Research and innovation projects
Organized conferences
18th Workshop on Algorithms and Models for the Web Graph, 2023, Fields Institute, Toronto
17th Workshop on Algorithms and Models for the Web Graph, 2020
Workshop on Hypergraphs — Theory and Applications, 2020, Fields Institute, Toronto
Summer School on Data Science Tools and Techniques in Modelling Complex Networks, 2019, Fields Institute, Toronto
Blockchain Technology Symposium BTS2018, Fields Institute, Toronto
International Conference on Group Decision & Negotiation 2015
Julia
I am the main co-author (maintaining code repositories) and maintain four officially registered Julia language libraries:
- OpenStreetMapX.jl – tools for working with data in the Open Street Map format, allowing for spatial data processing for constructing complex system models in the transport space. These tools enable the creation of data sources within the optimization and simulation models.
- OpenStreetMapXPlot.jl – tools for visualizing maps in transport system studies.
- SimpleHypergraphs.jl – tools for modeling and analyzing the properties of hypergraphs. Hypergraphs enable, among other things, modeling information asymmetry and multilateral connections in economic systems.
- OSMToolset.jl – tools for extracting spatial data from open map repositories for complex system modeling. I created this project as part of the NCN OPUS 2021/41/B/HS4/03349 project I lead.
SilverDecisions
I am co-author of application SilverDecisions.
The software allows for creation and analysis of decision trees.
The application can be used in web browser at http://silverdecisions.pl. The software has been selected by the European Commission (the executive body of the European Union) for the Innovation Radar Programme, which identifies the best innovations in Europe funded by the European Union (Innovation Radar - https://innovation-radar.ec.europa.eu/innovation/29875). The tool has been featured, among others, in studies outside the presented publication cycle – Kamiński et al. (2018) and Szufel et al. (2022).
D-MASON in the cloud
The D-MASON enviroment enables execution of distributed multi-agent simulation models. In cooperation with ISISLab Salerno University (Italy) I work on tool that will automate creation of distributed computing clusters in the Amazon Web Services cloud. The tool will be created as a plugin to the MIT StarCluster enviroment - one of the most popular HPC tools for the cloud.
SOF: Zero Configuration Simulation Optimization Framework on the Cloud
SOF is a toolset that utilizes the map-reduce model along with the Hadoop platform for HPC computations in the cloud.
The source code along with the technical documentation can be obtained at https://github.com/isislab-unisa/sof.
A detailed project concept is described in the paper:
M. Carillo, G. Cordasco V., Scarano, F. Serrapica, C. Spagnuolo., P. Szufel, SOF: Zero Configuration Simulation Optimization Framework on the Cloud, In Proc. of 24th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, Heraklion,Crete, 2016.
Starcluster quick cloud setup
I have created a bash temaplate that enables rapid computing cluster creation in the cloud.
Starting is simple - just create any Ubuntu instance (e.g. t2.micro) in the Virginia region, copy credentials.csv file to /home/ubuntu and run the following commands
wget https://szufel.pl/sc_setup.sh bash sc_setup.sh
ROUTE-TO-PA
"Raising Open and User-friendly Transparency-Enabling Technologies for Public Administrations" (ROUTE-TO-PA) is a reasearch project financed by the 8th EU Framework Programme - Horizon 2020
ROUTE-TO-PA is an innovation project aimed at creating tools and software for increasing transparency of public administration.
The goal of the Decision Support and Analysis Division team is to create a multi-agent simulation tool to analyse preference elicitation in heterogenous communities.
The project web site is available at http://www.routetopa.eu/
Asynchronous Knowledge Gradient
Asynchronous Knowledge Gradient algorithm enables distributed stochasic optimization computations for ranking & selection problems.
Implementation in Java language of the Asynchronous Knowledge Gradient algorithm can be downloaded here.
Documentation of the algorithm is presented in paper:
B. Kamiński, P. Szufel: Asynchronous Knowledge Gradient Policy for Ranking and Selection, Winter Simulation Conference, Proceedings of the 2014 Winter Simulation Conference, A. Tolk, S. Y. Diallo, I. O. Ryzhov, L. Yilmaz, S. Buckley, and J. A. Miller, eds., s. 3785-3796, 2014
PyCX
Together with Bogumił Kamiński we take part in development of Project PyCX.
PyCX enables creation and visualistion models in Python. The main package application is educational.