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  • Paulo Maia
Paulo Maia

Paulo Maia

  • Data Scientist

I'm a Biomedical Engineer who went from AI in Healthcare to multiple industries. Talk with me if you are interested in having data-driven projects in your organization, if you're stuck trying to improve a model's performance and need new ideas, and if you'd like an out-of-the-box approach to data science problems. Also, I'm an enthusiast of applications of data science for social good!

  • Knowledge
  • Business
  • Technical
  • Languages
  • English
  • Portuguese
  • Consultants
Book a Meeting

Industries

  • Automotive
  • Healthcare
  • Marketing & CRM
  • Real Estate
  • Telco

Areas of Expertise

  • Computer Vision
  • Design Thinking in AI
  • MLOps
  • NLP
  • Tabular Data

Education

  • Universidade do Porto MSc in Bioengineering (Biomedical Engineering) 2014-2019

Interests & Hobbies

  • Always eager to binge-watch the newest TV Show!
  • A curious mind for science.
  • Diving in water that is too cold for the typical human.

Articles by Paulo

Article
Ditch the Crystal Ball: Reverse-Engineering with Machine Learning

Dec 27, 2023 in Opinion

  Machine Learning models are estimators – which means they can be used not only to predict unknowns in your business but also to reverse-engineer complex business processes. As part of this blog post, you will learn how to identify these potential points of improvement, prioritize them, and create models to estimate them. Identification How […]

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Article
Customizing Language Models: Fine-Tuning vs. Prompt Engineering

Nov 6, 2023 in Technical

In the rapidly evolving landscape of artificial intelligence, there’s a notable surge in interest and activity surrounding generative AI. The question arises: Why this rush? What’s the driving force? The answer lies in the transformative power of customizing Large Language Models (LLMs). Businesses are increasingly captivated by the potential these models hold, specifically when tailored […]

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Article
Classifying text using LLMs

Aug 29, 2023 in Technical

  Text classification is one of the most common use cases in Natural Language Processing, with numerous practical applications – now easier to access with Large Language Models. Companies use text classification in multiple scenarios to become more efficient: Tagging large volumes of data: reducing manual labor with better filtering, automatically organizing large volumes of […]

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Article
Spatial Explanations: Unlocking Insights with Occlusions

Aug 2, 2023 in Machine Learning

Spatial Explanations with Occlusions: In computer vision, businesses must grasp the workings of image models to fully leverage visual data. Our simple method called spatial explanations with occlusions, helps achieve a deeper understanding. By employing spatial occlusions across images, this technique unveils critical areas that significantly influence the model’s predictions.” What to do with these […]

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Article
The Impact of Large Language Models

May 25, 2023 in Industry Overview

Large Language Models (LLMs) are THE hot topic of the year. If the name Large Language Models sounds unfamiliar to you, I’m pretty sure you’ve heard of ChatGPT, OpenAI, and Bard. People who don’t know how to code have gained access to a tool that allows them to build Proof of Concepts for ideas they’ve […]

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unlock poor models
Article
In medio stat virtus? Not always!

Apr 10, 2023 in Technical

The Problem What do you do when the model is underperforming? When the models’ performance does not meet our expectations, we usually spend time searching for the flaws, selecting and analyzing the cases where it failed to understand why it happened. Then, we try to apply more robust solutions, train, test, and repeat. In some […]

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Article
Our vision of AI in Financial Services

Dec 12, 2022 in Industry Overview

In recent years, the financial services industry has been innovating technologically, supported by a complex ecosystem including banks, financial service providers, and start-ups (link). Within this blogpost, we showcase our vision of AI in Financial Services. AI in Financial Services From our point of view, we can group use cases in AI in three distinct […]

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Article
Stop removing outliers just because!

Nov 14, 2022 in Technical

Outliers are data points that stand out for being different from the remaining data distribution. An outlier can be: An odd value in a feature A data point distant from the centroid of the data A data point in a region of low density, but between areas of high density. Suppose you have been working […]

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Article
Achieving diverse product recommendations

May 25, 2022 in Use Case

In this blog post, you’ll learn about some examples of decision processes you can use in recommender systems: do you see any usage for recommending less popular products as a way to improve your business? You will see it now! The Use Case Let’s imagine a use case where you are building a MOOC platform […]

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Article
Teaching Models With Free Data

Feb 23, 2022 in Technical

“The more I see, the less I know” might be a saying, but it does not apply to AI models. It’s well known that the performance of an artificial neural network is highly dependent on the volume and on the diversity of the data that was shown to the model. This happens because exposing the […]

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Article
WDL – Solving Social Problems Using Data Science

Nov 29, 2021 in News

This article describes the key points of my participation at the 2021 Edition of the World Data League. The Tech Moguls Team, composed of me, Tiago Gonçalves, Tomé Albuquerque and Joana Morgado, from INESC TEC, finished second place in this edition. World Data League (WDL) is a Data Science competition where groups of Data Scientists […]

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Article
Multiple Product Forecasting in the construction industry

Nov 9, 2021 in Use Case

In this article, we will cover a use case in the construction industry related to forecasting the needed materials for construction and the time in which they will be required. In the construction industry, there is a lot of uncertainty between the order time and the time in which it is actually executed, due to […]

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Article
You Have the Right to Remain Silent

Aug 2, 2021 in Technical

The Miranda warning prevents us from self-incrimination. You have the right to remain silent. Anything you say will be used against you. If we hold ML models accountable for their predictions, shouldn’t we at least grant them that right? Can we expect ML models to know everything? I guess we don’t! Moreover, it would be […]

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Article
ML System Design: Federated Learning

Jul 14, 2021 in Use Case

NILG.AI, together with Neu.ro decided to try a format similar to a Reading Club, where the topic is not a specific paper but an entire research area. After a short discussion, we had a System Design part where the team described a specific use case to apply the new approach. Ideally, the discussion would stick […]

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Article
Speeding up Science: AI tools for Pharma

Jun 1, 2021 in Industry Overview

At NILG.AI, our motto is “Unlocking business capabilities using Data Intelligence”, since we see Artificial Intelligence as a powerful tool designed to maximize the potential of human activity. A lot of fields have been taking advantage of the AI revolution creating more efficient systems able to get more accurate results while saving time and operation […]

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Article
An Introduction to Multiple Instance Learning

May 18, 2021 in Technical

Multiple Instance Learning (MIL) is a form of weakly supervised learning where training instances are arranged in sets, called bags, and a label is provided for the entire bag, opposedly to the instances themselves. This allows to leverage weakly labeled data, which is present in many business problems as labeling data is often costly: Medical […]

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Article
Embedding Domain Knowledge

Feb 17, 2021 in Technical

In the good old days, working as a Machine Learning Engineer meant working 95% of the time on feature engineering and 5% on training models with the extracted features. This was a manually intensive and time-consuming process, that usually led to inflexible proofs of concept that could hardly be adapted to new settings. Fortunately, Deep […]

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Article
Reducing Unemployment using AI

Jan 18, 2021 in Use Case

With COVID-19, many were affected by the economic crisis and lost their jobs. In Portugal alone, between February and September, there was a 30% increase in unemployment! AI can be a powerful tool in allocating scarce resources in a more efficient way. Inspired by DSSG Fellowship’s Project in Partnership with IEFP (Instituto de Emprego e […]

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Article
Difficult Targets to Optimize: the ROC AUC

Dec 18, 2020 in Technical

In many binary classification problems, especially in domains with highly unbalanced problems (such as the medical domain and rare event detection), we need to make sure our model does not become too biased for the more predominant class.  Thus, you may have heard that accuracy is not a good metric to validate classifiers in unbalanced […]

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A balance between two unbalanced options, representing the potential imbalance an AI algorithm generates
Article
Fairness in AI

Aug 18, 2020 in Webinar

In collaboration with Data Science for Social Good Portugal, we are excited to announce a groundbreaking series of webinars focusing on AI topics that intersect with the greater social good. Our recent webinar, the second installment in this series, took place on the 29th of July and featured an insightful presentation by Francisca Morgado. She […]

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Article
Applying geospatial data for Machine Learning, with a focus on social good

Jul 16, 2020 in Webinar

In partnership with Data Science for Social Good Portugal, we are launching a series of webinars in AI topics related to social good. The first talk was by Paulo Maia, on the 28th of June, with the topic “Applying geospatial data for Machine Learning, with a focus on social good”. In case you weren’t able […]

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Article
Detecting Errors in Insurance Claims

May 5, 2020 in Use Case

Insurance codes are used by people’s health plan to make decisions about how much your doctor and other healthcare providers should be paid.  There is some variety of coding systems currently used [1]: Current Procedural Terminology (CPT) codes, used by physicians to describe the services they provide. Healthcare Common Procedure Coding System (HCPCS),  used by […]

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Article
Thermal Imaging in AI

Apr 24, 2020 in Industry Overview

Artificial Intelligence (AI) is one of the current hottest issues, intersecting many fields of interest. With the dissemination of this concept, the expectations about its potential grew a lot among the society. Some people look at AI as a set of mechanisms that can improve people’s intelligence, increasing the human activities performance, others look at […]

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Article
Embedding Domain Knowledge for Estimating Customer Lifetime Value

Apr 6, 2020 in Technical

As part of the rise of Deep Neural Networks in the ML community, we have observed an increasing fit-predict approach, where AI practitioners don’t take the time to think about the domain knowledge that is already available and how to embed that knowledge in the models. In this blogpost, we will cover how we created […]

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Article
Appendix: Embedding Domain Knowledge for Estimating Customer Lifetime Value

Apr 6, 2020 in Technical

This is an appendix to the blog post Embedding Domain Knowledge for Estimating Customer Lifetime Value. We will describe some alternatives we considered for solving the proposed problem, but did not end up being implemented. First, let’s assume we have a pre-trained model for estimating the probability of the target and . Estimating Lifetime Value using […]

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Article
Objectively Estimating Data Quality

Feb 27, 2020 in Technical

In Artificial Intelligence, it is important to measure the quality of the data we are trying to use. For instance, if we want to classify a cervix image according to the degree of cancer, how do we know if that image follows the acquisition protocol and can be used for diagnosing the patient [1] so […]

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