On March 7th, Ditsuhi Iskandaryan defended her PhD thesis titled ““Study and Prediction of Air Quality in Smart Cities through Machine Learning Techniques Considering Spatiotemporal Components” under the supervision of Dr. Francisco Ramos and Dr. Sergio Trilles. The hybrid defence was overseen by Marco Painho, Michael Gould, and Mohammad Mehdi Moradi, and was a resounding success.

The dissertation is an exciting contribution to the field of air quality prediction, introducing several new innovations and ideas. Among these innovations, Ditsuhi presents a spatiotemporal forecast of a specific forecast target, nitrogen dioxide, using machine learning techniques. Additionally, her research incorporates and integrates air quality data, meteorological data, and traffic data in spatiotemporal dimensions within a defined spatial extent and time interval. Notably, the impact of the coronavirus disease 2019 pandemic was also taken into account as an external key factor influencing air quality levels. In addition, providing code and data that encourages and ensures reproducibility can be very useful to the domain. Her research raises many ideas and questions that can be developed and expanded in future work and launched into new projects or lines of research.
Ditsuhi’s successful PhD defence marks a significant milestone in her career, and we look forward to seeing where her research will take her in the future. Once again congratulations on this achievement!