My active area of research is in applications of statistics, machin learning, deep learning and computer vision in manufacturing, medical imaging and in the radiology business. I am specifically interested in designing AI models that are explainable and tractable.
- Applications of deep learning algorithms to multi-modal screening mammography for classification and localization of cancer
- Development of explainableAI models for medical applications.
- Domain adaptation of Deep Leaning and Machine Learning models
- Self-supervised learningto incorporate large amounts of unlabeled medical data
- Applications of modern web technologies to make deep learning research more transparent, reproducible and easy to share.
- Using fundamentals of stochastic learning to model consumer behavior.
AI and Computer Vision Skills
Skills I acquired during 14+ years of being in grad school and tech industry
Deep Learning / Machine Learning
- PyTorch, Tensorflow and Keras
- Self-supervised Learning
- Representation Learning
- Mlflow Development
- Tree-based Models
- Support Vector Machines
- Clustering Algorithms
- Spine and Brain CT-Scan and MRI Imaging
- Breast Screening
- Tomography Synthesis Images
- Lung Imaging
- Anamoly Detection
- Object Detection with Detectron2
- Medical Imaging In-painting via GANs
- Trust in Medical AI systems
Web Development Skills
Skills I learned during my free time and special during the quarantine
- Tailwind CSS and Component Libraries
- SEO-friendly and Accessible Designs