PhD Training Program of the Department of Computer Engineering, Faculty of Informatics and Computer Engineering, in the 2025 academic year
Postgraduate training at the Department of Computer Engineering is conducted in the field of Information Technologies under the following educational and scientific programs:
Third-cycle (PhD) Educational and Scientific Program “Software Engineering” in the specialty F2 “Software Engineering” (PhD). View the program.
Third-cycle (PhD) Educational and Scientific Program “Computer Engineering” in the specialty F7 “Computer Engineering” (PhD). View the program.
Entrance Exam Programs:
Entrance exam programs for obtaining the Doctor of Philosophy degree under the Educational and Scientific Program “Software Engineering” in the specialty F2 “Software Engineering” in the 2025 academic year.
Entrance Exam Programs for obtaining the Doctor of Philosophy degree under the Educational and Scientific Program “Computer Engineering” in the specialty F7 “Computer Engineering” in the 2025 academic year.
The PhD and doctoral training programs include the following research areas, which are offered to applicants for admission to doctoral studies in the 2025 academic year:
Embedded Systems and IoT; improving the efficiency of data collection and analysis in IoT systems; enhancement of IoT system architecture and network infrastructure; edge computing (EDGE)
System-on-Chip (SoC) based on FPGAs; reconfigurable computers
High-performance computer systems; organization of parallel data processing; real-time systems
D.Sc. (Eng.), Professor Mykhailo Anatoliiovych Novotarskyi
Methods and tools for mathematical modeling of complex physical processes
Development of parallel formal modeling frameworks
Methods for analyzing large-scale datasets
Machine learning methods
Deep machine learning
Ph.D. (Eng.), Associate Professor Artem Mykolaiovych Volokyta
Information security
Distributed computing
Real-time systems
High-performance fault-tolerant systems
Neural systems and genetic algorithms
Scalable iso-efficient systems
For applicants to Master’s and PhD programs in the 2025 academic year
The following dissertation topics are proposed:
Hordiienko Yu.G.
Method for optimizing large-scale data exchange in the context of the Internet of Things for balanced network traffic management (supervisor: not specified)
Method of hybridization of classical and non-classical computing for artificial intelligence tasks
Method of hybridization of classical and non-classical computing for artificial intelligence tasks
Method of measuring similarity of video content
Method for integrating distributed computing based on wearable electronics
Development of a method for identity verification in the Internet of Things
Method for optimizing software development processes based on a context-modular paradigm
Method of semantic image segmentation based on deep learning
Method for optimizing large-scale data exchange in the Internet of Things for balanced network traffic management
Methods for optimizing algorithms for generating ranking lists of university applicants during admission to higher education institutions
Kulakov Yu.O.
Method for building a local Internet access network based on SDN technology
Method for traffic engineering in data center networks with branched topology
Neural-network-based routing method in mesh networks
Method of multipath routing in software-defined networks
Methodology for deploying cloud infrastructure solutions
Markovskyi O.P.
Methods and tools for accelerating the computational implementation of asymmetric cryptography algorithms
Method for improving the efficiency of generating pseudorandom binary sequences for information security systems (supervisor: not specified)
Method and software tools for accelerating the implementation of computational procedures of asymmetric cryptography
Method for improving the efficiency of generating pseudorandom binary sequences for information security systems.
Method for secure implementation of information security algorithms on terminal devices
Method and tools for correcting multiple synchronization errors in serial interfaces of computer systems
Stirenko S.G.
Improving the efficiency of technical document processing methods using neural networks
Method for transaction risk assessment based on neural networks
Graph analysis using Bayesian neural networks
Integration of augmented reality elements with an image recognition system
Serhiienko A.M.
Methods and tools for designing hardware-oriented signal processing systems
Method for improving the efficiency of devices for computing elementary functions
Method of hardware modeling of ultrasonic wave propagation in a solid body
Method for improving the efficiency of non-recursive digital filters
Boldak A.A.
Methods and tools for distributed data processing
Zhabin V.I.
Improving the efficiency of computations in FPGA-based streaming systems
Method for implementing neural networks on a chip
Design of highly reliable scalable real-time computing systems
Method for dynamic task allocation in parallel computing systems
Method for synthesizing specialized parallel systems with direct inter-processor connections
Klymenko I.A.
Method and tools for building an IoT platform for solar panel monitoring
Method and tools for managing road infrastructure based on IoT technologies
Methods for improving the network infrastructure of IoT systems for Smart City applications
Method for adaptive mapping of algorithms in reconfigurable FPGA-based computing systems
Method for task allocation in a multiprocessor system-on-chip based on embedded processor cores
Neurocomputing system on FPGA for high-performance computing
Rusanova O.V.
Method for scheduling computations in heterogeneous multicore computer systems
Novotarskyi M.A.
Development of models and methods for ranking objects with dynamically changing features
Development of neural network methods and tools for predicting material properties
Development of deep learning methods for recognizing human facial emotional states
Development of methods and tools for modeling fluid motion in complex enclosed surfaces with moving boundaries
Development of formal tools for modeling parallel processes in distributed systems with non-stationary link structures
Development of methods for kernel selection and metrics for evaluating the effectiveness of kernel-based learning systems
Development of machine learning methods for dynamic multi-agent environments that are uncertain and incomplete
Pysarchuk O.O.
Multicriteria optimization neural network for assessing risks in bank lending
Volokyta A.M.
Methods and tools for improving the efficiency of physical process modeling in a fault-tolerant environment
Methods and tools for improving the efficiency of mobile platform control
