Affiliation: Singidunum University, Danijelova, Serbia

Nebojsa Bacanin received his Ph.D. in Computer Science from the Faculty of Mathematics, University of Belgrade, in 2015, with an outstanding average grade of 10.00. He served as the vice-dean of the Graduate School of Computer Science and the Faculty of Informatics and Computing in Belgrade, Serbia. Currently, Dr. Bacanin works as a Full Professor and Vice-Rector for Scientific Research at Singidunum University.

His scientific research focuses on various areas of computer science, with particular expertise in artificial intelligence, machine learning, deep learning, stochastic optimization algorithms, swarm intelligence, soft-computing, optimization and modeling, image processing, computer vision, and cloud and distributed computing. Dr. Bacanin is also deeply involved in the emerging field of hybrid methods, combining machine learning and metaheuristics. In this domain, he applies metaheuristics to solve non-deterministic polynomial hard (NP-hard) problems in machine learning, such as hyperparameter optimization, training, and feature selection.

In addition to improving machine learning and deep learning models for tasks like classification and regression, Dr. Bacanin's research includes optimizing deep learning models for univariate and multivariate time-series forecasting. As an expert in metaheuristics, he works on enhancing swarm intelligence and other types of metaheuristic algorithms. He modifies the algorithms by adjusting exploitation/exploration expressions, parameters, or through hybridization with other methods, including low-level and high-level hybrid metaheuristics.

Dr. Bacanin applies his research to a wide range of practical applications, including cloud computing scheduling, wireless sensor networks (WSNs) localization, coverage, and energy consumption, X-ray image classification, stock price forecasting, and portfolio optimization, among others.