Has a PhD in Computer Science (University of São Paulo / Univeristé Paris-Sud), in which he developed novel theory and technology related to Software Engineering, Formal Methods, Formal Verification, Simulation, Artificial Intelligence and Multiagent Systems. Published several peer-reviewed research papers in these areas. Has also built a number of consumer products and developed more experimental business technologies, mainly for consumer behavior analysis and optimization. Counting the PhD, has more than 10 years of experience working in highly sophisticated technologies, including Formal Modeling, Verification and Evolutionary Computation. For the last few years he has been improving his knowledge of Machine Learning and related fields. Besides technical skills, he also has a deep interest in business issues, having founded a software company and headed a group of entrepreneurs prior to his present position.
2006 – 2012 | PhD in Computer Science
Universidade de São Paulo (Brazil) / Université Paris-Sud (France)
Verification of behaviourist multi-agent systems by means of formally guided simulations
I had both a CNPq (in Brazil) and a CAPES (in France) scholarships, as well as a scholarship provided directly by Université Paris-Sud.
2001 – 2005 | Bachelor of Computer Science
Universidade de São Paulo (Brazil)
1998 – 2000 | High school
2019 – present | Funcional Health Tech (Health Analytics business unit)
Data Science Manager
I am responsible for managing the Data Science area of our Health Analytics business unit. This includes leading a team (three Data Scientists and one Solutions Architect), developing strategic technology and methods, as well as promoting good practices across the company and its customers. Specifically, some important initiatives I led were:
- Established an agile (Scrum-based) work routine for the team;
- Designed and delivered workshops for internal business customers, in order to elicit the most valuable and feasible Data Science use cases;
- Designed and established a Data Science process for systematic and gradual work. This can be used both in consulting engagements and in product development;
- Compiled the most relevant Data Science use cases into more abstract and reusable scenarios, which allows more efficient use of the team’s time;
- Infused good Software Engineering practices in Data Science work, in order to make it more reusable and automated;
- Promoted marketing work, which resulted in a favorable press release in top newspapers and magazines;
- Directly provided Data Science advisory as needed by other areas of the company.
2016 – 2019 | Dell Technologies (Consulting Services)
As a Data Science consultant, I designed and implemented machine learning models for corporate customers, in particular through the analysis of large-scale, distributed, datasets (i.e., “big data”), typically using a Python stack. General expertise exercised involved:
- Hadoop-based tools (mainly Spark and Hive).
- machine learning libraries (e.g., scikit-learn, keras) and notebooks environments (i.e., Jupyter and Zeppelin).
- worked directly with customers in order to assess relevant business problems and propose solutions.
- worked mostly in an agile manner (Scrum).
More concretely, I worked mainly in problems for the financial sector, such as:
- customer analysis through various techniques, including clustering and behavior forecast.
- cash flow forecasts using Recurrent Neural Networks (RNNs) and Decision Trees.
- recommendation system for a major Brazilian bank through (a simple version of) Reinforcement Learning, in collaboration with various other Data Scientists, Data Engineers and Solutions Architects.
- credit score analysis using non-traditional methods, in collaboration with other Data Scientists.
Other engagements included:
- technical advice with respect to the Data Science practices of a major European telecommunications operator.
- classification of crops using satellite imagery and Deep Learning techniques for a biotechnology company.
- advice for a major oil company regarding possible Data Science applications involving seismic data.
- mentoring of junior members of the Data Science team.
- technical guidance to development team, particularly with respect to software testing.
- helped in various project proposals, with a particular interest in developing the customers’ internal Data Science capabilities.
2015 – 2017 | Salem Sistemas
My software company, through which I provided consulting services and developed new technologies. My main technical achievement here was called Empirica, an experimental software designed to optimize human behavior through the analysis of online user interactions. This research and development is currently paused.
2012 – 2016 | Liberalis
A startup product that I conceived, implemented and marketed after my PhD. It is an online tool through which professionals (e.g., psychologists, lawyers, architects, etc.) can easily create their own websites. The generated websites adapt to quantity and type of content inserted, without any need of manual layout or design configuration. Liberalis operated under a “freemium” model: the basic offer is free (with ads), and a premium offer (with a number of advantages) is charged. This system had over 2500 users and was implemented in Ruby on Rails.
In the press
The payment subsystem of Liberalis was the inspiration for a formal verification software that I developed as an independent library and is now open sourced (https://github.com/paulosalem/verum). I also produced a related academic publication (see below; published in May/2016).
2005 – 2009 | Distincards
An e-cards website for people interested in art, literature and philosophy. “Distinct cards for distinct people.”
Fluent. TOEFL iBT (116/120).
Good oral and written understanding; good oral expression; reasonable written expression. I lived in Paris for more than a year during my doctorate.