About me

Sandro is a computer scientist interested in spatial complexity, random walks on graphs, population dynamics, urban segregation, algorithmic fairness and the quantification of these phenomena through graphs and data models.

Currently, he is a Postdoc in the NEtwoRks, Data, and Society Group (NERDS) at IT University of Copenhagen and a visiting Postdoc at (SODAS). His research concentrates on quantifying algorithmic fairness and bias in Science of Science through randomised controlled experiments and analysis of large datasets of academic publications.

He has a PhD in Complex Systems at The School of Mathematical Sciences, Queen Mary University of London, with supervision by Vincenzo Nicosia. His PhD research focused on quantifying the heterogeneity of spatial systems through random walks on graphs with a particular interest on urban segregation. Previously he had worked as a research associate on a project between Brazilian and British academics entitled RESOLUTION where the cities of London and São Paulo were compared for social segregation and transport accessibility. His MSc used a graph-based approach to quantify topological changes in Sao Paulo’s public transport network at different spatial scales while tested the robustness of the system against simulated attacks. Before the research career, he worked on IT consulting and data solutions for more than 7 years.

Download my resumé.

  • Complex Networks
  • Spatial Complexity
  • Science of Cities
  • Computational Social Science
  • Algorithmic fairness and bias
  • PhD in Mathematical Sciences, 2021

    Queen Mary University of London

  • MSc in Complex Systems Modelling, 2015

    University of Sao Paulo

  • PG Cert in Information Management and Business Intelligence, 2013

    Business School Sao Paulo

  • BSc in Computer Network Management, 2008

    College Inforium of Technology


Nov 2021 – Present Copenhagen, DK
Postdoc in Science of Science and Algorithmic fairness.
PhD Researcher
Sep 2017 – Dec 2021 London, UK
PhD in Mathematical Sciences. Research on quantifying spatial heterogeneity of complex systems through random walks on graphs.
Research Associate
May 2016 – May 2017 São Paulo/London, BR/UK
Research Associate at the Centre for Metropolitan Studies (USP, BR) in collaboration with the Centre for Advanced Spatial Analysis (CASA - UCL, UK) for the study of segregation dynamics. Analysis of population data, spatial data (GIS) and ABM modelling.
Business Intelligence Architect
Dec 2011 – Jun 2014 São Paulo, BR
Management of business Intelligence projects (full cycle). Design, development and deployment of data solutions.
Business Intelligence Consultant
Oct 2010 – Dec 2011 São Paulo, BR
Design, development and deployment of business Intelligence solutions on the SAP platform.
Business Consultant
Oct 2010 – Feb 2010 São Paulo, BR
Design, development and deployment of business processes on the TOTVS platform.
Business Analyst
Aug 2009 – Feb 2010 Maringá, BR
Design, development and deployment of business processes on the TOTVS platform.

Academic Activities

Scholarships and Grants

  • 2019 CSS Scholarship for the Mediterranean School of Complex Networks, Salina, Fondazione Bruno Kessler.
  • 2019 yrCSS Travel Grant for the Complexity72h Workshop, IMT School for Advanced Studies Lucca.
  • 2017 Research Studentship Queen Mary Principal’s Award, QMUL.
  • 2016 Research Scholarship Technical Training Award, Sao Paulo Research Foundation (FAPESP).
  • 2016 Travel Grant for the Summer School on Understanding Urban Transformations thought Data, Manchester School of Architecture.
  • 2014 Research Studentship Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, CAPES.

Conferences, Schools and Workshops

  • Sep 2020 International School and Conference on Network Science (NetSci)
    Rome, IT (Online).
  • Dec 2019 Alan Turing Institute Data Study Group
    London, UK. Data challenge: The National Archives.
  • Sep 2019 Mediterranean School of Complex Networks
    Salina, IT.
  • Jul 2019 3rd UK Network Science Workshop
    Leeds, UK.
  • Jul 2019 International Workshop on Networks and Urban Systems,
    London, UK.
  • Jul 2019 Complexity72h Workshop
    Lucca, IT.
  • Oct 2018 2nd Network Science Workshop
    London, UK.
  • Sep 2018 Conference on Complex Systems (CCS)
    Thessalokini, GR. Talk: Quantifying spatial heterogeneity through random walks.
  • Jun 2018 International Conference on Network Science (NetSci)
    Paris, FR.
  • May 2018 Network Micro-structures Workshop
    London, UK.
  • Apr 2018 The Second King’s Workshop on Random Graphs and Random Processes
    London, UK.
  • Jan 2018 Next Generation Network Analytics
    London, UK.
  • Sep 2016 DACAS Summer school on Understanding Urban Transformations through Data
    Manchester, UK. Talk: Public transportation as a complex network.
  • Jun 2016 DACAS/ICTP Workshop on Modelling of Urban Systems
    Sao Paulo, BR.
  • Mar 2016 Workshop on Agent-Based Modelling for Social Sciences
    Sao Paulo, BR.
  • Sep 2015 Complex Systems Digital Campus ’15 – World
    e-Conference. Talk: Empirical analysis and modeling of urban public transport network of Sao Paulo.
  • Sep 2015 School on Complex Networks and Applications to Neuroscience
    Sao Paulo, BR.


I’ve been Demonstrator for the following courses at QMUL:

  • 2019 - 2020 Introduction to Computer Programming in Python (MTH5001).
  • 2018 - 2019 Probability and Statistics I (MTH4116/MTH4216).


Software, books, websites, datasources, etc. Resources arbitrarily categorised.

Useful software

Network analysis
Graph-tool | NetworkX | igraph | SNAP Stanford Network Analysis Project | OSMnx Street networks | Hive Plots | NetBunch

Network analysis - no coding
Cytoscape | Gephi

Large networks analysis
Large Network Visualization Tool | Multinet Large multi-layered graphs | Cosmograph Visual analytics for big graphs

Power-law Distributions | GNU Parallel, Shell tool for jobs in parallel

Network analysis with R and igraph: NetSci Tutorial | Static and dynamic network visualization with R | Temporal networks with R and igraph | Network Analysis Made Simple

Visualising and representing Data

Matplotlib Parts of a Figure | Python_Matplotlib_Cheat_Sheet | Colormaps in Matplotlib | List of named colors Matplotlib | Choosing color palettes seaborn | ColorBrewer Color Advice for Maps | Create a palette Coolors | What to consider when choosing colors

Data Art
Kirell Benzi | Information is Beautiful Awards | Data design and storytelling Tiziana Alocci

Data viz
Chartable | Find the graphic you need | Free Logo Maker | scientific-visualization-book | Redundant coding, text annotations | Streamline Icon Library | That ole Illustrator magic | The Python Graph Gallery


Index of Complex Networks | Netzschleuder the network catalogue | Network Data Repository | KONECT The Koblenz Network Collection | Stanford Large Network Dataset Collection

BlackDemographics US | Colouring London | data.europa.eu | Datasets UBDC Data Portal | GoodCityLife | SoBigData.eu | Metroverse Harvard Growth Lab | Office for National Statistics | OpenAlex The open catalog to the global research system | QuantUrb | DataShine Census | Our World in Data | Humanitarian Data Exchange

Overpass turbo | TIGER/Line® Shapefiles | IPUMS NHGIS | National Historical Geographic Information System | Mapzen

TransitFeeds | Transitland

Free reading material

Network Science
Glossary of graph theory terms | Network Science book by A. Barabási | The Atlas for the Aspiring Network Scientist

Complexity Explorer | Think Complexity 2e | Complexity Explained | Complexity Digest | Complexity Explorables

3blue1brown | Encyclopedia of Mathematics | Guide To The Fourier Transform | List of mathematical symbols | Random: Probability, Mathematical Statistics, Stochastic Processes | Wolfram Alpha | Sybolab math solver

Other collections

Resources Amaral Lab

Awesome lists
awesome-network-analysis | awesome-understanding-math | awesome-math | awesome-dataviz | awesome-datascience | awesome-computational-social-science | awesome-python | awesome-causality | awesome-nlp | speech-language-processing | awesome-open-science | awesome-quarto


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