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Search results for: ARTIFICIAL INTELLIGENCE
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Identification of High-Value Dataset determinants: is there a silver bullet for efficient sustainability-oriented data-driven development?
PublicationOpen Government Data (OGD) are seen as one of the trends that has the potential to benefit the economy, improve the quality, efficiency, and transparency of public administration, and change the lives of citizens, and the society as a whole facilitating efficient sustainability-oriented data-driven services. However, the quick achievement of these benefits is closely related to the “value” of the OGD, i.e., how useful, and reusable...
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Influence of algorithmic management practices on workplace well-being – evidence from European organisations
PublicationPurpose Existing literature on algorithmic management practices –defined as autonomous data-driven decision making in people's management by adoption of self-learning algorithms and artificial intelligence – suggests complex relationships with employees' well-being in the workplace. While the use of algorithms can have positive impacts on people-related decisions, they may also adversely influence job autonomy, perceived justice...
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Macro-nutrients recovery from liquid waste as a sustainable resource for production of recovered mineral fertilizer: Uncovering alternative options to sustain global food security cost-effectively
PublicationGlobal food security, which has emerged as one of the sustainability challenges, impacts every country. As food cannot be generated without involving nutrients, research has intensified recently to recover unused nutrients from waste streams. As a finite resource, phosphorus (P) is largely wasted. This work critically reviews the technical applicability of various water technologies to recover macro-nutrients such as P, N, and...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublicationThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Smart Embedded Systems with Decisional DNA Knowledge Representation
PublicationEmbedded systems have been in use since the 1970s. For most of their history embedded systems were seen simply as small computers designed to accomplish one or a few dedicated functions; and they were usually working under limited resources i.e. limited computing power, limited memories, and limited energy sources. As such, embedded systems have not drawn much attention from researchers, especially from those in the artificial...
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Mohsan Ali Master of Science in Computer Science
PeopleMohsan Ali is a researcher at the University of the Aegean. He won the Marie-Curie Scholarship in 2021 in the field of open data ecosystem (ODECO) to pursue his PhD degree at the University of the Aegean. Currently, he is working on the technical interoperability of open data in the information systems laboratory; this position is funded by ODECO. His areas of expertise are open data, open data interoperability, data science, natural...
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Sathwik Prathapagiri
PeopleSathwik was born in 2000. In 2022, he completed his Master’s of Science in Biological Sciences and Bachelor’s of Engineering in Chemical Engineering in an integrated dual degree program from Birla Institute Of Technology And Science, Pilani, India. During his final year, he worked as a research intern under Dr Giri P Krishnan at Bazhenov lab, University of California San Diego school of medicine to pursue his Master’s Thesis on...
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Marek Czachor prof. dr hab.
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Karol Flisikowski dr inż.
PeopleKarol Flisikowski works as Associate Professor at the Department of Statistics and Econometrics, Faculty of Management and Economics, Gdansk University of Technology. He is responsible for teaching descriptive and mathematical statistics (in Polish and English), as well as scientific research in the field of social statistics. He has been a participant in many national and international conferences, where he has presented the results...
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Nina Rizun dr
PeopleNina Rizun is an assistant professor at the Faculty of Management and Economics at the Gdańsk University of Technology. In October 1999 she obtained a PhD degree in technical sciences in the Faculty of Enterprise Economy and Production Organization, National Mining Academy, Dnipropetrovsk, Ukraine. PhD thesis title: Development of Complex Subsystem of the Organization and Planning of Mining and Transport Processes. In the years...
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Andrzej Chybicki dr inż.
PeopleA graduate of the Faculty of Electronics, Telecommunications and Informatics at the Gdańsk University of Technology, PhD in technical sciences in the field of IT specializing in distributed data processing in IT . Aimed at exploiting the achievements and knowledge in the field of industrial research. He cooperated with a number of companies including OpeGieka Elbląg, Reson Inc., Powel Sp. z o. o., Wasat, Better Solutions, the European...
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Tomasz Deręgowski dr inż.
PeopleTomasz Deręgowski is Assistant Professor at the Department of Informatics in Management, Faculty of Management and Economics, Gdańsk University of Technology, Poland, and Head of Data Platform Engineering Department, working on Big Data, Machine Learning and Data Science solutions at Nordea Bank AB - the largest Scandinavian financial institution. He has more than 15 years of industrial experience, working as a programmer, team...
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AFarCloud Aggregate Farming in the Cloud
ProjectsProject realized in Department of Microwave and Antenna Engineering according to 783221 — AFarCloud agreement from 2018-05-17
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Jacek Rumiński prof. dr hab. inż.
PeopleWykształcenie i kariera zawodowa 2022 2016 2002 1995 1991-1995 Tytuł profesora Habilitacja Doktor nauk technicznych Magister inżynier Prezydent RP, dziedzina nauk inżynieryjno-technicznych, dyscyplina: inzyniera biomedyczna Politechnika Gdańska, Biocybernetyka i inżyniera biomedyczna, tematyka: „Metody wyodrębniania sygnałów i parametrów z różnomodalnych sekwencji obrazów dla potrzeb diagnostyki i wspomagania...
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Milena Sobotka
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Marek Galewski dr hab. inż.
PeopleMgr inż. - 2002r. - Politechnika Gdańska; Wydział Elektroniki, Telekomunikacji i Informatyki; Automatyka i RobotykaDr inż. - 2007r. - Politechnika Gdańska; Wydział Mechaniczny; Budowa i eksploatacja maszynDr hab. inż. - 2016r. - Politechnika Gdańska; Wydział Mechaniczny; Budowa i eksploatacja maszyn Dotychczasowe i planowane obszary badań: Redukcja drgań podczas obróbki frezowaniem i toczeniem Zastosowanie zmiennej prędkości obrotowej...
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Digital Interaction and Machine Intelligence. Proceedings of MIDI’2021 – 9th Machine Intelligence and Digital Interaction Conference, December 9-10, 2021, Warsaw, Poland
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Medical Image Dataset Annotation Service (MIDAS)
PublicationMIDAS (Medical Image Dataset Annotation Service) is a custom-tailored tool for creating and managing datasets either for deep learning, as well as machine learning or any form of statistical research. The aim of the project is to provide one-fit-all platform for creating medical image datasets that could easily blend in hospital's workflow. In our work, we focus on the importance of medical data anonimization, discussing the...
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Modified nanodiamond particle size studies by means of dynamic light scattering technique
PublicationThe Methods Utilizing the Phenomena of Light Scattering to Measure Particle Size distribution in different solvent, such as deionise water and alcohol and also to study the various structural formation when nanodiamond solution is placed on silicon surface. The purpose of this research project is divided into two parts to configure the measurement units for examining modified nanodiamond particles, examination...
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Modified nanodiamond particle size studies by means of dynamic light scattering technique
PublicationThe Methods Utilizing the Phenomena of Light Scattering to Measure Particle Size distribution in different solvent, such as deionise water and alcohol and also to study the various structural formation when nanodiamond solution is placed on silicon surface. The purpose of this research project is divided into two parts to configure the measurement units for examining modified nanodiamond particles, examination...
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AUTOMATIC LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA
PublicationBelow work tries to answer a question: if it is possible to replace real human with computer system in social games. As a subject for experiments, card games were chosen, because they require a lot of player interaction (playing and taking cards), while their rules are easy to present in form of clear list of statements. Such a system, should allow real players to play without constant worrying about guiding or helping computer...
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Adjusting Game Difficulty by Recreating Behavioral Trees of Human Player Actions
PublicationThis paper presents a proposition of a method for adjusting game difficulty to the current level of player's skills in one-on-one games. The method is based on recognition of human player's actions and recording of those actions in the form of behavioral trees. Such trees are later used to drive behaviors of computer-controlled opponents so that human player has beat hit own strategy and improve on it, to win subsequent games....
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Antropoidalny Model Inteligentnego Systemu Decyzyjnego dla Jednostek Autonomicznych
PublicationGłównym celem pracy jest opracowanie modelu procesów psychologicznych -- od momentu otrzymania bodźca do momentu podjęcia adekwatnej reakcji -- zachodzących w mózgu człowieka (psychologia poznawcza), oraz teorii motywacji (potrzeb, popędów i emocji). Model, zaprezentowany w pracy nazwany Inteligentnym Systemem Decyzyjnym (ISD), może mieć zastosowanie w systemie sterowania jednostką autonomiczną (agentem). W rozprawie rozważa się...
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Integration of brood units in game universe
PublicationAn access to a great number of various services allows for decomposition of complex problems Developing a game universe usually involves creation of various units which can be encountered by a player. Those can be lonely or organized in broods animals and monsters wandering around the game world. In order to provide natural gaming experience those units should behave variously depending on the world situation. Those behaviours...
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Cognitum Ontorion: Knowledge Representation and Reasoning System
PublicationAt any point of human activity, knowledge and expertise are a key factors in understanding and solving any given problem. In present days, computer systems have the ability to support their users in an efficient and reliable way in gathering and processing knowledge. In this chapter we show how to use Cognitum Ontorion system in this areas. In first section, we identify emerging issues focused on how to represent and inference...
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The impact of the temperament model on the behavior of an autonomous driver
PublicationBecause it is generally believed that the personality and temperament of a human driver influence his/her behavior on the road, the article presents a computational model of the temperament of an autonomous agent - a driver. First, a short review of the four ideas of Galen’s temperament in psychology is presented. Temperament traits are grouped into four other sets, one of which is chosen for implementation in the project of integration...
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JamesBot - an intelligent agent playing StarCraft II
PublicationThe most popular method for optimizing a certain strategy based on a reward is Reinforcement Learning (RL). Lately, a big challenge for this technique are computer games such as StarCraft II which is a real-time strategy game, created by Blizzard. The main idea of this game is to fight between agents and control objects on the battlefield in order to defeat the enemy. This work concerns creating an autonomous bot using reinforced...
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Possible uses of crisis situation aiding system in virtual world simulation
PublicationMany of the real world crisis situations like spreading fire, hostile units attack, flood, and etc. are commonly used in computer games where a simulation of extensive virtual world is crucial. This paper presents some ideas for possible uses of existing crisis situation aiding system in such environments. Moreover, it shows how this kind of system can be taught during subsequent games with a large number of players. As an example...
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Smart experience engineering to support collaborative design problems based on constraints modelling
PublicationEngineering design is a knowledge intensive process. Experts' experiences from different product life-cycle stages play a key role in problem solving during design decision making by linking up knowledge to find better solutions for a specific design problem. Different approaches have been used to support Collaborative and Concurrent Product Design, such as Constraint Satisfaction Problem (CSP) modelling. Additionally, due to the...
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Visual Features for Endoscopic Bleeding Detection
PublicationAims: To define a set of high-level visual features of endoscopic bleeding and evaluate their capabilities for potential use in automatic bleeding detection. Study Design: Experimental study. Place and Duration of Study: Department of Computer Architecture, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, between March 2014 and May 2014. Methodology: The features have...
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INDIRECT CONTROL OVER SUBORDINATE UNITS
PublicationDeveloping a game universe usually involves creation of various units which can be both, encountered by a player or controlled by him. There is a number of works considering autonomous behaviors of units wandering around the game world. When it comes to the units controlled by the player, they are often deprived of autonomy and are strictly controlled by the player. This paper presents a concept of units behavior depending on their...
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SPECTRAL-BASED MODAL PARAMETERS IDENTIFICATION WITH MULTIPLE PARTICLE SWARMS OPTIMIZATION
PublicationThe paper presents usage of a Particle Swarm Optimization [1] based algorithm for spectral-based modal parameters identification. The main algorithm consists of two groups of swarms, namely, scouts and helpers. For the first group additional penalizing process is provided to force separation of scouting swarms in frequency space. The swarms have an ability to communicate with each other. At first stage, each swarm focuses on a...
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Social media and efficient computer infrastructure in smart city
PublicationSocial media require an efficient infrastructures of computer and communication systems to support a smart city. In a big city, there are several crucial dilemmas with a home and public space planning, a growing population, a global warming, carbon emissions, a lack of key resources like water and energy, and a traffic congestion. In a smart city, we expect an efficient and sustainable transportation, efficient management of resources...
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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublicationOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks
PublicationThe presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods....
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Greencoin as an AI-Based Solution Shaping Climate Awareness.
PublicationOur research aim was to define possible AI-based solutions to be embedded in the Green- coin project, designed as a supportive tool for smart cities to achieve climate neutrality. We used Kamrowska-Załuska’s approach for evaluating AI-based solutions’ potential in urban planning. We narrowed down the research to the educational and economic aspects of smart cities. Furthermore, we used a systematic literature review. We propose...
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Skills mismatch in the context of technological change
PublicationThe main purpose of this dissertation is to assess the perception asymmetry of smart skills and formal education in ICT based economy. In other words, the goal of this research is to assess perceptions of smart skills and competences in the context of technological change from the perspectives of employers and students in Poland. Determining the fore-mentioned relationship gives insight into the hypothetical perception asymmetry...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublicationArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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Automatic Breath Analysis System Using Convolutional Neural Networks
PublicationDiseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is common for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected as...
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Qualia: About Personal Emotions Representing Temporal Form of Impressions - Implementation Hypothesis and Application Example
PublicationThe aim of this article is to present the new extension of the xEmotion system as a computerized emotional system, part of an Intelligent System of Decision making (ISD) that combines the theories of affective psychology and philosophy of mind. At the same time, the authors try to find a practical impulse or evidence for a general reflection on the treatment of emotions as transitional states, which at some point may lead to the...
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Impact of digital technologies on reliability of risk forecasting models - case study of enterprises in three global financial market regions
PublicationThis chapter focuses on the evaluation of impact of ICT on reliability of financial risk forecasting models. Presented study shows how the development of ICT can improve the effectiveness of such models. Determining a firm’s financial risk is one of the most interesting topics for investors and decision-makers. The multifaceted goal of the presented research is to separately estimate five traditional statistical and five soft computing...
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Nowe technologie w procesie projektowania architektonicznego
PublicationProjektowanie architektoniczne zmienia się wraz z wprowadzaniem nowych technologii. Zmiany, które są wynikiem cyfrowej rewolucji z końca XX wieku przyczyniły się do zmiany metod stosowanych w projektowaniu, ale nie sposobu myślenia o projektach i ich etapach. Można stwierdzić, że tradycyjna deska kreślarska została zastąpiona cyfrową. Jednak dziś w związku ze wzrostem skomplikowania procesów projektowych, ich wielowarstwowości...
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Multiple Cues-Based Robust Visual Object Tracking Method
PublicationVisual object tracking is still considered a challenging task in computer vision research society. The object of interest undergoes significant appearance changes because of illumination variation, deformation, motion blur, background clutter, and occlusion. Kernelized correlation filter- (KCF) based tracking schemes have shown good performance in recent years. The accuracy and robustness of these trackers can be further enhanced...
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Potential and Use of the Googlenet Ann for the Purposes of Inland Water Ships Classification
PublicationThis article presents an analysis of the possibilities of using the pre-degraded GoogLeNet artificial neural network to classify inland vessels. Inland water authorities monitor the intensity of the vessels via CCTV. Such classification seems to be an improvement in their statutory tasks. The automatic classification of the inland vessels from video recording is a one of the main objectives of the Automatic Ship Recognition and...
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Neural network based algorithm for hand gesture detection in a low-cost microprocessor applications
PublicationIn this paper the simple architecture of neural network for hand gesture classification was presented. The network classifies the previously calculated parameters of EMG signals. The main goal of this project was to develop simple solution that is not computationally complex and can be implemented on microprocessors in low-cost 3D printed prosthetic arms. As the part of conducted research the data set EMG signals corresponding...
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Data Acquisition and Processing for GeoAI Models to Support Sustainable Agricultural Practices
PublicationThere are growing opportunities to leverage new technologies and data sources to address global problems related to sustainability, climate change, and biodiversity loss. The emerging discipline of GeoAI resulting from the convergence of AI and Geospatial science (Geo-AI) is enabling the possibility to harness the increasingly available open Earth Observation data collected from different constellations of satellites and sensors...
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Adam Brzeski dr inż.
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Michał Lech dr inż.
PeopleMichał Lech was born in Gdynia in 1983. In 2007 he graduated from the faculty of Electronics, Telecommunications and Informatics of Gdansk University of Technology. In June 2013, he received his Ph.D. degree. The subject of the dissertation was: “A Method and Algorithms for Controlling the Sound Mixing Processes by Hand Gestures Recognized Using Computer Vision”. The main focus of the thesis was the bias of audio perception caused...
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Tomasz Białaszewski dr inż.
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Paweł Rościszewski dr inż.
PeoplePaweł Rościszewski received his PhD in Computer Science at Gdańsk University of Technology in 2018 based on PhD thesis entitled: "Optimization of hybrid parallel application execution in heterogeneous high performance computing systems considering execution time and power consumption". Currently, he is an Assistant Professor at the Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Poland....
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Paweł Syty dr inż.
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Dawid Wieczerzak mgr inż.
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Kacper Cierpiak
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Barbara Klaudel
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Hossein Nejatbakhsh Esfahani PhD
PeopleMy research interests lie primarily in the area of Learning-based Safety-Critical Control Systems, for which I leverage the following concepts and tools:-Robust/Optimal Control-Reinforcement Learning-Model Predictive Control-Data-Driven Control-Control Barrier Function-Risk-Averse Controland with applications to:-Aerial and Marine robotics (fixed-wing UAVs, autonomous ships and underwater vehicles)-Multi-Robot and Networked Control...
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Leszek Chomacki Dr inż.
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Muhammad Jamshed Abbass Phd in Electrical Engineering
PeopleMuhammad Jamshed Abbass received the M.S. degree in electrical engineering from Riphah International University, Islamabad. He is currently pursuing the Ph.D. degree with the Wrocław University of Science and Technology, Wroclaw, Poland. His research interests include machine learning, voltage stability within power systems, control design, analysis, the modeling of electrical power systems, the integration of numerous decentralized...
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Maria Ferlin MSc
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Gabriela Małyszko
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Karol Zdzisław Zalewski mgr inż.
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Tadele Ayana PhD student at Gdansk University
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Asad Jan Mr.
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Igor Niemczyk
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Rafał Wolniak
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Hassan Bazazzadeh mgr Inż. Arch.
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Szymon Zdybel
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Jakub Gaffke
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Natalia Ziółkowska mgr inż.
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Moizuddin S. Khaja Doctoral Candidate
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Rafał Buler
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Dharm Jain
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