Bruno Focassio

Bruno Focassio

PhD candidate
Nanoscience and Advanced Materials

Universidade Federal do ABC

About me

I am a fourth-year PhD student in Nanoscience and Advanced Materials at the Federal Univerisity of ABC (Brazil), under the supervision of Prof. Adalberto Fazzio. During 2022, I was visiting the Computational Spintronics Group in the School of Physics in Trinity College Dublin (Ireland), under the supervision of prof. Stefano Sanvito. My main interest is using data analysis, machine learning, materials informatics, and data-driven techniques to explore the materials phase space to achieve efficient design and discovery of materials. My PhD thesis includes using data science and machine learning applied to materials science to discover and design new materials.

Interests
  • Data Science
  • Machine Learning
  • Computational Materials Science & Engineering
Education

  • PhD in Nanoscience and Advanced Materials, 2019-present

    Universidade Federal do ABC

  • BEeng in Materials Engineering, 2019

    Universidade Federal do ABC

  • BSc in Science and Technology, 2017

    Universidade Federal do ABC

Projects

How lignin sticks to cellulose—insights from atomic force microscopy enhanced by machine-learning analysis and molecular dynamics simulations
Application of data analysis and machine learning on experimental data. Data cleaning and transformation. Noise reduction with PCA. Time series clustering.
Check publication
How lignin sticks to cellulose—insights from atomic force microscopy enhanced by machine-learning analysis and molecular dynamics simulations
Linear Jacobi-Legendre expansion of the charge density for machine learning-accelerated electronic structure calculations
Fingerprint coding. Data transformation. Regression Analysis. Deployment of regression model to application.
Check publication Check data on Zenodo Check GitHub tutorial
Linear Jacobi-Legendre expansion of the charge density for machine learning-accelerated electronic structure calculations
Machine learning for materials discovery: Two-dimensional topological insulators
Data mining. Feature transformation & Feature Engineering. Classification model. Model deployment to discover new materials.
Check publication
Machine learning for materials discovery: Two-dimensional topological insulators
Machine learning of microscopic ingredients for graphene oxide/cellulose interaction
Feature transformation & feature engineering. Insights from regression and classification models. Data visualization.
Check publication
Machine learning of microscopic ingredients for graphene oxide/cellulose interaction

Skills

Python
SQL
Tableau
pandas
scikit-learn
Data Analysis
Exploratory Data Analysis (EDA)
Data Visualization
Machine Learning

Regression, Classification, Clustering

Predictive Modelling
Statistical Analysis
A/B Testing
Deep Learning

TensorFlow, PyTorch

Problem-Solving
Effective Written Communication

Experience

 
 
 
 
 
Brazilian Center for Research in Energy and Materials (CNPEM)
Associate Researcher (PhD student)
Brazilian Center for Research in Energy and Materials (CNPEM)
February 2019 – Present Campinas, Brazil
  • Collaboration with experimental scientists.
  • Data Mining and Statistical Analysis of experimental data.
  • Insights from machine learning models (regression and classification).
  • Interpretation of time series data using clustering.
  • Data visualization and presentation.
 
 
 
 
 
Trinity College Dublin
Visiting Research Fellow (PhD student)
Trinity College Dublin
February 2022 – February 2023 Dublin, Ireland
Machine learning and Predictive modelling for two-dimensional materials’ properties at the Computational Spintronics Group, led by Stefano Sanvito.

Licenses & Certifications

Coursera
Google Advanced Data Analytics
Coursera Jun 2023
See certificate
Coursera
The Nuts and Bolts of Machine Learning
Coursera May 2023
See certificate
Coursera
Regression Analysis: Simplify Complex Data Relationships
Coursera May 2023
See certificate
Coursera
The Power of Statistics
Coursera May 2023
See certificate
Coursera
Go Beyond the Numbers: Translate Data into Insights
Coursera May 2023
See certificate
Coursera
Foundations of Data Science
Coursera May 2023
See certificate
Coursera
SQL for Data Science
Coursera May 2023
See certificate

Recent Publications

Quickly discover relevant content by filtering publications.
Connecting Higher-Order Topology with the Orbital Hall Effect in Monolayers of Transition Metal Dichalcogenides
Marcio Costa, Bruno Focassio, Luis M. Canonico, Tarik P. Cysne, Gabriel R. Schleder, R. B. Muniz, Adalberto Fazzio, Tatiana G. Rappoport
PDF Cite
Linear Jacobi-Legendre Expansion of the Charge Density for Machine Learning-Accelerated Electronic Structure Calculations
Bruno Focassio, Michelangelo Domina, Urvesh Patil, Adalberto Fazzio, Stefano Sanvito
PDF Cite Project
Topological Insulating Phase Arising in Transition Metal Dichalcogenide Alloy
F Crasto de Lima, Bruno Focassio, RH Miwa, A Fazzio
PDF Cite
How Lignin Sticks to Cellulose-Insights from Atomic Force Microscopy Enhanced by Machine-Learning Analysis and Molecular Dynamics Simulations
Diego M Nascimento, Felippe M Colombari, Bruno Focassio, Gabriel R Schleder, Carlos AR Costa, Cleyton A Biffe, Liu Y Ling, Rubia F Gouveia, Mathias Strauss, George JM Rocha, others
PDF Cite Project
Machine Learning of Microscopic Ingredients for Graphene Oxide/Cellulose Interaction
Romana Petry, Gustavo H Silvestre, Bruno Focassio, Felipe Crasto de Lima, Roberto H Miwa, Adalberto Fazzio
PDF Cite Project
See all publications

Contact

Feel free to send me an email