Pursuing MSE Biomedical Engineering at Johns Hopkins University
Building AI systems at the intersection of deep learning, medical imaging, and clinical domain knowledge.
I am a BME graduate student with a background that spans biomedical engineering, clinical psychology, and 5+ years in scientific data systems. My work focuses on making AI practical and interpretable in healthcare from automated synapse detection pipelines to deep learning-based vector surveillance for global health.
- Previously: Scientific Application Analyst (ELN systems, pre-clinical research)
- Currently: MS BME @ JHU | Computational Medicine, AI in Medicine, Biomedical Data Science, AI Project & Product Management
- Looking for: Medical Imaging AI · ML Engineering · Data Science & Data Analysis · Healthcare Consulting · AI Project & Product Management roles
- Baltimore, MD → Open to Relocation
ML & Deep Learning
PyTorch TensorFlow scikit-learn ResNet ViT EfficientNet MobileNet-V3 Mask R-CNN
Computer Vision & Imaging
OpenCV scikit-image 3D Segmentation Image Classification ECG/EEG Signal Processing
MLOps & Infrastructure
Docker Hydra Git Google Colab Kaggle
Data & Domain
Python IBM SPSS IDBS ELN Microfluidics Clinical Workflow Optimization
| Project | What it does | Key Result |
|---|---|---|
| Digital Entomologist | Automated taxonomic classification of malaria-vector mosquitoes via deep learning | 99.65% Hamming accuracy · 30× faster training |
| Synpipe | Containerized synapse detection pipeline — Python migration + Docker/Hydra orchestration | 2.43s per volume · reproducible one-click workflow |
| ResNet vs ViT | Benchmarking CNNs vs Vision Transformers on CIFAR-10 for medical imaging insights | ViT + transfer learning: 98.75% vs ResNet: 90.48% |
| NeRF & Gaussian Splatting | 3D scene reconstruction pipeline — COLMAP, nerfstudio, headless GPU environments | Deep MLOps debugging across Windows/Linux/Colab |
| Hospital-Resident Matching | Gale-Shapley stable matching algorithm for NRMP residency allocation | O(n²) guaranteed stability · hackathon project |
- Coursework: Advanced Data Science for BME · Deep Learning for Medical Imaging · Fundamentals of Product Management
- Building: Synpipe: containerized ML pipeline for synaptic segmentation
"The goal is not to build models. The goal is to build things that matter."