Theodoros Panagiotis Chatzinikolaou

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• Engineering Diploma with Integrated Master (M.Eng.)
• PhD Candidate at Democritus University of Thrace

The use of Cellular Automata (CA) in combination with Learning Automata (LA) has demonstrated effectiveness in handling hard-to-be-solved problems. Due to their capacity to learn and adapt, as well as their inherent parallelism, they can expedite the problem-solving process for a range of problems, such as challenging logic puzzles. One such puzzle...

Towards achieving efficient computational approaches, the perspective of Cellular Automata (CAs) appears to be highly potent, owing to its performance hidden in the parallel computing capabilities inherent in its local units, known as cells. Through their local interconnections and adherence to fixed or dynamic rules, these cells demonstrate except...

Computing demands are growing rapidly as bigdata and artificial intelligence applications become increasingly tasking. Bio-inspired and quantum-based techniques are proving to be quite promising for the development of novel circuits and systems. These systems can contribute to the resolution of a wider variety of problems while also providing impro...

One of the most enticing candidates for next-generation computing systems is the memristor. Memristor-based novel architectures have demonstrated considerable promise in replacing or augmenting traditional computing platforms based on the Von Neumann architecture, which faces many issues in the big-data era, as well as in newly developed neuromorph...

Learning Automata (LA) in combination with Cellular Automata (CA) have been proven to be viable candidates as a mean to deal with problems of high complexity. Their ability to learn and adapt combined with their inherit parallelism can speed-up the solution process of various problems, including complex logic puzzles. A well-known logic puzzle is t...

Cellular Automata (CAs) have been proved to be a robust tool for mimicking a plethora of biological, physical and chemical systems. CAs can be used as an alternative to partial differential equations, in order to illustrate the evolution in time of the aforementioned systems. However, CAs are preferred due to their formulation simplicity and their...

Nowadays, the huge power consumption and the inability of the conventional circuits to deal with real-time classification tasks have necessitated the devising of new electronic devices with inherent neuromorphic functionalities. Resistive switching memories arise as an ideal candidate due to their low footprint and small leakage current dissipation...

Unconventional and, specifically, wave computing has been repeatedly studied in laboratory based experiments by utilizing chemical systems like a thin film of Belousov–Zhabotinsky (BZ) reactions. Nonetheless, the principles demonstrated by this chemical computer were mimicked by mathematical models to enhance the understanding of these systems and...

Self-selective memory devices are considered promising candidates for suppressing the undesired sneak path currents that appear within crossbar memory structures and compromise their performance during the write and read operations. Along these lines, in this work we present forming free SiO $_{\mathbf{2}}$ -based resistive devices with inherent s...

Memristor networks are capable of low-power and massive parallel processing and information storage. Moreover, they have presented the ability to apply for a vast number of intelligent data analysis applications targeting mobile edge devices and low power computing. Beyond the memory and conventional computing architectures, memristors are widely s...