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."
Programming & Computation
- Python, R, Bash
- GPU Computing (CUDA, RAPIDS stack)
- HPC Systems (SLURM, PBS)
AI/ML & Deep Learning
- TensorFlow, PyTorch, JAX
- AlphaFold3, RFdiffusion, Boltz-2
- Foundation models for protein design
Molecular Modeling
- GROMACS, AutodockGPU
- Free Energy Perturbation (FEP)
- Quantum Chemistry (DFT, QM/MM)
Bioinformatics
- NGS Analysis (WES/WGS, RNA-seq)
- Single-cell RNA-seq
- Variant Calling (GATK, Mutect2)
Workflow Automation
- Nextflow, Snakemake
- Docker, Singularity
- CI/CD (GitHub Actions, GitLab)
Cloud & Infrastructure
- AWS (EC2, S3, HealthOmics)
- NVIDIA NeMo Framework
- HPC cluster management
GPU-accelerated molecular docking platform for high-throughput virtual screening. Achieves 10x speedup over CPU implementations using CUDA-accelerated algorithms.
Key Features: High-throughput screening | ML scoring | Virtual screening optimization
Protein-ligand interaction visualizer with 2D ligand structure representation. Generates publication-ready interaction diagrams for structural biology applications.
Key Features: Interaction analysis | Contact mapping | Network visualization
Enhanced protein visualization toolkit with rich color mapping and interactive 3D views for publication-ready figures.
Key Features: Advanced color mapping | Interactive visualization | Publication-ready outputs
Fragment-based drug design GUI with visual atom selection, fragment library management, and combinatorial generation.
Key Features: Real-time ADMET calculations | 3D visualization | SDF export formats
Molecular property analysis package for ADMET calculations and drug-likeness assessment matching Discovery Studio standards.
Key Features: Lipinski's Rule compliance | Drug-likeness scoring | Property prediction
Operating Room Bio-Intelligence Twin for real-time patient monitoring with AI clinical support and predictive analytics.
Key Features: Multi-patient dashboard | Predictive analytics | Intelligent alert systems
Created comprehensive tutorial series on YouTube covering:
- AI-driven drug design
- NGS analysis workflows
- Quantum chemistry simulations
- Molecular dynamics
- Machine learning in bioinformatics
Impact: Empowering global learners to adopt computational research tools effectively
I'm always open to collaboration opportunities in:
- 🧬 AI-driven drug discovery
- 🔬 Computational biology pipelines
- 🤖 Foundation models for biological systems
- 📊 Multi-omics data integration
- 🚀 Open-source scientific software
Contact:
Crafted with dedication to advancing computational biology and precision medicine