
<h2>Title<h2>
<h3>Title<h3>
<h4>Title<h4>
<h5>Title<h5>
<h6>Title<h6>

Texts

<p>Paragraph<p>
<label>Label<label>
<span>Span<span>
<code>Code<code>
<pre>Pre<pre>
<a>Anchor<a>

Lists

<ul>
<li>item</li>
<li>item</li>
<li>item</li>
<li>item</li>
</ul>

Need Support

Still have questions?

Well, Thanks so much for purchased our items! We’re really appreciated it and hope you enjoy it! If you need support, you can leave your questions or doubts in comments area of the item. We usually get back to you within 2-12hours (except holiday seasons which might take longer).

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