Computational Biology & ML Researcher | RNA/DNA Design 路 Evolutionary Optimization 路 AI for Science
I build computational systems for biomolecular sequence design, combining evolutionary optimization, machine learning, multi-tool validation, and reproducible scientific software.
- Completing an MASc in Computer Engineering at Concordia University
- Research focus: RNA/DNA sequence design, inverse folding, and evolutionary optimization
- First-authored and presented an RNA inverse-folding paper at IEEE CEC / WCCI 2026
- Open to Computational Scientist, Research Engineer, and ML-for-Biology roles across Canada
馃К cFold
A multi-tool evolutionary framework for designing RNA sequences under structural and IUPAC constraints, presented at IEEE CEC / WCCI 2026.
- DNA aptamer design: Optimizing multivalent fluorescent aptamer architectures with oxDNA simulations; eight candidates selected for experimental validation.
- RNA and ribozyme design: Extending cFold to additional predictors and pseudoknotted targets, with selected designs undergoing experimental validation.
Python 路 PyTorch 路 Evolutionary Algorithms 路 ViennaRNA 路 MXFold2 路 oxDNA 路 Linux 路 Docker 路 Git 路 SLURM