Thesis supervisor: Márton Ispány
Location of studies (in Hungarian): University of Debrecen Faculty of Informatics Abbreviation of location of studies: DE IK
Description of the research topic:
Syllabus
Developing theoretical models on the field of information technology based on the up-to-date data science methods which can succesfully be applied to solve different Smart City problems. The research includes both the theoretical investigation of the models, analyzing architectures developing and testing. The research topic is basically, an interdisciplinary field where computer sciences meet conventional city-related fields, like transportation, civil engineering, environment, economy, ecology, and sociology in the context of urban spaces.
Bibliography
Bishop, C. M., Pattern Recognition and Machine Learning, Springer, 2006.
Hastie, T., Tibshirani, R., Friedman, J., The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer-Verlag, 2009.
Yu Zheng, Licia Capra, Ouri Wolfson, Hai Yang, Urban Computing: Concepts, Methodologies, and Applications. ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Urban Computing archive
Volume 5 Issue 3, September 2014
Michele Chambers, Christine Doig, and Ian Stokes-Rees, Breaking Data Science Open. O’Reilly Media, 2017.
Deadline for application: 2024-05-15
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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