Rate My Professor Michal Aibin

Michał Aibin serves as Research Faculty in the Computing Department at the British Columbia Institute of Technology (BCIT), where he contributes to the School of Computing and Academic Studies as a faculty researcher and Program Head in AI initiatives. He holds a Visiting Associate Professor position at Northeastern University's Khoury College of Computer Sciences and is a network member in the Disaster Resilience Research Network at the University of British Columbia, listed under Computing. Aibin completed his Ph.D. in 2017 at Wroclaw University of Science and Technology, defending a thesis titled "Dynamic Routing Algorithms for Cloud-Ready Elastic Optical Networks" at the Department of Systems and Computer Networks, where he began studies in 2012. During his doctoral tenure, he received Dean's Awards for scientific achievements in the academic years 2014/2015 and 2015/2016 from the Dean of the Faculty of Electronics.

Aibin's research centers on artificial intelligence, machine learning, deep learning, optimization, computer vision, and their applications to unmanned aerial vehicles (UAV/RPAS), wildfire detection, remote sensing, eHealth, optical networks, traffic prediction, and disaster-resilient communication networks. His projects include real-time image detection for search and rescue using drones, wildfire monitoring with AI, brain tumor detection from MRI images, and contributions to international efforts like the Canadian Hyper-K neutrino experiment. Notable publications encompass "Guide to disaster-resilient communication networks" (2020, Springer Nature), "A survey on traffic prediction techniques using artificial intelligence for communication networks" (2021, Telecom), "An overview of security challenges in communication networks" (2016, RNDM), "Adaptive modulation and regenerator-aware dynamic routing algorithm in elastic optical networks" (2015, IEEE ICC), "Traffic prediction based on machine learning for elastic optical networks" (2018, Optical Switching and Networking), and "Traffic Prediction in Optical Networks using Graph Convolutional Generative Adversarial Networks" (2020, ICTON). With over 1,000 citations across his work, Aibin has advanced resilient network design and AI applications in real-world scenarios. He earned the BCIT Employee Excellence Award in June 2018 for applied research on brain tumor detection software and leads a special issue in the journal Remote Sensing.