INFORMATION AND COMMUNICATION TECHNOLOGY
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Time series classification is a popular machine learning task with many practical applications. To date, there have been many papers devoted to the classification of binary and multiclass time series of one and many variables. Thanks to the resources collected on the UEA/UCR Time Series Classificat…
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The evolution of 5G/6G network infrastructure towards integrated communication and computing infrastructure, improves currently offered services and enables new services such as Augmented/Virtual/Mixed reality (AR/VR/MR), immersive 6DoF video, 360 videos, as well as Internet of Everything (IoT/IoE)…
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Signal processing, especially speech processing. Natural language processing, in particular in the cybersecurity context. Voice biometry. Applications of machine learning. Computer technology in therapeutical applications.
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Methods of analysis and optimisation of intelligent complex systems SoS (System-of-Systems) – autonomous interacting technology-intensive systems, communicating and interacting with the environment, involved in real-time decision-making. The primary subject of research are network systems – compute…
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New video compression methods based on neural networks: The research problem is devoted to the development of new architectures of convolutional neural networks and other video signal processing components for effective compression of video sequences. These other elements include the use of orthogo…
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New video compression methods for low-latency transmission: The research issue is devoted to the development of new algorithms for selecting the encoding modes and adjusting the compression rate for video sequences. The aim of the work is to develop software methods for creating information streams…
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Optical transmission in free space and in optical fibers with application of advanced digital signal processing methods, multiplexing and coding to increase the spectral efficiency of optical transmission with both coherent and direct detection. Designing new techniques to counter the effects of in…
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General research are is digital processing of radar signals (or other signals with similar properties - echolocation, acoustic localization).
Specific areas proposed for a PhD student are:
- nonuniform sampling and incomplete data problems (including, but not limited to Compressed Sensing and its…
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Operations and Maintenance system in 6G Mobile Networks: analysis of Machine Learning impact in the network management as a whole (multi-agent environment)
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Use of information technology for proactive detection (identification and exposure) of disinformation and misinformation content - automated methods for flagging disinformation content, tracking propagation channels, detecting original sources of spreading false information. I am primarily interest…
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Theory and algorithms of intelligent hypercomplex signal processing: The research is concentrated on the theory and search of practical applications of theoretical results in multidimensional signal processing. Nowadays, the methods of intelligent signal processing are extensively developping as th…
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Theoretical studies and experiments in the domain of multidimensional complex and hypercomplex signals: The research is focused on development of theory and looking for possible practical applications of theoretical results in 2-D and 3-D signal processing. The theoretical part concerns the develop…
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1)Methods of detection and classification of heart abnormalities using deep learning techniques - concerns techniques and algorithms for processing ECG signals for automatic detection and classification of heart abnormalities using deep machine learning methods. It is planned to use a variety of d…
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cyber security, network security, IoT security, ICS security, malware analysis, HoneyPot systems
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Research Area of the Research Group on Radar Imaging Techniques, lead by dra hab. inż. Piotr Samczyński, prof. WUT, specializes in digital signal processing for the creation of two-dimensional (2D) and three-dimensional (3D) radar images using the synthetic aperture technique (SAR – Synthetic Apert…
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Research in the field of methods of observing new cyber attacks: anomaly detection and network steganography. The study aims to uncover cybercrimes through digital forensics effectively. The primary research issue is the development of new methods of observing phenomena, in particular in ICT networ…
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The research area covers the issues of image processing, computer vision, machine learning (including deep learning) and broadly understood artificial intelligence.
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Data analysis systems in various aspects: applications, modeling and implementation, the use of machine learning and artificial intelligence, SQL and NoSQL databases, structured and unstructured data, Big Data, optimization, visualization and understanding of data, data context and environment, eff…
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see https://www.gagolewski.com/
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1) Different categories of radar clutter and telecommunications interferences have probability distributions, the "tails" of which can be treated in a uniform way using the extreme value theory (EVT). This theory, however, describes only the asymptotic behavior of these distributions, for the detec…
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I deal with research on the practical aspects of using artificial intelligence. In particular, in recent years, my research has focused on: (1) the use of semantic technologies to represent and use knowledge, (2) the use of artificial intelligence methods in IoT systems (especially in situations wh…
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Research in the application of innovative techniques in the area of cybersecurity of information systems. The aim of the research is to develop mechanisms to increase the level of cybersecurity of computer systems, information networks or hardware implementations of systems (FPGA, ASIC, SoC) by app…
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The use of artificial intelligence methods for detection, tracking and target recognition in radar. Nowadays, artificial intelligence methods are used in more and more different fields. One of them is radar. The classic approach to radar uses methods and algorithms for the detection, tracking and r…
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Research on software engineering automation This research topic pertains to the influence of software development automation tools on the development process and monitoring, maintenance and further evolution of software. It is planned to undertake research on methods and … More
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Research on low-code systems (new generation visual general purpose programming languages) This research topic pertains to programming languages based on a visual paradigm and related to conceptual programming, knowledge modelling and constrained natural language. It is p… More
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Research on dedicated modelling languages for different application areas This research topic pertains to the development of modelling languages that serve defining executable models for different areas of application, e.g. Public Open Data (POD), the Internet of Thing (I… More
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Convergence of high-performance computing and machine learning. Development of distributed programming methods, techniques and environments, with particular emphasis on machine learning solvers and their integration into classic HPC solutions used in a cluster, grid and cloud environments in relati…
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The aim of the research is to develop the theory of floating-point calculations for elementary and special functions, using "magic constants" (bit-manipulation technique) for various formats - fp16, fp32, fp64. Development of a modern theory of approximation of such functions by algebraic polynomia…
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Applications of Artificial Intelligence (AI, such as deep learning) in the field of technical and environmental sciences, including the analog systems diagnostics (for instance, audio amplifiers or RIAA correctors), exploration of human musical taste based on the analysis of acoustic features of so…
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software engineering, bioinformtics, artificial intelligence, data fusion
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The research will be related to the systems for non-intrusive monitoring of elderly persons; in particular – the systems based on the radar sensors and depth sensors. The research will be focused on the development of new methods for: • the analysis of movements of monitored persons; • the predicti…
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Integration of knowledge and ICT systems.
The development of ICT infrastructure as a key layer of civilization will follow several basic directions.
At the technological level, it is the integration of more and more distant functionalities, virtualization, development
of structural components, m…
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bioinformatics, big data, distributed computing, machine learning
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computer vision (SLAM, visual search), machine learning (deep learning, generative models, continual learning), representation learning (binary descriptors).
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cyber security, network security, information hiding techniques, analysis of cyber threats and their countermeasures, security mechanisms
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Modeling, control, and simulation of complex systems (ICT, financial engineering, medicine, water resources, etc.), computer decision support systems, recommendation systems, wireless sensor networks, mobile ad hoc networks, optimal resource allocation in data networks and computing centers, par… More
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Distributed and prosumer-centered energy systems create conditions for local cooperation between producers and consumers. As a result, local market technical and business models are emerging, e.g., clusters and energy cooperatives. The proposed research field covers the design of market mechanis… More
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The prevailing solutions used in the practice of the operation of power systems are narrowed to the central balancing mechanisms. The proposed research field is about breaking this paradigm and considering a distributed balancing system involving multiple agents with different, sometimes conflic… More
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Informatyka medyczna; Informatyka zorientowana na człowieka; Teoria informacji; Komputerowe wspomagania decyzji; Inteligencja obliczeniowa, rozszerzona, wzmocniona; Reprezentacje rzadkie sygnałów; Oszczędne próbkowanie; Ocena jakości obrazów; Przetwarzanie i analiza obraz&oa… More
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Medical informatics; Human-centered computing; Information theory; Computerized decision support; Computational, augmented, amplified intelligence; Sparse signal representations; Compressed sensing; Image quality assessment; Image processing and analysis; Multimedia More
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Bioinformatyka, genomika obliczeniowa, sztuczna inteligencja, uczenie maszynowe More
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Opis obszaru badawczego More
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Machine learning for social and sensor data This issue is dedicated to candidates with knowledge of machine learning methods, the ability to acquire and process data and those interested in both development in this area and the application of these methods to social issues. The goal will be to d… More
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Red teamming AI foundation models. Foundation models (for language or image data) will play an increasingly important role in AI systems. They will also provide more and more opportunities for a diverse range of applications, often not foreseen at the model training stage. An in-depth analysis a… More
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Polyrepresentation learning for image or text models. AI systems use numerous approaches to train data representations. Often, however, a single approach is based on one selected perspective related to the loss function used to train the representation. When looking for fundamental models, it ma… More
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I invite doctoral students and researchers interested in harnessing the latest technologies in medicine to collaborate. My work is interdisciplinary, offering the opportunity to engage in both fundamental and applied research. The goal is not just to hone your analytical and programming skills b… More
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I am interested in interdisciplinary topics related to the development and use of modern IT methods. My experience includes computer modelling of biological phenomena, problem-solving in computational intelligence, and IT system security. I am currently researching large language models (LLMs) a… More
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First research field: artificial intelligence, machine learning, in particular, dimensionality reduction, data visualization, clustering, classification, self-organization, outlier detection, artificial neural networks, feature extraction and selection. Second research field: concurrent programm… More
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In recent years, the development of optimization algorithms tends toward specialization. State-of-the-art solutions primarily require laborious setting of multiple initial parameters, which in real-world scenarios can be difficult, if at all possible. In this view, we advocate the need to shifti… More
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Self-supervised learning (SSL) methods have shown significant potential in improving the sample efficiency of deep learning and in providing a starting point for the learning of downstream tasks. Contrastive SSL methods have become a standard pre-training approach for a range of domains such as … More
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A prevalent theme present in the contemporary representation learning approaches is to pre-train large foundation models on huge datasets. Such approaches utilize static datasets constructed at a particular point in time, which contrasts with the constantly changing and expanding nature of data … More
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Globalization of threats to homeland security, such as international terrorism, smuggling of weapons or drugs became one of the main challenges for security forces in the 21st century. In effect, new, scientifically grounded methods for fighting organized crime have been proposed in recent years… More
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Abstract Visual Reasoning (AVR) comprises problems that resemble those appearing in human IQ tests. For example, Raven's Progressive Matrices present a set of images arranged in a 3x3 grid with a missing panel in the bottom-right corner. The test-taker has to discover relations governing 2D … More
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