Docente
Nuno Maria Carvalho Pereira Fernandes Fachada

Nuno Maria Carvalho Pereira Fernandes Fachada
nun***@ulusofona.pt
E111-7012-9FCC
0000-0002-8487-5837

Resume

Nuno Fachada is an Assistant Professor at Universidade Lusófona de Humanidades e Tecnologias (ULHT) and a researcher at COPELABS research unit at the same University, while also collaborating with HEI-Lab (ULHT) and LaSEEB/ISR (Instituto Superior Técnico/IST) research units. He is currently teaching Programming and Artificial Intelligence at the Videogames Bachelor of Arts (of which he is also the Vice-Director) and Research Software at the Computer Science PhD program. Nuno's main research interests lie in Research Software, Machine Learning, Artificial Intelligence, Modeling and Simulation, High Performance Computing and Computer Science Education. He completed his degree in Electrical and Computer Engineering from IST in 2005, and went on to pursue a master degree (M.Sc.) in the same institute on the topic of immune system simulation, from which he graduated in 2008. During this period Nuno was a teaching assistant at IST, lecturing subjects such as Programming, Digital Systems, Microprocessors and Computer Architectures. He successfully defended his PhD thesis in 2016 (IST), entitled "Agent-Based Modeling on High Performance Computing Architectures", for which he was awarded the maximum grade "Pass with Distinction and Honour". After a year as a postdoctoral researcher at LaSEEB/ISR, Nuno moved to his current position at COPELABS/ULHT.

Graus

  • Licenciatura
    Licenciatura em Engenharia Electrotécnica e de Computadores (5 year degree, pre-Bologne)
  • Mestrado
    Masters Degree in Electrical and Computer Engineering (Pre-Bologna)
  • Doutoramento
    Doctorate Degree in Electrical and Computer Engineering

Publicações

Dataset

  • Usage examples for the micompr R package, This repository contains concrete application examples for the micompr R package, which implements a procedure for comparing multivariate samples associated with different groups.
  • Snappable Meshes Performance Dataset, This dataset contains performance and navigation benchmarks obtained by generating eight maps with the snappable meshes algorithm multiple times.
  • Retail fuzzy cognitive map dataset, This dataset contains experts interview results for the Fuzzy Cognitive Map of the retail system, reported influences from the published articles in the domain, and aggregated weighted matrix of influences in the retail system. Based on this dataset Fuzzy Cognitive Map of the retail system was generated. Obtained map used for system analysis and scenario planning in the retail business.
  • Reference data sets for benchmarking clustering algorithms, These data sets were used as clustering benchmarks in the following publication: Fachada, N., Figueiredo, M.A.T., Lopes, V.V., Martins, R.C., Rosa, A.C., Spectrometric differentiation of yeast strains using minimum volume increase and minimum direction change clustering criteria, Pattern Recognition Letters, vol. 45, pp. 55-61 (2014), doi: 10.1016/j.patrec.2014.03.008
  • PPHPC ParStrat Datasets, These are the datasets used in the article "Parallelization strategies for spatial agent-based models" by Fachada, N., Lopes, V.V., Martins, R.C. and Rosa, A.C. (2016), published in the International Journal of Parallel Programming. DOI: 10.1007/s10766-015-0399-9. The data is divided into two parts: 1. Simulation output 2. Simulation duration and CPU usage
  • PPHPC OpenCL-Thesis Datasets, These are the datasets used for the CPU and GPU OpenCL results in the PhD thesis "Agent-Based Modeling on High Performance Computing Architectures" by Nuno Fachada (2016).
  • PPHPC NetLogo Datasets, These are the datasets used in the article "Towards a standard model for research in agent-based modeling and simulation" by Fachada, N., Lopes, V.V., Martins, R.C. and Rosa, A.C., available at https://peerj.com/articles/cs-36/.
  • PPHPC MIComp Datasets, These are the datasets used in the following study: Fachada, N., Lopes, V.V., Martins, R.C. and Rosa, A.C., Model-independent comparison of simulation output. Simulation Modelling Practice and Theory, 72:131–149, 2017, http://dx.doi.org/10.1016/j.simpat.2016.12.013 (arXiv version available at http://arxiv.org/abs/1509.09174)
  • PPHPC Java vs OpenCL-CPU Datasets, These datasets contain the results from a performance comparison between Java and OpenCL/CPU implementations of the PPHPC model.
  • MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification, This dataset contains 10,917 news articles with hierarchical news categories collected between January 1st 2019, and December 31st 2019 classified by using NewsCodes Media Topic taxonomy. We manually labelled the articles based on a hierarchical taxonomy with 17 first-level and 109 second-level categories. This dataset can be used to train machine learning models for automatically classifying n
  • ColorShapeLinks 2019/20 Grades Dataset, This dataset contains grades (0-20 scale) given to students in the context of the ColorShapeLinks AI assignment during the two semesters of the 2019/20 academic year. A number of results presented in the research paper "ColorShapeLinks: A Board Game AI Competition for Educators and Students" are obtained from this dataset.

Journal article

  • 2022-10-17, Uavnoma: A UAV-NOMA Network Model under Non-Ideal Conditions, Journal of Open Research Software
  • 2022-08-01, Unity Snappable Meshes, Software Impacts
  • 2022-07-01, TextCL: A Python package for NLP preprocessing tasks, SoftwareX
  • 2022-06, Drop Project: An automatic assessment tool for programming assignments, SoftwareX
  • 2022-05-13, Retail System Scenario Modeling Using Fuzzy Cognitive Maps, Information
  • 2022-04-20, Procedural Generation of 3D Maps with Snappable Meshes, IEEE Access
  • 2022-04, Enlarged PLIN5-stripped lipid droplets in inner regions of skeletal muscle type II fibers associate with Type 2 Diabetes, Acta Histochemica
  • 2021-02-23, ColorShapeLinks: A Board Game AI Competition for Educators and Students, Computers and Education: Artificial Intelligence
  • 2020-10, Population Sizing of Cellular Evolutionary Algorithms, Swarm and Evolutionary Computation
  • 2020-05-22, generateData—A 2D data generator, Software Impacts
  • 2020, Generative Art with Swarm Landscapes, Entropy
  • 2019-08-26, Steady state particle swarm, PeerJ Computer Science
  • 2018-08-27, Teaching database concepts to video game design and development students, Revista Lusófona de Educação
  • 2018-03, micompm: A MATLAB/Octave toolbox for multivariate independent comparison of observations, Journal of Open Source Software
  • 2017-09, cf4ocl: A C framework for OpenCL, Science of Computer Programming
  • 2017-07, Parallelization Strategies for Spatial Agent-Based Models, International Journal of Parallel Programming
  • 2017-03, Model-independent comparison of simulation output, Simulation Modelling Practice and Theory
  • 2016-12-31, micompr: An R Package for Multivariate Independent Comparison of Observations, The R Journal
  • 2016-10-21, SimOutUtils – Utilities for Analyzing Time Series Simulation Output, Journal of Open Research Software
  • 2016-05-12, PerfAndPubTools – Tools for Software Performance Analysis and Publishing of Results, Journal of Open Research Software
  • 2015-11-25, Towards a standard model for research in agent-based modeling and simulation, PeerJ Computer Science
  • 2014-08, Spectrometric differentiation of yeast strains using minimum volume increase and minimum direction change clustering criteria, Pattern Recognition Letters
  • 2012, TopoCell – An image analysis tool to study intracellular topography, The FASEB Journal
  • 2008-09-15, Simulations of Antigenic Variability in Influenza A, Nature Precedings

Conference paper

  • 2022-04-24, A Computational Pipeline for Modeling and Predicting Wildfire Behavior, COMPLEXIS 2022: 7th International Conference on Complexity, Future Information Systems and Risk
  • 2021-06-27, PyXYZ: an educational 3D wireframe engine in Python, ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE '21)
  • 2020-11-27, Procedural Game Level Generation by Joining Geometry with Hand-Placed Connectors, Videojogos 2020 - 12th International Conference on Videogames Sciences and Arts
  • 2020-06-17, Top-down Design of a CS Curriculum for a Computer Games BA, ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE '20)
  • 2020-06, Fun maths for all game development students, ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE '20)
  • 2019-09-13, Desafios no ensino da programação a alunos de Videojogos, Atas do 1.º SEVj - Seminário Sobre Ensino de Videojogos
  • 2018, Revisiting Population Structure and Particle Swarm Performance, International Joint Conference on Computational Intelligence
  • 2018, Particle swarm and population structure, Genetic and Evolutionary Computation Conference Companion on - GECCO '18
  • 2017-05, Assessing the feasibility of OpenCL CPU implementations for agent-based simulations, 5th International Workshop on OpenCL - IWOCL 2017
  • 2009-10-05, Artificial Life Model of Dengue Host-Vector Disease Propagation, International Joint Conference on Computational Intelligence
  • 2009-03, Simulating antigenic drift and shift in influenza A, 2009 ACM symposium on Applied Computing
  • 2008, Simulation of immune system response to bacterial challenge, European Simulation and Modelling Conference
  • 2007-12, Agent Based Modelling and Simulation of the Immune System: a Review, Portuguese Conference on Artificial Intelligence

Other output

  • 2022-01-07, Snappable Meshes PCG, The Snappable Meshes PCG technique consists of a system of connectors with pins and colors which constrains how any two map pieces (i.e., meshes) can snap together. Through the visual design and specification of these connection constraints, and an easy-to-follow generation procedure, the method is accessible to game designers and/or other non-experts in PCG, AI or programming.
  • 2021-07-12, ColorShapeLinks, an AI competition for the IEEE CoG conference, ColorShapeLinks is an AI competition for the Simplexity board game with arbitrary game dimensions, which ran in the 2020 and 2021 editions of the IEEE CoG conference.
  • 2020-05-30, generateData: 2D data generator, A MATLAB/Octave script which generates 2D data for clustering; data is created along straight lines, which can be more or less parallel depending on the selected input parameters
  • 2020-01-03, CoreGameEngine: a .NET Core console-based game engine for educational purposes
  • 2019-12-19, AIUnityExamples: Artificial intelligence examples in Unity
  • 2019-12-17, libGameAI: a .NET Standard 2.0 library of AI algorithms for video games
  • 2019-12-05, OpenPSO: an efficient, modular and multicore-aware framework for Particle Swarm Optimization
  • 2019-10-28, Oclgrind - An OpenCL device simulator and debugger
  • 2019-09-10, PerfAndPubTools - Performance analysis and publishing tools, A set of MATLAB/Octave functions for analyzing software performance benchmark results and producing associated publication quality materials
  • 2019-08-28, cf4ocl: C framework for OpenCL, The C Framework for OpenCL, cf4ocl, is a cross-platform pure C object-oriented framework for developing and benchmarking OpenCL projects
  • 2019-08-27, pval_adjust - MATLAB/Octave function for adjusting p-values for multiple comparisons
  • 2018-09-03, micompr: Multivariate independent comparison of observations, The micompr R package implements a procedure for comparing multivariate samples associated with different groups
  • 2018-07-30, micompm: Multivariate independent comparison of observations, micompm is a MATLAB/Octave port of the original micompr R package for comparing multivariate samples associated with different groups
  • 2017-08-18, SimOutUtils - Utilities for analyzing time series simulation output, A number of MATLAB/Octave functions for analyzing output data from simulation models, as well as for producing publication quality tables and figures
  • 2017-05-18, PPHPC: Predator-Prey for High-Performance Computing, A standard model for research in agent-based modeling and simulation
  • 2016-09-04, CL_Ops, A library of common OpenCL operations
  • 2016-01-12, AMVIDC Clustering Algorithm, Clustering algorithm based on agglomerative hierarchical clustering (AHC) which uses minimum volume increase (MVI) and minimum direction change (MDC) as clustering criteria
  • 2016-01-09, TopoCell - an image analysis tool to study intracellular topography
  • 2013-08-31, LAIS1 - A transparent multithreaded 2D agent-based simulator based on RepastJ

Book chapter

  • 2022, SimpAI: Evolutionary Heuristics for the ColorShapeLinks Board Game Competition, Videogame Sciences and Arts, VJ 2020, 1531, Springer International Publishing
  • 2017, Verifying and Validating Simulations, Understanding Complex Systems, Springer International Publishing
  • 2011, Agent-Based Model of Dengue Disease Transmission by Aedes aegypti Populations, Advances in Artificial Life. Darwin Meets von Neumann, 5777, Springer Berlin Heidelberg
  • 2009, Agent-Based Model of Aedes aegypti Population Dynamics, Progress in Artificial Intelligence, 5816, Springer Berlin Heidelberg

Magazine article

  • 2021-10-06, Dimensionamento de populações de algoritmos evolutivos celulares, Técnica. Revista da Associação de Estudantes do Instituto Superior Técnico

Conference abstract

  • 2018-04-19, Biofeedback Game Design, Play2Learn 2018
  • 2011-06, Batch Processing of Intramyocellular Biomolecule Localization, Scandem 2011 - 62nd Meeting of the Scandinavian Microscopy Society

Online resource

  • 2017-10, Lusófona Videogames GitHub Page, https://github.com/VideojogosLusofona
  • 2014, LaSEEB GitHub Page, https://github.com/LaSEEB

Conference poster

  • 2017-06, A method for detecting statistically significant differences in EEG data, 2017 Annual Meeting of the Organization for Human Brain Mapping

Thesis / Dissertation

  • 2016-09-13, PhD, Agent-Based Modeling on High Performance Computing Architectures
  • 2008-07, Master, Agent-based Simulation of the Immune System
  • 2005-12, Degree, SimulIm: an application for the modelling and simulation of Complex Systems, using the Immune System as an example

Preprint

Journal issue

Email


Política de Cookies
Este website utiliza cookies para lhe proporcionar uma melhor experiência de navegação.
Aceitar
Lisboa 2020 Portugal 2020 Small Logo EU small Logo PRR Logo UE Financed Logo PT Livro de reclamaões Elogios