Alejandro Correa Bahnsen, PhD

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Passionate about Machine Learning and Data Science. I hold a PhD in Machine Learning and Pattern Recognition from Luxembourg University. Many years of experience in the use and development of predictive models to real-world problems such as: Algorithmic trading, fraud detection, HR analytics, credit scoring, collections, churn and direct marketing. I have written and publish many academic and industrial papers in best per-review publications. Lastly, I also have experience as instructor of econometrics, financial risk management and Machine Learning. I Enjoy giving talks on successful applications of big data science on different applications.

machine learning fraud detection cost-sensitive classification phishing churn modeling sas data mining analytics cybersecurity deep learning information security data science banking analytics adversarial learning lstm neural networks credit scoring bigdata ai apwg data products marketing lime credit card fraud detection direct marketing ensemble methods predictive modeling credit card fraud detection; cost sensitive classi

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Alejandro Correa Bahnsen, PhD

Modern Data Science

Example-Dependent Cost-Sensitive Credit Card Fraud Detection

Maximizing a churn campaign’s profitability with cost sensitive predictive analytics

2013 credit card fraud detection why theory dosent adjust to practice

Classifying Phishing URLs Using Recurrent Neural Networks

Fraud Detection with Cost-Sensitive Predictive Analytics

Fraud Detection by Stacking Cost-Sensitive Decision Trees

PhD Defense - Example-Dependent Cost-Sensitive Classification

Fraud analytics detección y prevención de fraudes en la era del big data slideshare

1609 Fraud Data Science

Ensembles of example dependent cost-sensitive decision trees slides

Demystifying machine learning using lime

Maximizing a churn campaigns profitability with cost sensitive machine learning

2011 advanced analytics through the credit cycle

Analytics - compitiendo en la era de la informacion

DeepPhish: Simulating malicious AI

2012 predictive clusters

black hat deephish

How I Learned to Stop Worrying and Love Building Data Products

AI vs. AI: Can Predictive Models Stop the Tide of Hacker AI?