2020 – 2022
- Feature-Level Fusion of Super-App and Telco Alternative Data Sources for Credit Card Fraud Detection, IEEE International Conference on Intelligence and Security Informatics, 2021, [paper]
- Relational Graph Neural Networks for Fraud Detection in a Super-App Environment, KDD Workshop on ML in Finance, 2021, [paper]
- Enhancing User’s Income Estimation with Super-App Alternative Data, Industrial Conference on Data Mining, 2021, [paper]
- Supporting Financial Inclusion with Graph Machine Learning and Super-App Alternative Data, Intelligent Systems Conference, 2021, [paper]
- Super-App Behavioral Patterns in Credit Risk Models: Financial, Statistical and Regulatory Implications, Expert Systems with Applications, 169(1), 2020, [paper]
- Combining behavioral biometrics and session context analytics to enhance risk-based static authentication in web applications, International Journal of Information Security, 2020, [paper]
2015 – 2019
- Risk-Based Static Authentication in Web Applications with Behavioral Biometrics and Session Context Analytics, Proceedings of the International Conference on Applied Cryptography and Network Security, 2019, [paper]
- Hunting Malicious TLS Certificates with Deep Neural Networks, Proceedings of the 11th ACM Workshop on Artificial Intelligence and Security, 2018, Toronto, Canada. [paper]
- DeepPhish: Simulating Malicious AI, IEEE APWG Symposium on Electronic Crime Research (eCrime), 2018, San Diego, USA. [paper][slides]
- Fraud Detection by Stacking Cost-Sensitive Decision Trees, Data Science for Cyber-Security Symposium, 2017, Imperial College London, UK. [paper] [slides]
- Classifying Phishing URLs Using Recurrent Neural Networks, IEEE APWG Symposium on Electronic Crime Research (eCrime), 2017, Scottsdale, USA. [paper] [slides]
- Knowing your enemies: leveraging data analysis to expose phishing patterns against a major US financial institution, IEEE APWG Symposium on Electronic Crime Research (eCrime), 1-10, 2016, Toronto, Canada. [paper] [slides]
- Phishing Classification using Lexical and Statistical Frequencies of URLs, Analytics Forum 2016, Universidad de los Andes, Bogota, Colombia. [abstract] [poster]
- Feature Engineering Strategies for Credit Card Fraud Detection, Expert Systems with Applications, 51(1), 134-142, 2016 [paper]
- PhD Thesis: Example-Dependent Cost-Sensitive Classification, University of Luxembourg, 2015. [thesis] [slides] [repo]
- Detecting Credit Card Fraud using Periodic Features, IEEE International Conference on Machine Learning and Applications, December, 2015, Miami, US [paper]
- A novel cost-sensitive framework for customer churn predictive modeling, Decision Analytics, 2015. [paper] [slides]
- Ensemble of Example-Dependent Cost-Sensitive Decision Trees, arxiv, 2015. [paper] [slides]
- Example-Dependent Cost-Sensitive Decision Trees, Expert Systems with Applications, 42(19), 6609–6619, 2015 [paper]
2014 –
- Example-Dependent Cost-Sensitive Logistic Regression for Credit Scoring, International Conference on Machine Learning and Applications, December 3, 2014, Detroit, US [paper] [poster] [slides]
- Improving Credit Card Fraud Detection with Calibrated Probabilities, SIAM International Conference on Data Mining, April 25, 2014, Philadelphia, US [paper]
-
Cost Sensitive Credit Card Fraud Detection using Bayes Minimum Risk, IEEE International Conference on Machine Learning and Applications, December 3, 2013, Miami, US [paper]
-
Constructing a Credit Risk Scorecard using Predictive Clusters, SAS Global Forum, April 22, 2012, Orlando, US [paper]