Three new FiDiPro Professors to Aalto
Tekes has decided to fund 12 new FiDiPro research projects. FiDiPro - Finland Distinguished Professor Programme provides competitive grants to projects recruiting highly merited scientists, who are able to commit to long-term cooperation with a Finnish university or research institute. Three of the research projects starts at Aalto.
FiDiPro Professors and projects starting 1 January, 2015 at Aalto University:
Gang Xiong (FiDiPro Professor): Social Manufacturing
Host organization: Professor Ilkka Kauranen, Aalto University, School of Sciences
The emergent phenomenon of social manufacturing is disrupting industries all over the world. People are increasingly engaging in socio-economic systems built around sharing of human and physical resources, leading to new end-user experiences and new value-creation logics for companies. It includes the shared creation, production, distribution, trade and consumption of goods and services by different people and organizations.
Examples of already disrupted industries include transportation and hospitality: the fastest growing taxi company in the world, Uber, does not own any of its cars, and AirBnB quickly grew into the largest hotel chain without ever owning a single room.
The social manufacturing project seeks to unravel the forthcoming paradigm shift within the manufacturing and energy industries, integral parts of the Finnish economy, and thereby to identify new sources of competitiveness ex-ante, so that the Finnish companies would be prepared, or even drive the global disruption.
Social manufacturing project facilitates industrial renewal and the creation of new global leaders with the specific aim of raising Finnish clothing and energy companies among the fastest growing companies in their respective industries.
Hiroshi Mamitsuka (FiDiPro Professor): Machine Learning for Augmented Science and Knowledge Work
Host organization: Professor Samuel Kaski, Aalto University, Helsinki Institute for Information Technology HIIT
As most fields of science, engineering and society are becoming data-dependent and even data-driven, it is becoming clear that a core common success factor across the fields is the ability to harness the ever more complex big data to form hypotheses and make inferences for actions – this is the motivation of machine learning research.
The objective of this project is to advance the current cutting-edge machine learning techniques beyond standard data tables to structured data, found in many modern applications, such as personalized medicine and bioinformatics. More generally, the objective is also to augment knowledge work across a multitude of fields.
The results of the developed machine learning techniques will be applied to personalized medicine, ultimately to tailor treatments for specific patients by predicting effectiveness, identifying biomarkers, and characterizing treatments of disease subtypes. Furthermore, in the context of bioinformatics this project deals with the enhancement of crop breeding given the changing climate and toughening environment conditions to bring new economic opportunities for agriculture.
Richard Cuthbertson (FiDiPro Fellow): Red Queen Effect – Strategies for an Innovative Landscape
The retail sector is experiencing technological disruptions that have implications for the competitiveness of established retailers. In particular, the Finnish retail sector is facing new forms of competition by retailers that leverage the online channel in novel ways. Further, the online channel enables new entrants to expand without incurring heavy investments in brick and mortar stores.
Retailers need to incorporate technological changes into their strategy work, or fall victim to them. The goal of this project is to advance our understanding regarding new strategy implementation during technological disruption by analysing and comparing experiences and experiments in two retail sectors: the United Kingdom and Finland.
The next Tekes FiDiPro application round will close at 26th February 2015.