Talks

2019

  • AI @Rappi,  Data Science for All, Bogota, Colombia, October 31, 2019, [slides]
  • Maximizing a churn campaign’s profitability with cost-sensitive Machine Learning,  Scipy Latam, Bogota, Colombia, October 8-10, 2019  [slides]
  • Experiencias usando Inteligencia Artificial en un Marketplace, Meetup Data Science Colombia, Bogota, June 12, 2019 [slides]
  • The Democratization of Artificial Intelligence,  Emerge Americas, April 30, 2019, Miami, USA.
  • Detection of Threats to IoT Devices using Scalable VPN-forwarded Honeypots, RSAConference, March 5-8, 2019, San Fransisco, USA [whitepaper]

2018

  • DeepPhish: Simulating Malicious AI,  Black Hat Europe, 2018, London, UK [paper]
  • CertHunter,  IEEE APWG Symposium on Electronic Crime Research Europe (EUeCrime), 2018, Krakow, Poland. [paper]
  • DeepPhish: Simulating Malicious AI,  IEEE APWG Symposium on Electronic Crime Research (eCrime), 2018, San Diego, USA. [paper][slides]
  • Creating Malicious AI, Emerge Americas, April 26, 2018, Miami, USA.
  • AI vs. AI: Can Predictive Models Stop the Tide of Hacker AI?, RSAConference, April 16-20, 2018, San Fransisco, USA [whitepaper] [slides]

2017

  • Behind the Scenes in Building Data Products, APWG European Symposium on Electronic Crime Research (eCrime), Ocober 20, 2017, Porto, Portugal [Slides]
  • Behind the Scenes in Building Data Products, September 31, 2017, Luxembourg University.
  • Fraud Detection by Stacking Cost-Sensitive Decision Trees, Data Science for Cyber-Security Symposium, September 30, 2017, Imperial College London, UK. [paper] [Slides]
  • Classifying Phishing URLs Using Recurrent Neural Networks, Mind the Sec, September 9, 2017, Sao Paulo, Brasil.
  • Maximizing a churn campaign profitability with cost sensitive machine learning, Big Data Analytics Summit, August 26, 2017, Lima, Peru [paper] [slides]
  • Data Science: From Statistics to Machine Learning, National Statistics Symposium, August, 11, 2017, Medellin, Colombia.
  • Classifying Phishing URLs Using Recurrent Neural Networks, IEEE APWG Symposium on Electronic Crime Research (eCrime), May 25, 2017, Scottsdale, USA [paper] [slides]
  • Detecting Phishing using Deep Learning, Meetup Machine Learning and Data Science Bogota, April 19, 2017.
  • Tutorial – Practical Machine Learning with Python, Pycon.co, February 10, 2017, Bogota [Notebooks]
  • Demystifying Machine Learning, Pycon.co, February 10, 2017, Bogota [Notebook] [slides]

2016

  • Fraud Data Science, Mexican Banking Association Summit, September 2, 2016, Mexico City [slides]
  • Modern Data Science, Big Data Summit, August 19, 2016, Lima, Peru [slides]
  • Applied Data Science, Meetup Machine Learning and Data Science Bogota, June 15, 2017.
  • Advanced Fraud Detection using Data Science, Analytics Forum Universidad de los Andes, April 4, 2016, Bogota, Colombia. [slides]
  • Example-Dependent Cost-Sensitive Fraud Detection using CostCla, PyCaribbean, Feb 21, 2016, Santo Domingo, Dominican Republic [slides]

2015

  • Fraud Detection with Cost-Sensitive Predictive Analytics, Business Analytics in Finance and Industry, December 4, 2015, Santiago, Chile [slides]
  • Fraud Analytics, Big Data Science Bogota Meetup, September 24, 2015,  [slides]
  • PhD Thesis: Example-Dependent Cost-Sensitive Classification, University of Luxembourg, September 15, 2015,[paper] [slides]
  • Example-Dependent Cost-Sensitive Credit Scoring using CostCla, PyData Berlin, May 30, 2015, Berlin, Germany [slides]
  • Ensembles of Example Dependent Cost-Sensitive Decision Trees, April 28, 2015, Luxembourg [paper]  [slides]
  • Do we Need Hundreds of Classifiers to Solve Real World Classification Problems?, DataScience Luxembourg Meetup, March 4, 2015, Luxembourg [webapp] 

2014 –

  • Fraud analytics: detección y prevención de fraudes en la era del big data, ASOBANCARIA – VIII Congreso de prevención del fraude, October 3, 2014, Bogota, Colombia [slides]
  • Maximizing a churn campaign’s profitability with cost sensitive predictive analytics, SAS Analitics Conference, June 4, 2014, Frankfurt, Germany [slides]
  • Example-Dependent Cost-Sensitive Credit Card Fraud Detection, March 21, 2014, Leuven, Belgium [slides]
  • Example-Dependent Cost-Sensitive Credit Scoring, DataScience Luxembourg Meetup, February 5, 2014, Luxembourg[slides]
  • Analytics – compitiendo en la era de la informacion, October, 2013, Bogota, Colombia [slides]
  • Data Analysis for Credit Card Fraud Detection, European Conference on Data Analysis, July 11, 2013, Luxembourg [slides]
  • Credit Card Fraud Detection: Why Theory Doesn’t Adjust to Practice, SAS Analytics Conference, June 2, 2013, London, UK  [slides]
  • Advanced Analytics through the credit cycle, SAS Analytics Conference, October 20, 2011, Orlando, US [slides]