Client: Specific Diagnostics https://specificdx.com/

Role: Machine Learning Engineer

Project Objective:

Developed an innovative, cost-effective, and rapid diagnostic system that combines bacterial infection identification with antibiotic susceptibility testing. Leveraged state-of-the-art computer vision and machine learning techniques to process and analyze proprietary sensor data, enabling potentially life-saving results within hours instead of days.

Technical Skills and Libraries:

• Deep Learning Frameworks: TensorFlow, Keras
• Scientific Computing: SciPy, NumPy
• Machine Learning: Scikit-learn
• Computer Vision: OpenCV, Pillow
• GPU Acceleration: CUDA, cuDNN
• Data Storage and Retrieval: SQL, Pandas
• Data Visualization: Matplotlib

Key Expertise:

• Biomedical engineering principles for medical image and signal analysis.
• Convolutional Neural Networks (CNNs) and Deep Neural Networks (DNNs) for image classification and segmentation.
• Relational and non-relational database management.
• Large-scale image processing pipelines with 2D filtering techniques.
• Computer vision techniques for object detection and recognition.
• Quality analysis and control workflows.

Accomplishments: