Privacy-aware Machine Learning.
Bias in Machine Learning and its mitigation using privacy-awareness methods.
Machine Learning for Cybersecurity
Adversarial Learning
Use of Machine Learning to Develop Burn Probability Models for Wildland Fires.
Privacy-preserving Machine Learning Development Pipelines.
Explainability in artificial intelligence models.
Education aspects during the COVID-19 pandemic.
Autism Spectrum Disorders Gene Incidence Prediction.
ACMSE 2020 - The Annual ACM Southeast Conference. University of South Florida. April 2-4, 2020.
ACMSE 2021 - The Annual ACM Southeast Conference. Jacksonville State University. April 15-17, 2021.
In partnership with CU Boulder, we are developing an scalable recommendation system to recommend Chicago young people activities within the city and their interests.
In partnership with the School of Medicine, we designed Google Assistant-enabled Applications to improve student success. Press release.
ECHO Data Warehouse Project:
We designed and implemented a highly scalable data warehouse to store and query datasets with hundred of thousand features.
NIJ Crime Prediction Challenge:
We implemented a solution with some members of the BDLab, trying to achieve a good prediction of crime.
Trajectory Consolidation Project:
Using SQLServer Spatial to store and consolidate trajectory points into well-defined trajectories.
Databases High Availability in Multiple Datacenter Architecture Design (DGI)
Factura Electronica Project (DGI)