Career Profile
Hello! I’m Everton, a seasoned Computer Scientist and Data Analyst with a rich background in developing algorithmic processes, solutions, and tools. I specialize in enabling efficient data-driven insights and decision-making solutions at The Faculty of Science of University of British Columbia, FEEC/Unicamp, PPGI/UTFPR, and USP.
I am a computer scientist and software engineer with 20+ years of experience leveraging machine learning, data analysis, and software development expertise. I have a proven track record in translating complex data into actionable insights, significantly improving business strategies and operational efficiency. I am passionate about developing innovative solutions to challenging problems.
In previous roles, including as a Senior Operations Research Analyst at Vanhack, Sicoob, Sancor, Solaris, Produtec and Senai HUB, I honed my skills in life cycle forecasting, risk, and decision analysis. My career spans applied analytic research, software development, educational content creation, and consulting. I have been working on applied analytic research, developing data analysis software, creating data science educational content, writing books, and providing analytic consulting services.
Besides, I have been working as a Visiting Professor at the University of São Paulo, University of Maringá, Pontifical Catholic University, FCV, and University of Londrina, where I have taught business analytics and courses in R and Python programming. My teaching style is building knowledge from general to specific, simple to complex, and using example-based methods before mathematical formalization.
I am also reviewer of journals Journal of Scientific Research and Reports (JSRR), Journal of Education, Society and Behavioural Science (JESBS), Journal of Computational and Cognitive Engineering (JCCE), Journal of Data Science and Intelligent Systems (JDSIS), Computer and Telecommunications Networking, Journal of Waste Resources and Recycling (JWRR), Trends in Computer Science and Information Technology, Asian Journal of Sociological Research, Asian Journal of Education and Social Studies, Trends in Computer Science and Information Technology, South Asian Journal of Social Studies and Economics, Artificial Intelligence Review, Machine Learning Research, ISPRS International Journal of Trends in Computer Science and Information Technology, Geo-Information, Smart Cities, Sensors, International Journal of Environmental Research and Public Health, Applied Sciences, Big Data and Cognitive Computing, and Future Internet.
Moreover, I have written many technical books and scientific papers related to computer science and I have been working as a researcher at FEEC/Unicamp. Also, I have a project approved by the IRAP and I am working with Harvard University researching stable match problems. Recently, I have started to work at University of British Columbia and The University of Guelph as a researcher dealing with a lot of farms animal’s datasets.
All opinions and views are my own and do not represent my employer(s).
Experiences
I have been leveraging cutting-edge technologies in machine learning, predictive analytics, IoT, and satellite imagery analysis to enhance wildfire prediction, detection, and response strategies.
- Develop and refine AI models to predict wildfire risks and behavior
- Collaborate with environmental scientists to integrate ecological data into AI systems
I have been working with Computational Intelligence (CI), a field of research combining several branches of computer science and artificial intelligence to create intelligent systems that can learn, adapt, and solve complex problems. CI draws inspiration from biological systems, such as the human brain, to develop algorithms that can handle tasks difficult for traditional rule-based programming.
- Speech recognition and natural language processing
- Recommendation systems for e-commerce and content platforms
I have supervised graduate students and young researchers, guiding them in their academic and research endeavors and providing support, advice, and valuable insights to help their mentees succeed in their academic careers
- Machine Learning
- Data Science
I have been working with computational intelligence techniques applied to various neurocomputing areas to better understand neural networks and learning systems. This includes, but is not limited to, architectures, learning methods, analysis of network dynamics, theories of learning, self-organization, biological neural network modeling, sensorimotor transformations, and interdisciplinary topics with artificial intelligence, artificial life, cognitive science, computational learning theory, fuzzy logic, genetic algorithms, information theory, machine learning, neurobiology, and pattern recognition.
- Neuro Science
- Computer Science
I have been working with many computational intelligence techniques applied to many areas of online social networks, which have revolutionized the way we interact and share information over the Internet. Social networking applications have millions of active users, generating multiple terabytes of information daily due to user interactions in such networks. The ability to collect and analyze this data provides unique opportunities to understand the underlying principles of social networks, their formation, evolution, and characteristics.
- Algorithms
- Systems
- User Behavior
- Complex Networks
I have worked with computational intelligence techniques applied to various areas of the financial and software industries, such as fraud detection, money laundering, pattern recognition, sentiment analysis, and recommender systems.
- Computational Intelligence
- Financial and Software Industries
I have worked with Java technology and its derivatives to architect, build, deploy, and maintain operations for many critical solutions.
- Java
- Software Engineering
I have worked with Java technology and its derivatives to build, deploy, and maintain operations for many types of critical solutions.
- Java
- Software Engineering
Side Projects
Some selected side open-source projects.
Publications
Below are some selected papers published in conferences and journals related to computer science, software engineering, and neuroscience.
Skills & Proficiency
Computer Science
Network
Statistics
Math
Machine Learning
Deep Learning
Communication
Data Science
Neuro Science
Pattern Recognition
Software Engineering
Software Architecture
Database Systems
Java DevOps
Project Management
Python
Data Analytics
Statistics Analysis
Statistical Modeling
Data Mining
Predictive Modelling
Spark
SQL
Hadoop
Big Data
Soft Skills
Microsoft Azure SQL
Data Engineering on Azure
Microsoft Azure AI
Data Science on Azure
ETL/ELT
Data Pipeline
Open Source Codes
Some selected open-source code.