Bioinformatician | AI-Driven Drug Discovery Specialist | Stanford Postdoctoral Scholar | Nextflow Ambassador

I'm currently working as a Postdoctoral Scholar at Stanford University School of Medicine, specializing in AI-driven protein design and molecular modeling for battlefield medicine applications. As a Research Scientist with 8+ years of experience, I advance computational biology through the integration of algorithmic innovation and scalable deployment. I create open-source tools with strong familiarity in full-stack frameworks, uniting scientific research with robust software engineering. My expertise spans automation, performance profiling, and workflow optimization for high-throughput biological data—driving faster therapeutic discovery and measurable R&D impact. I define research frameworks and evaluation methodologies that shape community standards, lead cross-sector collaborations, and mentor emerging scientists. I architect end-to-end workflow systems from foundation models to active learning pipelines transforming computational advances into precision medicine breakthroughs.

Current Focus:

• Designing novel anesthetics using AI-driven protein design and high-throughput virtual screening
• Developing multimodal foundation models for protein structure prediction
• Building open-source tools for reproducible computational biology research

"At the heart of every robust scientific protocol lies rigorous analysis. In an era of exponential data generation—where multi-omic, structural, clinical, and high-throughput datasets proliferate—we face not a scarcity of information but a scarcity of synthesis. My work centers on transforming raw biological noise into mechanistic clarity."