Hi, I'm Blake Sonnier
AI/ML Engineer
Healthcare Tech Specialist
Computer Vision Expert
Full Stack Developer
AI/ML Engineer with 7+ years of experience delivering data-driven solutions in healthcare. Specialized in deploying deep learning models for diagnostic imaging, patient monitoring, and risk prediction using Python, PyTorch, and cloud technologies.
Featured Projects
Check out some of my recent work
- Achieved >90% precision in clinical simulations for stress/fatigue detection
- Optimized inference speed to <200ms latency on edge devices through model pruning
- Achieved high Dice scores on tumor segmentation tasks
- Implemented DICOM image loaders with advanced preprocessing pipeline
- Achieved sub-200ms inference time on resource-constrained edge devices
- Reduced model size by 70% through quantization-aware training and pruning
Technical Skills
My expertise across various technologies and tools
Python
JavaScript
TypeScript
SQL
C++
Java
RAchievements
Key accomplishments from my professional journey
Led real-time EEG stress/fatigue detection model with >90% precision
Reduced model inference latency to <200ms on edge devices
Built deep learning segmentation pipeline for brain MRI scans
Created LSTM-based truck demand forecast model, improving fleet utilization by 18%
Reduced ETA prediction error from 30min to <10min
Developed model explainability layer for loan default predictions
Built NLP-based email triage system saving 30+ hours/week
M.S. in Computer Science from University of Texas at Austin
Deployed AI tools into multiple healthcare production environments
Recommendations
What clients and colleagues say about my work
"Blake's MRI segmentation model has transformed our workflow. What used to take our radiologists hours can now be done in minutes, with remarkable accuracy. The interactive visualization dashboard has become an invaluable tool for our team's diagnostic process."
Dr. Sarah Robinson
Director of Clinical Research, NeuroCare
Client • March 15, 2025
"Blake consistently demonstrates exceptional technical ability and problem-solving skills. His work optimizing neural networks for edge deployment has been crucial to our success in the medical device market. His ability to bridge the gap between clinical requirements and technical implementation is outstanding."
Michael Zhang
CTO, Invene
Manager • January 28, 2025
"The EEG cognitive state classifier Blake developed has significantly improved our patient monitoring capabilities. The system alerts us to patient stress and fatigue states before conventional vital signs show concerning changes, allowing for earlier intervention."
Dr. Anita Patel
Head of ICU, Central Medical
Stakeholder • February 12, 2025