Department of Mathematics and Systems Analysis

Current

Public defence in Systems and Operations Research, M.Sc. (Tech) Pekka Laitila, 25.5.2022

13. May 2022

Risk management and decision-making under uncertainty are common challenges in business and public administration. Often the framework of a decision-making problem consists of various types of factors and variables whose mutual probabilistic dependencies may be difficult to know or perceive exactly. For instance, there might not be suitable historical data available, or the relevant data may be difficult to identify. These problems are typical in situations where risks are novel or unprecedented. Among such instances are, e.g., unique projects, ecological and economical disasters, and governmental conflicts.

Even though there might be a lack of suitable historical data, there is often an abundance of expert insight available, along with diverse information on indirectly related factors. In these situations, analysis of risks and decision-making under uncertainty can effectively be supported by Bayesian networks (BNs). A BN represents a system of linked components both visually and numerically enabling a rigorous quantification of risks and a clear communication of the components’ interaction. BNs can be constructed based on various information sources such as experimental data, historical data, and expert knowledge. The applications of BNs are numerous and cover a wide range of domains, such as medical decision support, risk analysis concerning epidemics, ecosystems, and industry, as well as policy and military planning.

The dissertation elaborates the construction of BNs by expert elicitation which involves subjective assessments of a domain expert and is often required in practical applications. The main contribution is the development of new elicitation approaches that help the expert to establish required numerical dependencies between BN components. The approaches improve an existing elicitation method commonly used in BN applications. They reduce the elicitation effort of the expert and also extend the application scope of the underlying method. Their practical execution is supported by thorough guidelines and online implementations. Consequently, the new approaches facilitate and promote the effective and diverse utilization of BNs in various applications.

Opponent is Professor Norman Fenton, Queen Mary University of London, UK

Custos is Professor Kai Virtanen, Aalto University School of Science, Department of Mathematics and Systems Analysis

Contact details of the doctoral student: pekka.laitila@aalto.fi

The public defence will be organised on campus and via Zoom. Link to the event

The doctoral thesis is publicly displayed 10 days before the defence in the publication archive Aaltodoc of Aalto University.

Electronic thesis


Public defence in Mathematics and Statistics, M.Sc. (Tech) Paavo Raittinen

19. April 2022

The age of machine learning is now. Machine learning application are ubiquitous in digital platforms such as Google, Netflix streaming service, or Wolt food delivery service. However, machine learning is not yet considered as state-of-the-art statistical analysis method, e.g., in the field of biomedicine. In scientific biomedical literature most of the method used for statistical analysis are classic frequentist methods.

In my doctoral thesis “On statistical analysis and machine learning in prostate cancer research”, the application of certain machine learning method (random forests) in prostate cancer research was studied, compared to traditional method (Wilcoxon rank sum test). Due to multidisciplinary nature of the study the purpose was two-branched: on one hand the feasibility of machine learning methods was studied while on the other hand the results were analysed in the context of prostate cancer and an attempt to explain the biological mechanisms were made. The basic data was based on ESTO1 randomized clinical trial (RCT) which was expanded with a spectrum of lipid and steroid compound measurements, i.e., lipidome and steroidome. The main purpose of the ESTO1 study was to investigate the impact of statin use on the cellular level, compared to placebo. To our knowledge, such vast lipidome / steroidome data have not been studied in similar study settings, not to mention analysed by machine learning.

With the selected machine learning method, random forests, we reached same results and arrived at same conclusion than by using classic methods. Moreover, random forests model results enable analysing the hierarchy between the features (variables) which is a clear benefit over classic methods. From the biology perspective, statin use influences serum steroidome and lipidome in general. Furthermore, statin use seems to have a down-shifting impact on the lipid and steroid milieu in the prostatic tissue. Both biological results are novel.

The result of the thesis gives a positive example about machine learning feasibility in analysing results from classic RCT study design in the field of prostate cancer research. The conclusion is that prostate cancer can already now benefit about machine learning and developments made in that field in the future.

Opponent is Professor Tommi Sottinen, University of Vaasa, Finland

Custos is Professor Pauliina Ilmonen, Aalto University School of Science, Department of Mathematics and Systems Analysis

Contact details of the doctoral student: paavo.raittinen@aalto.fi

The public defence will be organised on campus.

The doctoral thesis is publicly displayed 10 days before the defence in the publication archive Aaltodoc of Aalto University.

Electronic thesis


Department's Biitsi Party 2022

5. April 2022
Perhaps the date (April Fool's Day) had an effect on the slightly low amount of the participants..
nevertheless Biitsi was super nice, food delicious and we had great fun!

Thanks for the participants! Here are some photos.

New hourly paid teachers of mathematics and systems analysis for fall 2022

4. April 2022

The Department of Mathematics and Systems Analysis is seeking

New hourly-paid teachers in Mathematics and Systems Analysis for fall term 2022.

Your tasks include teaching in exercise groups and grading exercises and exams.

Regarding teaching in mathematics, we expect the applicants to have completed at least 20 credits of mathematical studies at university level with good grades. Regarding teaching in systems analysis (courses MS-C/E2xxx), we expect the applicants to have completed the course they would like to teach. If you have previous experience in teaching, it is considered as an advantage, but is not necessary. This is a part-time job (2-4 hours/week). The salary is 30-40 euros/teaching hour based on your education level.

Grading exercises and exams will be (typically) compensated separately (300-400 euros depending on your education and the course level).

Read carefully! If you are not working for Aalto at the moment you apply, fill in the application form here. If you are working for Aalto at the moment you apply, you have to apply as an internal candidate via Workday, see instructions Sisäisen työpaikan hakeminen | Aalto-yliopisto.

Attach an open motivation letter, a cv and a transcript of records as one PDF file.

Deadline for the applications is Monday 9 May 2022.

Based on the applications, we will invite some of the applicants for a web interview.

More information: johanna.glader@aalto.fi 

Note: if you have previously worked as an hourly-based teacher at the MS Department, you have received a separate link from johanna.glader(at)aalto.fi. 

 

 


Defence of doctoral thesis in the field of mathematics, MSc Milo Orlich, 25.2.2022

11. February 2022

This thesis is in abstract algebra, more specifically in the theory of monomial ideals. The main algebraic objects considered here are polynomials, and all polynomials can be built by summing together monomials, which are products of variables. A monomial ideal is the set of polynomials that one can obtain starting from some fixed monomials. The key idea in this subject is to associate to any monomial ideal a combinatorial object, for instance a graph (also called a network), consisting of nodes and edges. Such a graph is a finite structure that can be easily "counted", and many algebraic properties of the monomial ideal are encapsulated in this graph. Vice versa, starting from a graph one can suitably define a monomial ideal, and tackle graph-theoretic problems from an algebraic point of view.

Some of the main concepts in this subject were defined in the 70's and 90's. However, many fundamental problems remain open. In order to tell graphs apart and understand their behaviour, one can associate numbers to them, like the number of nodes, the number of edges, the number of connected components, etc. There is in fact an infinite family of such numbers, called Betti numbers, that one can associate to a given graph. Starting from some specific basic information about the graph, there are algorithms to determine all the Betti numbers, but one does not know what to expect a priori. One of the main open problems is to give closed formulas that describe the Betti numbers in essentially one line, without going through a long algorithm. The main results of this thesis are in this direction.

In the first paper of the thesis we determine exactly this kind of formulas for a specific class of graphs. In the second paper we generalize this to a larger class of monomial ideals, not necessarily associated to graphs. The third paper introduces a new approach to this subject, using critical graphs, which allow to control the Betti numbers asymptotically.

Opponent: Doctor Emil Sköldberg, National University of Ireland, Ireland

Custos: Professor Alexander Engström, Aalto University School of Science, Department of Mathematics and Systems Analysis

Contact details of the doctoral student: milo.orlich@aalto.fi

The public defence will be organised on campus and via Zoom. Link to the event

The doctoral thesis is publicly displayed 10 days before the defence in the publication archive Aaltodoc of Aalto University.

Electronic thesis


Multidisciplinary research project based on origami seeks solutions for industrial needs

26. January 2022

A joint projectcovering the fields of mathematics, engineering and arts is about to start at Aalto, where the aim is to study and develop folding technology for the needs of industry. In addition to Aalto, the project includes VTT as coordinator, and several companies from the forest industry to the machine design and cosmetics brands, such as Stora Enso, Metsä Group, Lumene, Mirka, Elomatic, Anpap, Orfer and Soften. Business Finland granted funding for the Co-Innovation project.

Folding originates from the origami culture, and the Miura fold and other periodically repeated forms are at the centre of the project. The end products of the project can take a variety of concrete forms, such as packaging, acoustic boards, other room dividers and abrasive products.

Jarkko Niiranen, Associate Professor in Computational Structural Engineering at the School of Engineering, will bring engineer-like knowledge and methods to the project table, for example in the form of quantitative structural analysis.

‘Origami is interesting from the structural point of view. It contains fairly rigid and flat structures, hinges through folds and folding patterns that can produce various shapes and properties. Computer-aided concept and product design, simulation of deformation and structural analysis are all required in folding-based structures. The same methods are used in the design of structural solutions in mechanical and structural engineering, the material, size scale and application are just different.’

According to Niiranen, origami structures have previously been used in biomedicine, where a DNA origami structure folds into a small stack that later opens inside the body. Soft robotics, which aims to mimic organic movement, can also be based on origami. For instance, it is common for aircrafts to have so-called sandwich structures, which typically include a honeycomb core between the skin plates, and the core can be based on origami folding.

‘The project that is about to start will focus on the origami structure as it is, because it is not always necessary, and perhaps not even appropriate, to reinforce the folded structure with skin plates commonly used in sandwich structures. Carefully planned folds can be used to adjust the folding patterns and thus the rigidity as well as the paths and directions of movement, among other things.’

Associate Professor Masood Masoodian and Design Researcher Markus Joutsela, a packaging expert who will solve various challenges related to the functionalities of packages, for example, are both involved in the project from the School of Arts, Design and Architecture. They will also investigate the wider potential of folded structures for effective visual communication in different application areas.

‘It is important to consider how the business world will use the folded structure and how these new solutions could be supported’, Joutsela explains.

‘The project is technology-driven, and we are exploring the possibility of industrial production of different Miura folding structures. While the focus of the research project is on a general level, several of the involved companies share an interest in e-commerce packaging applications and reducing the use of fossil-based packaging materials. The project will create prototypes for different applications. Folding can be used to make truly impressive structures.’

Peltonen approaches the folding properties through mathematical models.

‘The thickness of the material prevents you to fold it infinitely, which would be possible for an extremely thin material that is in line with the ideal mathematical model. On the other hand, the material can have elasticity that allows the folding to succeed in practice, even if the mathematical forecast deems it impossible. Mathematics alone cannot answer these questions, and that is why we need genuine multidisciplinary cooperation.’

The project saw the light of day already in 2017 when VTT developed an interest in folding and launching an industrial project. In 2018–2021 the FinnCERES flagship of Aalto and VTT (funded by the Academy of Finland) that focused on the bioeconomy of materials had a Co-Innovation project focusing on folding, which laid the foundation for this soon-to-begin Co-Innovation project.

 

 

 


Summer internships at the department in 2022

21. December 2021

Department of Mathematics and Systems Analysis at Aalto University School of Science is looking for

interns for the summer of 2022

A summer internship includes research under the supervision of a professor or a person designated by a professor. 

You can find the job ad here. The application period will be 10-25 January 2022 and the related information session will be held on 12 January at 12:15-14:00 in Zoom. 
Link to the information session: https://aalto.zoom.us/j/68663476802

Defence of doctoral thesis in the field of mathematics, LicSc (Tech) Diana Andrei, 10.12.2021

19. November 2021

Title of the doctoral thesis is "Extensions of the multicentric functional calculus"

Opponent is Doctor Jari Taskinen, University of Helsinki, Finland

Custos is Professor Juha KinnunenAalto University School of Science, Department of Mathematics and Systems Analysis

The public defence will be organised on campus.

The doctoral thesis is publicly displayed 10 days before the defence in the publication archive Aaltodoc of Aalto University.

Electronic thesis (link will be added)


Defence of doctoral thesis in the field of mathematics, Msc Joona Karjalainen, 17.12.2021

19. November 2021
Title of the doctoral thesis is "Structure and estimation of network models with overlapping communities"


Opponent is Professor Remco van der Hofstad, Eindhoven university of technology, The Netherlands

Custos is Professor Lasse Leskelä, Aalto University School of Science, Department of Mathematics and Systems Analysis

The public defence will be organised on campus.

The doctoral thesis is publicly displayed 10 days before the defence in the publication archive Aaltodoc of Aalto University.

Electronic thesis (link will be added)


Defence of doctoral thesis in the field of Systems and Operations Research, M.Soc.Sc. Jussi Lindgren, 17.12.2021

19. November 2021
Title of the doctoral thesis is "The Principle of Least Action and Stochastic Dynamic Optimal Control - Applications to Economic, Financial and Physical Systems"

Opponent is Professor Grigorios A. Pavliotis, Imperial College London, UK

Custos is Professor Ahti Salo, Aalto University School of Science, Department of Mathematics and Systems Analysis

The public defence will be organised via Zoom and on campus. Link to the event will be added

Zoom Quick Guide

The doctoral thesis is publicly displayed 10 days before the defence in the publication archive Aaltodoc of Aalto University.

Electronic thesis (will be added)



Postdoctoral Researchers in the general area of Mathematical Physics / Random Geometry / Conformal Field Theory

17. November 2021

The Department of Mathematics and Systems Analysis (http://math.aalto.fi/en/) is seeking 2-3

Postdoctoral Researchers in the general area of Mathematical Physics / Random Geometry / Conformal Field Theory

to work in the research groups of Profs. Eveliina Peltola and Kalle Kytölä. The positions are offered for 2(+1) years, starting between January and October 2022.

The review of applications will begin on December 1st, 2021 (first deadline), and the selection may be done also before the final deadline December 31st, 2021.


Doctoral candidate positions in Mathematics, Operations Research and Statistics

17. November 2021

The Department of Mathematics and Systems Analysis (https://math.aalto.fi/en/) at the Aalto School of Science is seeking several

Doctoral Candidates in Mathematics, Operations Research and Statistics

The candidates will work within one of the department’s main research areas

  • Algebra and discrete mathematics,

  • Analysis and partial differential equations,

  • Numerical analysis,

  • Stochastics, statistics and mathematical physics,

  • Systems and operations research.

The review of applications will begin on 15 December 2021 (first deadline), and decisions may be made already before the final deadline on 16 January 2022 at 23:59 EET (UTC+2).


Postdoctoral Researcher in Algebraic Statistics

17. November 2021

The Department of Mathematics and Systems Analysis (http://math.aalto.fi/en/) at the School of Science is seeking a

Postdoctoral Researcher in Algebraic Statistics

The postdoctoral researcher will work in the research group of Kaie Kubjas. The position is part of the Academy of Finland project “Algebraic geometry of hidden variable models in statistics”. The position is for one year with the starting date on September 1st, 2022.

To guarantee full consideration, the application should be received by December 15, 2021.

Summer 2022 Bridges conference

5. August 2021
In 2022 we are planning to hold an in-person Bridges conference! Join us for invited and contributed talks, hands-on workshops, art galleries and live performance events, and an excursion.

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