Methods of AI and Data Analytics

The Methods of AI and Data Analytics Research Group focuses on advancing techniques for analysing, modelling, and interpreting complex data. The group is dedicated to developing novel artificial intelligence methods and data-driven approaches, with applications spanning domains such as healthcare, engineering, natural sciences, and business. Our research integrates traditional AI methodologies, such as probabilistic reasoning and optimization, with state-of-the-art advancements in machine learning, deep learning, and large-scale data analytics to address real-world challenges effectively. Examples include novel error-correction mechanism for AI systems, novel methods for domain adaptation, and mechanisms to prevent adversarial attacks on AI systems.

Research expertise

• Advanced data analytics and data-driven modelling techniques
• Probabilistic reasoning and statistical inference
• Optimization methods for artificial intelligence
• Machine learning and deep learning methodologies
• Applications of AI and data analytics in healthcare, engineering, natural sciences, and business
• Scalable algorithms for large-scale data analysis and interpretation
• Error correction mechanisms for AI systems

Group members

• Bogdan Grechuk (group lead)
• Alexander Gorban
• Bo Wang
• Evgeniy Mirkes
• Katrin Leschke
• Neslihan Suzen
• Alexander Baranov
• Paul King