I have a Master's in Computational Biology from Carnegie Mellon University, with expertise focused on applying advanced AI and generative models for protein engineering and drug discovery. My experience includes implementing deep learning models such as ProteinMPNs, ProtBert, diffusion models, GNNs, and CNNs specifically for protein sequence embedding, antibody design, and optimization. I have worked on projects involving generative AI for novel molecule generation, multimodal machine learning for protein classification, and active learning approaches for identifying carcinogenic signatures. My collaborative and interdisciplinary background positions me to effectively contribute to computational antibody discovery pipelines and accelerate therapeutic innovations.

Computational Neuroscience, health tech, PM in life sciences, Computational Biologist, Bioinformatics

Investigating acquisition function to Optimize the Bayesian Optimizer in BoTorch, identifying targets in a noisy hyperparameter space of rodent models, via focused ultrasound, tracking arousal and behavior (brain stimulation)