Kutatás
Budapesti Műszaki és Gazdaságtudományi Egyetem
Villamosmérnöki és Informatikai Kar
Artificial Intelligence
Activity of the research group:
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.
Recent results:
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.
Recent projects:
H2020/IMI2, MELLODDY • EUREKA, iCare4NextGen • OTKA K139330
International relations:
University of Minnesota • K.U.Leuven
Industrial partners:
SOTE • Richter • Dealogic • Abylon Kft. • E-Group • Continental
Data Science and Content Technologies
Activity of the research group:
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.
Recent results:
- Active learning in image classification, Few-shot learning in X-ray image analysis,
- Character recognition (digit recognition) in extreme conditions,
- Spectral clustering on multimedia datasets, Recognition of plants in images by deep learning, Balanced active learning, Machine learning in an open set.
- 1st place in the SnakeCLEF 2021 International Image Classification Competition organized by ImageCLEF / LifeCLEF
Special infrastructure:
GPU (Titan X)
Industrial partners:
Posta • Tigáz • Magyar közút • Pannon University • ELTE • Debrecen University • NKE