Luiz G. A. Alves

Luiz G. A. Alves

Postdoctoral fellow

Northwestern University

About me

I am a Postdoctoral Fellow in the Amaral-Lab at Northwestern University. Previously, I was a postdoct at the Institute of Mathematics and Computer Science at the University of São Paulo. I have a bachelor’s degree in Physics (2012), a master’s degree in Physics (2014), and a Ph.D. degree in Physics (2017) from State University of Maringá.

The focus of my research is driven by the need to contribute solutions to some of the most challenging problems of this century: climate change, economic inequalities, and violence. For example, I address questions such as how can we design better transportation networks that help reduce greenhouse gas emissions? how can we promote more inclusive urban systems? how can we reduce crime and gun violence in cities?

To tackle such questions, I use data science tools, including regression, spatial, and time series analysis, clustering techniques, supervised machine learning, computer vision, and complex networks. I also rely on concepts from statistical physics (scaling, universality, criticality, and phase-transition), information theory, and complex systems (emergent behavior, self-organization, nonlinearity, and adaptation).

I have successfully pursued these approaches in interdisciplinary collaborations with physicists, computer scientists, engineers, economists, criminologists, and biologists and I have published my work in multi-disciplinary journals (Physical Review Letters, Journal of Complex Networks, Scientific Reports, PLoS ONE, etc). My publications have received more than 600 citations (Google Scholar) and was also extensively covered by the media (BBC, Wired, El País, MIT review of technology, etc). I have also been consulted as a referee for several journals in the area of physics, complex systems, and data science, including journas such as Physical Review Letters, Proceedings of the National Academy of Sciences, Nature Communications, and Journal of the Royal Society Interface.

Download my CV.

Interests
  • Data Science
  • Machine Learning
  • Complex Systems
  • Network Theory
  • Statistical Physics
Education
  • PhD in Physics, 2017

    State University of Maringá

  • MSc in Physics, 2014

    State University of Maringá

  • BSc in Physics, 2012

    State University of Maringá

Skills

Programming
Statistics
Machine Learning

Experience

 
 
 
 
 
Postdoctoral Fellow at McCormick School of Engineering
Nov 2018 – Present Evanston, IL - USA
 
 
 
 
 
Postdoctoral Fellow at Institute of Mathematics and Computer Science
Apr 2017 – Oct 2018 São Carlos, SP - Brazil
 
 
 
 
 
Visiting Scholar at McCormick School of Engineering
Nov 2015 – Oct 2016 Evanston, IL - USA
 
 
 
 
 
Graduate Research Assistant at the Department of Physics
Mar 2013 – Mar 2017 Maringá, PR - Brazil

Research

Teaching

 
 
 
 
 
Instructor
Sep 7, 2021 – Sep 16, 2021 Northwestern University - Northwestern Institute of Complex Systems, Evanston, IL - USA

NICO101/NICO401 - Introduction to Programming for Big Data:

 
 
 
 
 
Invited Lecturer
Jul 1, 2019 – Jul 6, 2019 University São Paulo - Institute of Mathematics and Computer Science, São Carlos, SP - Brazil

School of Applied Mathematics - Crime and political corruption analysis using data mining, machine learning and complex networks:

  • Program: The accumulation of large amounts of data by private or public initiatives is increasingly common. On the one hand, these data allow a detailed historical review of the process in question; on the other, information overload makes it very difficult to extract summary information and make decisions supported by empirical facts. This modern phenomenon has been called big data and understanding these systems and extracting patterns from these data requires a multidisciplinary approach. During this course at the School of Applied Mathematics at ICMC, we address topics involving computer science, statistics, and physics. Among them, we focus on the following topics:



    • Introduction to python, scraping and data mining;
    • Machine learning;
    • Complex networks.

    Using these tools, we will focus on two issues that are of great relevance in Brazil: the prediction of homicides in cities and the description of the mechanism behind political corruption networks. In the first theme, we will use machine learning techniques to predict the number of crimes in Brazilian cities. In the second theme, we will use complex networks to describe the interaction between politicians investigated in corruption scandals in Brazil from 1987 to 2014.

  • Web Page: School of Applied Mathematics

  • Jupyter notebooks: Crime and political corruption analysis using data mining, machine learning and complex networks

 
 
 
 
 
Invited Lecturer
Apr 23, 2018 – Apr 23, 2018 FGV - Brazilian School of Public and Business Administration, Rio de Janeiro, RJ - Brazil

Graduate Seminars - The dynamical structure of political corruption:

  • Program:Data collection of corruption networks. Growth dynamics of the number of people involved in corruption scandals. Network representation of corruption scandals. Evolution of the corruption network. Predicting missing links in corruption networks.

  • Web Page: Graduate Seminars 2018

 
 
 
 
 
Invited Lecturer
Apr 23, 2018 – Apr 23, 2018 State University of São Paulo - Department of Mathematics, Jaboticabal, SP - Brazil

Workshop - Web scraping, data mining, and machine learning using Python:

 
 
 
 
 
Teaching Assistant
Jun 1, 2017 – Dec 20, 2017 University São Paulo - Institute of Mathematics and Computer Science, Department of Statistics, São Carlos, SP - Brazil

Scientific methodology II:

  • Program: Introduced to the student the organization of academic work and develop the ability to compile a data analysis project, emphasizing the importance of the written form for reporting results. The topics discussed during the course includes how to write a technical report, ethics and research, the participation in projects of other statistical areas of knowledge, and standards of citations and references.

 
 
 
 
 
Teaching Assistant
Jan 1, 2014 – Jun 30, 2014 State University of Maringá - Department of Chemical Engineering, Maringá, PR - Brazil

Physics I:

  • Program: Kinematics and particle dynamics. Newton's laws. Conservation laws. Kinematics and rotation dynamics. Conceptual applications of physics and mathematics as a basis for the understanding of Physics I.

 
 
 
 
 
Teaching Assistant
Jan 1, 2014 – Jun 30, 2014 State University of Maringá - Department of Civil Engineering, Maringá, PR - Brazil

Physics I:

  • Program: Electrostatic. Current and electrical resistance. Electromotive force and electrical circuits. Magnetostatic. Time-dependent electromagnetic phenomena.

 
 
 
 
 
Teaching Assistant
Jun 1, 2013 – Dec 20, 2013 State University of Maringá - Department of Civil Engineering, Maringá, PR - Brazil

Methods of Approximation in Physics:

  • Program: Analytical and discrete approximation methods applied to physical problems.

Talks

Coming soon

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Media Coverage

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