Aalto University rewards the top 10% of doctoral dissertations with an Aalto University Dissertation Award. The criteria for the award are strong academic quality, high impact and a high level of originality. The awarded dissertations were approved during 2018, the size of the award is €3,000.
The awarded dissertations were suggested by the departments, recommended by the Doctoral Programme Committee and finally decided by the Dean Jouko Lampinen. The prizes were awarded during the SCI annual Get Together morning. The event, which took place in the A Bloc resturaunt in Otaniemi also featured talks on the theme Careers After Graduation by Dr. An Chen and Dr. Jaakko Timonen from Aalto University, and Dr. Robert Albrecht, from Noiseless Acoustics.
The Prize Winners
- Dr. Abdulmelik Mohammed, Department of Computer Science
Supervising professor and thesis advisor: Prof. Pekka Orponen
Dissertation: Algorithmic Design of Biomolecular Nanostructures
The doctoral thesis of Abdulmelik (Melik) Mohammed introduced algorithmic techniques to the design of biomolecular nanostructures at a new level of complexity and sophistication. His methods were first applied to the automated design of 3D wireframe DNA origami structures in a breakthrough article published in the journal Nature in 2015. This article has at the moment 225 citations on Google Scholar and 169 citations on Web of Science, making it one of Web of Science's list of "highly cited papers". As a fundamental contribution to the rapidly emerging field of DNA nanotechnology, Melik's methods have relevance to a wide spectrum of problems in nanoscience and nanoengineering. Most recently, his work was displayed in the January 2019 National Geographic feature article on revolutionary ideas in medical technology.
- Dr. Anna Cichonska, Department of Computer Science
Supervising professor: Prof. Juho Rousu
Thesis advisors:Prof. Tero Aittokallio, FIMM (Institute for Molecular Medicine Finland) and University of Turku and Dr. Matti Pirinen, FIMM (Institute for Molecular Medicine Finland)
Dissertation: Machine Learning for Systems Pharmacology
Dr. Anna Cichonska developed machine learning tools to facilitate biomedical research in the “multiple genes - multiple diseases - multiple drugs” paradigm. The results of the thesis find applications in personalised medicine as well as drug repurposing. The publications of the thesis have attracted significant interest in short time: for example, the metaCCA software package has been downloaded over 4000 times and the papers summarised in the thesis have been already cited around 100 times to date.
- Dr. Polina Rozenshtein, Department of Computer Science
Supervising professor: Prof. Aristides Gionis
Thesis advisor: Dr. Nikolaj Tatti, F-Secure, Finland
Dissertation: Methods for analyzing temporal networks
The dissertation of Dr. Polina Rozenshtein develops novel algorithms for analyzing temporal networks. The research articles have been published in top journals and conferences. The dissertation is not only a step ahead in the analysis of temporal networks, but it also opens new directions for future research.
- Dr. Siavash Khajavi, Department of Industrial Engineering and Management
Supervising professor: Prof. Jan Holmström
Thesis advisor: Prof. Jouni Partanen, Aalto University
Dissertation: Improving additive manufacturing enabled operations – A forward looking empirical study
Dr Siavash Khajavi doctoral research is on the leading edge of the emerging research field of operations management in direct digital and additive manufacturing. His 2014 paper on the use of additive manufacturing in the spare parts supply chain (Khajavi, S., Partanen, J. and Holmström, J. (2014) was the first to consider how to digitalize spare parts supply operationally, and has become one of the highly cited papers of the research field.
- Dr. Juulia Suvilehto, Department of Neuroscience and Biomedical Engineering
Supervising professor: Prof. Mikko Sams
Thesis advisor: Prof. Lauri Nummenmaa, University of Turku
Dissertation: Maintaining social bonds via touching: a cross-cultural comparison
Juulia Suvilehto has been developing very original methods to study the most intimate and socially the most important of our senses, the social touch. She has collected maps of body parts which we are allowed to touch, depending on how close we are to each other. One of the original papers was published in the Proceedings of the National Academy of Sciences, reflecting the excellence of Juulia’s work.
- Dr. Alex Westström, Department of Applied Physics
Supervising Professor: Prof. Christian Flindt
Thesis advisor: Prof. Teemu Ojanen, Tampere University, Finland
Dissertation: Majorana and Weyl Modes in Designer Materials
The dissertation of Alex Westström made significant contributions to theory of quantum matter, in particular understanding of topological superconductors and Weyl semimetals. Successful research on these topics requires deep analytic thinking, creativity and constant willingness to push oneself further.
- Dr. Tuomas Vanhala, Department of Applied Physics
Supervising professor: Prof. Päivi Törmä
Thesis advisor: Dr. Ari Harju, Varian medical systems, Finland
Dissertation: Dynamical mean-field theory studies of superfluidity and topological phases in lattice models
Tuomas Vanhala theoretically predicted novel quantum states of matter for interacting particles confined in lattice potentials. He found, for instance, an interacting topological state, and co-existence of superconductivity and spatially varying magnetization. His results increase fundamental knowledge about interacting topological systems, and contribute towards applications where materials with new types of magnetic and electronic properties are needed.
- M.Sc. (defended) Sampo Hämäläinen, Department of Applied Physics
Supervising professor and thesis advisor: Prof. Sebastiaan van Dijken
Dissertation: Spin-wave excitations in multiferroic heterostructures and CoFeB/YIG bilayers
Sampo Hämäläinen studied magnetic excitations in thin films, known as spin waves, which are a promising carrier of information for new energy-efficient computing technologies. In his thesis, Sampo reports on original experiments that show how magnetic domain walls can be utilized to emit and actively control spin waves. These results, which have been published in high-impact journals such as Nature Communications, pave the way towards practical devices.