Our Team
Our team consists of highly-motivated, dedicated and passionate people, with years of experience in research and development.
Welcome to the Intelligent Systems Laboratory
[ Research Areas ] – [ Current Research ] – [ Meet Us ] – [ Conferences and Special Issues] – [ Campaigns ] – [ Strategic Alliances ]
The Intelligent Systems Laboratory is part of the Department of Computer Science of the Neapolis University of Pafos, Cyprus. The laboratory aims to develop solutions to a variety of different everyday problems, as well as push forward the informatics industry.
Our main focus is the development and advancement of disruptive technologies, such as Robotics, Internet of Things(IoT), Machine Learning, Computer Vision and Blockchain. We are interested in the design and control of systems that autonomously adapt to different situations and cope with our uncertain and dynamic daily environment. In search of clever solutions, we take inspiration from humans and animals with the goal to improve the skills and autonomy of complex systems. We are driven by the immense challenges faced by robots with imperfect sensors and incomplete knowledge of the world operating in unstructured environments.
Research Areas
Computer Vision & Robotics
One of the major objectives of the Group focuses on interdisciplinary research applied to the state of the art autonomous intelligent robotics and human-robot interaction.
We research several topics related to learning in computer vision. Our current focus is on visual localization and mapping (V-SLAM), image retrieval techniques and educational robotics.
Internet of Things
The main research activity of the Internet of Things team focuses on wireless communication in the Internet of Things. More specifically, we are working on the communication challenges of Low Power Wide Area Networks (LPWAN).
Our latest research includes mobility support and connectivity of mobile things in LoRaWAN.
Blockchain
The Blockchain team of the ISL focuses on studying the innovative concepts leveraged by this newly emerged technology and by its new application-driven directions. The main research activity of the team focuses on designing and developing special-purpose decentralized applications (dApps).
Some of our works include Parkchain, RandomBlocks, Logistics, etc.
Current Research
ITSO: A novel Inverse Transform Sampling-based Optimization algorithm for stochastic search
Optimization algorithms appear in the core calculations of numerous Artificial Intelligence (AI) and Machine Learning methods, as well as Engineering and Business applications. Following recent works on the theoretical deficiencies of AI, a rigor context for the optimization problem of a black-box objective function is developed. The algorithm stems directly from the theory of probability, instead of a presumed inspiration, thus the convergence properties of the proposed methodology are inherently stable. [Read More]
A Gradient Free Neural Network Framework Based on Universal Approximation Theorem
This paper presents a numerical scheme for the computation of Artificial Neural Networks’ weights, without a laborious iterative procedure. The proposed algorithm adheres to the underlying theory, is highly fast, and results in remarkably low errors when applied for regression and classification of complex data-sets, such as the Griewank function of multiple variables x∈R^100 with random noise addition, and MNIST database for handwritten digits recognition, with 7×10^4 images. [Read More]
The Lagrangian remainder of Taylor’s series distinguishes O(f(x)) time complexities to polynomials or not
The purpose of this letter is to investigate the time complexity consequences of the truncated Taylor series, known as Taylor Polynomials. In particular, it is demonstrated that the examination of P=NP equality, is associated with the determination of whether the n^th derivative of a particular solution is bounded or not. Accordingly, in some cases, this is not true, and hence in general. [Read More]
Meet the Team and the Lab
Be a student for a day
Would you like to know more about a Department of Computer Science, Neapolis University and Intelligent Systems Laboratory? Department of Computer Science & Intelligent Systems Lab offers the possibility to be a student for a day. Experience what it is like to study at Neapolis University!
Invite us to your school
The Intelligent Systems Laboratory provides talks to schools in Cyprus in order to challenge stale thinking and stimulate debate and to inspire students to be more ambitious in developing and pursuing their academic passions. Subjects: Robotics, and Artificial Intelligence.
Conferences and Special Issues
International Conference on Distributed Computing in Sensor Systems (DCOSS 2021)
The conference will take place at the Coral Beach Hotel on 07-09 June 2021, with the participation of eminent scientists from around the world.
Intelligent Systems for the Internet of Things
The ISIoT workshop aims at bringing together researchers and practitioners designing and deploying systems that apply intelligent technologies in IoT.
Special Issue “Recent Trends in Multi-Robot Systems: From Theoretical Contributions to Practical Applications“
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section “Systems & Control Engineering“. Deadline for manuscript submissions: 30 June 2020.
Campaigns we Support
Remove one image to make millions of women feel welcome in tech.
We believe that an effective society is one in which all members benefit and offer equally in technology. The evolution of technology requires diversity. The momentum of learning the technology does not need unintended biases of the past like Lena, but requires creativity, perseverance, patience, perfection, traits that every woman possesses. Let’s change the perception by giving the challenge to every woman programmer to show that computer science isn’t just the physics of how a transistor works or how code runs, but the need to understand that if we all work on science together, it’s going to be robust, broader, better, and more thorough than anything men can do themselves.
Strategic Academic Alliances
