Research

Virtual Screening Using a Novel Contrastive Learning Framework

Advisor: Prof. Jarek Meller
January 2026 - Present
  • Developing a contrastive learning framework for protein-family-aware virtual screening.
  • Studying how such representations transfer across major protein target families.

Manuscript in preparation

Prediction of Opioid–Induced Respiratory Depression in Pediatric Patients

Advisor: Prof. Jarek Meller
January 2026 - Present
  • Developing machine-learning models to predict opioid-induced respiratory depression from genotype and clinical features in a multi-center pediatric cohort.
  • Designing robust, consensus-based feature-selection methods for identifying variants associated with risk.

Manuscript in preparation

Benchmarking the Generalization of Chemical Language Models

Advisor: Prof. Jarek Meller
January 2026 - Present
  • Evaluated how well chemical language models (MolFormer, ChemBERTa) separate active from inactive compounds in embedding space, at both the target and the family level.
  • Conclusion: training ML classifiers on top of the DUD-E benchmark is not appropriate; DUD-E is better used to benchmark the generalization of chemical language models directly.

Poster, ISMB 2026