MADAM Seminar: Measuring the efficacy of league formats in ranking football teams (Jan Lasek)

On January 5, 2018 at the MADAM (Methods for Analysis of Data: Algorithms and Modeling) seminar, Mr Jan Lasek ( & PhD student @ ICS PAS) will discuss various issues concerning the efficacy of league formats in ranking football (soccer) teams.

Abstract. Choosing between different tournament designs based on their accuracy in ranking teams is an important topic in football since many domestic championships underwent changes in the recent years. In particular, the transformations of Ekstraklasa -- the top-tier football competition in Poland -- is a topic receiving much attention from the organizing body of the competition, participating football clubs as well as supporters. In this presentation we will discuss the problem of measuring the accuracy of different league formats in ranking teams. We will present various models for rating teams that will be next used to simulate a number of tournaments to evaluate their efficacy, for example, by measuring the probability of the best team win. Finally, we will discuss several other aspects of league formats including the influence of the number of points allocated for a win on the final league standings.


Associate Professor @ WUT

I have been promoted to associate professor at the Faculty of Mathematics and Information Science, Warsaw University of Technology.

MADAM Seminar: How accidental scientific success is? (Grzegorz Siudem)

On November 24, 2017 at the MADAM (Methods for Analysis of Data: Algorithms and Modeling) seminar, Dr Grzegorz Siudem (Faculty of Physics, Warsaw University of Technology) will discuss a new agent-based model for citation networks.

Abstract. Since the classic work of de Sola Price the rich-gets-richer rule is well known as the most important mechanism governing the citation network dynamics. (Un-)Fortunatelly it is not sufficient to explain every aspect of bibliometric data. Using the proposed agent-based model for the bibliometric networks we will shed some light on the problem and try to answer the important question stated in the title. Joint work with A. Cena, M. Gagolewski and B. Żogała-Siudem.

2017-04-07 software

stringi 1.1.6 released

Another release of the stringi package for R is on CRAN. The package is one of the most downloaded R extensions and provides a rich set of string processing procedures.


* [WINDOWS SPECIFIC] #270: Strings marked with `latin1` encoding
are now converted internally to UTF-8 using the WINDOWS-1252 codec.
This fixes problems with - among others - displaying the Euro sign.

* [NEW FEATURE] #263: Add support for custom rule-based break iteration,
see `?stri_opts_brkiter`.

* [NEW FEATURE] #267: `omit_na=TRUE` in `stri_sub<-` now ignores missing values
in any of the arguments provided.

* [BUGFIX] fixed unPROTECTed variable names and stack imbalances
as reported by rchk
2017-10-24 software

TurtleGraphics v1.0-7

A bugfix release of the TurtleGraphics package for R is now available for download from CRAN.


Today I have been awarded a habilitation degree, thesis title: New algorithms for data aggregation and analysis: construction, properties, and applications.

Research Visit @ Deakin University

From July 17 until August 8, 2017 I shall be visiting Dr Simon James, Prof. Gleb Beliakov, Dr Tim Wilkin and their colleagues at the School of Information Technology, Deakin University in Burwood, Victoria, Australia. The support by the SEBE Researcher in Residence 2017 Program from Deakin University is fully acknowledged.
2017-07-06 new paper

Measuring Traffic Congestion

Measuring traffic congestion: An approach based on learning weighted inequality, spread and aggregation indices from comparison data has been accepted for publication in Applied Soft Computing. Assigned DOI is 10.1016/j.asoc.2017.07.014. Simon James did a wonderful work leading this research project. The paper was written in collaboration with researchers from Deakin University, namely: Gleb Beliakov, Shannon Pace, Nicola Pastorello, Elodie Thilliez, and Rajesh Vasa.
Abstract. As cities increase in size, governments and councils face the problem of designing infrastructure and approaches to traffic management that alleviate congestion. The problem of objectively measuring congestion involves taking into account not only the volume of traffic moving throughout a network, but also the inequality or spread of this traffic over major and minor intersections. For modelling such data, we investigate the use of weighted congestion indices based on various aggregation and spread functions. We formulate the weight learning problem for comparison data and use real traffic data obtained from a medium-sized Australian city to evaluate their usefulness.