Improving Ethical Outcomes with Machine-in-the-Loop; Broadening Human Understanding of Data Annotations, (NeurIPS/HCAI, 2021)
Trusted Neural Network (TNN); Reversibility in Neural Networks for Inference Integrity Verification, (ICMLA, 2022)
Efficacy of novel Summation-based Synergetic Artificial Neural Network in ADHD diagnosis, (Elsevier, 2021)
Hey ML, what can you do for me?, (IEEE AIKE, 2020)
TexAnASD - Text Analytics for ASD Risk Gene Predictions, (IEEE BIBM, 2019)
Data adequacy bias impact in a data-blinded semi-supervised GAN for privacy-aware COVID-19 chest X-ray classification, (ACM BCB, 2022)
Data-Blind ML; Building privacy-aware machine learning models without direct data access, (IEEE AIKE, 2021)