Meet our newest Academy of Finland Fellows

Dr Miguel Caro aims to model the chemistry and material properties of cellulose and its derivatives with unprecedented detail, with the focus on optimizing fabrication conditions for cellulose-derived carbon microfibers and the properties of magnetic carbon nanocomposites. In his project, Caro will develop new machine-learning-based mathematical functions, interatomic potentials, which will combine a hierarchization strategy for interatomic interactions with improved representation of atomic environments. This will allow Caro to explore the rich and complex chemistry of cellulose with accuracy and computational efficiency that are currently out of reach.

The project will benefit from the new ecosystem of supercomputers currently being deployed in Finland.

Dr Lu Cheng’s work will explore how cell mechanisms affect cancer development.  Alternative splicing is an important mechanism that modify messenger RNA after it is generated. If not working properly, alternative splicing might lead to cancer. We will resort to single cell RNA sequencing techniques to identify and quantify alternative splicing events, as well as its regulation. We hope this project will help us to gain a deeper understanding about the functions of alternative splicing in cancer development.

Dr Markus Heinonen’s fellowship will study Deep learning with differential equations. Machine learning is developing at an unprecented pace due to a paradigm shift caused by deep neural network models, which have revolutionised the several domains of science. Deep neural networks represents learning as a series of deterministic, complex and discrete transformations. In this project we will propose a groundbreaking new viewpoint on machine learning by developing a novel deep learning paradigm of probabilistic continuous-time deep learning, where interpretable, simple distributions of smooth transformations, or time differentials, encode the learning process as a continuous flow. The novel paradigm draws from solid foundations of physics, statistics and dynamical systems literature. 

Dr Pasi Nevalainen’s project will examine how the management of state-owned enterprise (SOE) has changed from the early 1970s until present. Chinese companies are prominent, but the fact is that state ownership is still strong in Europe too. In Europe, however, the form of ownership and the way SOEs operate have undergone a major overhaul. A broader understanding of this phenomenon – the return of state capitalism – requires qualitative research that challenges existing expectations, allowing also the theoretical concept of SOE to be redefined. The study will determine how the concept of a state-owned company has changed in Finland and the other Nordic countries, and how the “old” and “new” SOE models differ. You can read more about how Dr Nevalainen’s work will examine the effects of the covid-19 pandemic here.

Dr Sebastiano Peotta’s project aims to make superconductors work close to room temperature. A long-standing dream of physicists is to make the wondrous properties of superconducting materials available at high and ultimately even at room temperature, that is without the need to attach them to expensive refrigerators. A promising route to this ambitious goal has been put forward precisely here at Aalto and consists of engineering materials in which electrons have a very large or even infinite apparent mass. In the condensed matter physics jargon it is said that the material possesses a “flat energy band.” Quite counterintuitively these heavy and sluggish electrons suddenly become very light and dynamic if they have the chance to interact with each other and form pairs, an intriguing phenomenon which can be explained only by means of quantum mechanics. Recently, superconductive behaviour has been detected in novel artificial materials with flat energy bands, a result which has attracted enormous interest but also opened many new questions. In this project, I will explore how disorder (imperfections in the regular arrangement of atoms) affects the superconductive properties in the case of materials with flat energy bands since I expect, among other things, that disorder may allow superconductivity to persists at even higher temperatures than predicted so far. You can read more about previous work on the “Flat energy band” here.

Dr Haichao Wang’s project will reduce the CO2 output of the heating industry. In the energy sector, heating is becoming increasingly important in our attempts to transition to a low-carbon energy society. This is because heating accounts for almost half of the final energy consumption in Europe. This project is dedicated to improving the understanding of the real operating mechanism of thermal energy storage, coupled with district heating networks and the heat demand of end users. The project will then develop technology to make the load matching between the heat supply and demand more accurate. For this purpose, the project will build an innovative mathematical modelling system and try to solve it with a tailored algorithm – which is more efficient than the traditional methods based on matrix equations. Reasonable experimental tests and case studies will also be designed and implemented to validate the developed methods. Overall, this project will contribute new scientific findings and efficient engineering tools for active load matching in order to further improve energy efficiency and reduce CO2 emissions in the heating sector.