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Alex D'Souza
Junior Machine Learning Researcher specializing in healthcare AI and security
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About
Research-focused AI/ML candidate who built an fMRI-based classifier to predict schizophrenia treatment effectiveness under small-dataset constraints. Demonstrated pragmatic model selection by moving from a complex GNN to graph-summary feature engineering with logistic regression, significantly improving accuracy and AUC; primarily works in Google Colab with script-based workflows.
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Key Strengths
- Improved model performance by simplifying from GNN to engineered graph-summary features + logistic regression
- Experience building high-accuracy classifiers on small, privacy-constrained medical datasets
- Strong focus on appropriate evaluation for imbalanced data (AUC over accuracy)
- Iterative experimentation across augmentation (Mixup), preprocessing, and hyperparameter/architecture choices
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Experience
Education
Skills
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Publications
1 publication
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