Modelling computer and communication systems with stochastic processes, in particular Markov chains, fluid models, reward models and mean-field models. Efficient numerical solution of large-scale Markov chains with regular structure. Theory of large deviations. Numerical inverse Laplace transform. Data modelling by fitting phase type processes with Markov arrival processes. Main application areas (with industrial experience): performance analysis of telecommunication systems, efficient routing in sensor networks, modelling of financial and IoT data sets, anomaly detection.
OKTA • MILAB • MTA TKI (Information Systems Research Group)
TU Dortmund • Universita di Torino • University of Antwerp
Nokia – Bell Labs • Ericsson
Our research covers the full spectrum of artificial intelligence (MI), organically linked to our group’s decades-long faculty role in general AI education, which is now present in BProf, BSc, MSc and PhD programs. Our working groups within the research group are Digital Humanities, Image Processing and Multimodal Diagnostics, Cooperative Intelligence, and Computational Biomedicine (ComBine). Digital Humanities examines semantic technologies through the processing of natural language. Image Processing and Multimodal Diagnostics explores the integration of classical image processing and information fusion methods with new artificial intelligence-based methods. Cooperative intelligence research examines federated learning, sensor networks, autonomous vehicles, multi-agent systems, and distributed computing methods. The ComBine team is developing artificial intelligence methods for bioinformatics, chemoinformatics and health informatics, with a particular focus on data and knowledge fusion, systems-based data analysis, and causal discovery.
We have launched an Artificial General Intelligence course to teach about the grand challenges, limits, trends, interdisciplinary nature and ethical, social dimensions of artificial intelligence. Our group is also participating in the development of a new Human-Centered Artificial Intelligence MSc program, which is part of an international EU project. We have launched and organized a student competition at the faculty in Artificial Intelligence and Machine Learning for the third time. In our research, we routinely use and constantly expand our Bayesian systems-based analysis to support biomarker discovery in several projects (UKB1602, TRAJECTOME, OTKA119866, OTKA139330). In addition to our statistical genetic research, we also focus on the development of AI methods for chemoninformatics and drug discovery, which is strengthened by our participation in national and international projects (MELLODDY). Our intelligent image processing and multimodal data fusion research has also been boosted by new projects, and we are examining the use of modern artificial intelligence tools in natural language processing in several collaborations.
H2020/IMI2, MELLODDY • EUREKA, iCare4NextGen • OTKA K139330
University of Minnesota • K.U.Leuven
SOTE • Richter • Dealogic • Abylon Kft. • E-Group • Continental
Investigation, development and implementation of modelling, signal processing and control techniques used in robotics. Autonomous behaviour of robots and robot groups, navigation and trajectory planning algorithms, specification and implementation of intelligent functions based on these algorithms. Robot applications in real and virtual environments, robot control hardware and software architectures.
TODO
Mitsubishi robotic arm • KUKA robotic arm
VKE • H2020 • TKP/FIKP
University of New South Wales • Kyungpook National University • University of New Hampshire • Griffith University
KUKA • Gamma digital • Knorr Bremse • ThyssenKrupp • Continental • Akytec • Emerson
The mission of the Laboratory of Multimedia Networks and Services (MEDIANETS) is to combine traditional strengths in networking with new competences in articifial intelligence, applying it to smart city environment. Research and development activities include machine learning and data analytics for intelligent and automated cities, V2X communication and intelligent transportation systems. MEDIANETS is active in significant European and national research projects, together with R&D projects carried out with our partners from the ICT industry.
Commsignia RS2/OB2
VKE
University of Babylon • Victoria University of Wellington, New Zealand • University of Cauca, Colombia • University of Donja Gorica • Technical University of Kosice, Slovakia • Raytheon BBN Technologies, University of Iowa • Universite libre de Bruxelles
Commsignia • T-Systems • RacioNet Zrt • Gamax Kft • Nokia Bell Labs • Ericsson • Utiber
Fundamental research in graph theory, hypergraphs, combinatorics, combinatorial optimization, combinatorial number theory, game theory, database theory, rigidity of graphs and structures, additive combinatorics, combinatorial geometry, search theory, extremal set systems, relation between databases and code theory, graph coloring, behaviour of graph parameters in product graphs
Péter Pach Pál developed a new version of the polynomial method in 2016 together with Croot and Lev. This new method has led to the solution of famous problems such as the cap set problem or the Erdős-Szemerédi sunflower conjeture. Since then, the method has had many applications, such as exact bound for Green’s lemma of “arithmetical triangle removal” (Fox-Lovász), Sárközy’s theorem for polynomials over finite bodies (Green), and many others. The article was published in the most prestigious mathematical journal, Annals of Mathematics, and Fields Medal-winning mathematicians Gowers, Tao, and other leading mathematicians such as Cameron and Kalai have also analyzed it on their blogs.
Géza Tóth, together with János Pach and Gábor Tardos, proved far-reaching generalizations of the Crossing Lemma to multigraphs under various natural conditions.
Gábor Wiener, together with Peter Dameschke and Azam Sheikh Muhammad, laid the combinatorial foundations of a new, practical and well-used strict group testing model, which was published in the Journal of Combinatorial Theory A, one of the leading combinatorial journals.
Gábor Simonyi, together with Gábor Tardos, gave a partial (complete in the 4-chromatic case) characterisation of the colour-critical edges of Schrijver graphs.
Gyula Katona and László Papp, in a joint work with Ervin Győri, gave lower and upper bounds on the optimal pebbling number of large grids.
Gyula Katona, with Kitti Varga, achieved several significant results in the study of minimally tough graphs.
MTA Lendület • OTKA
Ibaraki University, Japan • Lancaster University, UK • University of Haifa, Israel • University of Warwick, UK • Ghent University • Yokohama National University • University of British Columbia, Canada • Sapienza – Universitá di Roma
Morgan Stanley • Lynx Analytics
Our research group works in 3 domains within the field of security and privacy:
In domain (1), we work on the security of industrial automation and control systems, security of modern vehicles and intelligent transport systems, and security of IoT systems and applications. The common in these topics is that attacks originating from cyberspace may have physical consequences, resulting in equipment or environmental damage, or potentially even loss of human life, and therefore, security is an important requirement. In domain (2), we study how machine learning can be used to solve security and privacy problems, and also how machine learning–based systems may be exploited maliciously. More specifically, we focus on the security of federated learning algorithms and the problem of adversarial examples (e.g., in machine learning-based malware detection). In domain (3), we apply game theoretic models to study the incentive structures in different systems, and the cause of security and privacy problems. Besides the domains mentioned above, we have strong competency in applied cryptography, privacy enhancing technologies, malware analysis, reverse engineering, and secure operation of networks and network-based systems, including IT infrastructure automation.
IoT devices, PLCs, industrial devices, servers • PIRAMID ICS/SCADA security testbed
PrOTectME (EIT Digital) • H2020 MELLODDY • H2020 SECREDAS • H2020 SETIT
NTNU, Trondheim, Norway • KU Leuven, Belgium • INRIA Rhones-Alpes, France • University of California, Irvine, CA • New York Institute of Technology
Microsec Zrt. • Tresorit Kft. • Ukatemi Technologies Kft.
Our lab group is an “old hand”, we have been present at the Department of Telecommunications and Media Informatics of the Budapest University of Technology and Economics since the beginning. Our main areas of expertise are speech communication and speech technology in Hungarian, human-machine, human-robot interfaces, assistive interfaces for blind, visually impaired and speech impaired users, general statistics and modern machine learning algorithms. A strong focus on deep learning research and education. We have gained experience in a number of national and international projects in the broader field of ICT applications (customer service automation, self-driving cars, etc.). Our technologies have been applied in practice in these areas for decades.
GPU servers
OTKA • CELSA
University of Novi Sad, Serbia • University of Ss. Cyril and Methodius, Skopje, Macedonia • diap Research Institute, Martigny, Switzerland • Université Pierre et Marie Curie, Paris, France • Langevin Institute, ESPCI-ParisTech, Paris, France • Tianjin University, Tianjin, China • University of Cologne, Cologne, Germany • Universidad Industrial de Santander Bucaramanga, Santander, Colombia • UPC Barcelona, Barcelona, Spain • National University of Defense Technology, Changsha, China • AGH University of Science and Technology, Department of Measurement and Electronics • University of Ss. Cyril and Methodius in Skopje, Macedonia • Università della Campania Luigi Vanvitelli and IIASS • Université Grenoble Alpes • Universidad Industrial de Santander Bucaramanga, Santander, Colombia
ELTE • SOTE • ELKH • Hospitals • Idomsoft • IT.DOT Kft • OTP • Microsoft Mo. Kft. • Auxiliis Pharma Kft. • SCI Hálózat zRt.
The Applied Computer Science group’s research interests include software development methods, efficient and maintainable development techniques, and testing. Other research areas include scalable software architectures and environments, and applied artificial intelligence, machine learning and big data, and business intelligence solutions. This is complemented by the area of smart data collection, which is of particular importance for the design and implementation of large-scale systems.
TODO
MI Nemzeti Labor • Autonóm Nemzeti Labor • TKP
University of Dresden • University of Helsinki
Sagemcom • Nokia
The group deals with modern methods of data mining, information retrieval, natural language processing, machine learning, image and video processing. These belong to the fields of artificial intelligence and data science, within which the research focuses on computer vision, neural networks, deep learning, active learning. In addition to research, the group also plays a significant role in education, as responsible for Specialization of Data Science and Media Informatics in the MSc Computer Engineering, Specialization of Analytical Business Intelligence in the MSc Business Informatics, and Data-Based Systems Specialization in BProf Computer Engineering.
GPU (Titan X)
Posta • Tigáz • Magyar közút • Pannon University • ELTE • Debrecen University • NKE