Rate My Professor Tatiana Kalganova

Her research specializations encompass artificial intelligence and real-life applications, evolutionary design and optimisation, evolvable hardware, modelling and optimisation of large systems, operational research, robotics, and swarm optimisation. She has secured funding for projects including Horizon Europe 'Recharged Climate aware resilience for sustainable critical and interdependent infrastructure systems enhanced by emerging digital technologies' (2023-2026), Department for Business Energy & Industrial Strategy RE-VOLT for high voltage asset monitoring (2021-2023), Intel autonomous digital supply chain (2020), and European Commission DERECKA (2020-2023). Key publications feature 'A review of faithfulness metrics for hallucination assessment in Large Language Models' (IEEE Journal of Selected Topics in Signal Processing, 2025), 'Identifying Suitability for Data Reduction in Imbalanced Time-Series Datasets' (AI, 2025), 'Intelligent Scheduling Methods for Optimisation of Job Shop Scheduling Problems' (Electronics, 2025), and 'Exploring 8-bit Arithmetic for Training Spiking Neural Networks' (IEEE COINS, 2024). Awards include 2nd place, Caterpillar Research and Innovation in Demand Strategy Competition (2012). She serves on editorial boards of Scientific Journals International, Information Engineering Journal, and Genetic Programming and Evolvable Machines (Springer), referees funding for Grant Agency of the Czech Republic, Research Council of Norway, Qatar National Research Fund, and program committees for EuroGP, GECCO. As examiner for PhD/EngD at Brunel, University of Edinburgh, Norwegian University of Science and Technology, and reviewer for IEEE Transactions on Evolutionary Computation. In teaching, she leads programming and research methods modules, coordinates projects, ERASMUS, and ECE International Partnerships.