University of Groningen
Advanced non-homogeneous dynamic Bayesian network models for statistical analyses of
time series data
Shafiee Kamalabad, Mahdi
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Publication date: 2019
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Shafiee Kamalabad, M. (2019). Advanced non-homogeneous dynamic Bayesian network models for statistical analyses of time series data. University of Groningen.
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Acknowledgments
First and above all, I would like to express my deepest thanks to my God for helping me through all the difficulties and always strongly supporting me. Thank you God for your great love and care, and for your many blessings on us. I would like to express my sincere gratitude to my day-to-day supervisor, Marco Grzegorczyk, for his strong scientific support, encouragement, and pa-tience throughout my PhD studies. His guidance and supervision have been essential for their completion. I would also like to thank my supervisor, Ernst Wit for his support, and valuable comments during my PhD studies.
I would like to express my appreciation to Dirk Husmeier, Casper Albers, and Joris Mulder for assessing the present thesis and sharing their time and knowledge with me.
I am grateful to Dirk van Kekem for translating the summary of my thesis into Dutch and thanks to Hassan and Georg for being my paranymphs. I am also grateful to the supervisors of my master’s thesis, Nader Nematollahi and Ahmad Parsian, for all I learned from them during my master’s, which proved to be helpful in my PhD. Furthermore, I want to acknowledge Mohsen Ghanbary for encouraging me to study at the University of Groningen, and my special thanks go to Fardin for welcoming us when we arrived in the Netherlands for the first time.
I am in debt to all my friends and colleagues in the Netherlands, especially in Groningen, for creating a pleasant environment and providing stimulating discussions. Most notably I would like to thank Ahmad, Ahmadreza, Alef, Ali, Ben, Bohuan, Dirk, Fentaw, Francisco, Fred, Gabriel, Georg, Hamed, Hassan, Jin, Jorge, Jris, Luca, Maartje, Mahdi, Marcus, Mathijs, Matthijs, Maurits, Mehdi, Mohammad, Nazia, Naomi, Nikolay, Reka, Reza, Rianne, Pariya, Sam, Spyros, Venus, Wim and Yongjiao.
Words cannot express how grateful I am to my family: my father and my mother, my brother and sisters for all of the sacrifices that they have made on my behalf. Your prayers for me are what have sustained me thus far. I also wish to thank my in-laws, especially my mother-in-law, for their love and encouragement.
Most importantly, it would have been impossible to finish my PhD studies and write this thesis without the unconditional love, support, care, and
162 ment from my beloved wife Mozhgan and my two dearly loved and wonderful children: Alicenna and Delina, who provide me with unending inspiration. I would like to dedicate this thesis to you from the bottom of my heart. My deepest appreciation is for you forever.
Mahdi Shafiee Kamalabad Groningen, January, 2019.
