Leading the development of specialized AI models to enhance medical documentation efficiency, with a focus on scalable, real-time clinical solutions.
- Fine-Tuning Med-BERT for Clinical Summaries: Leading the adaptation and optimization of Med-BERT to accurately summarize patient notes across multiple medical specialties.
- Data Curation and Preprocessing: Managing the acquisition and preprocessing of medical datasets (e.g., MIMIC-III, i2b2) to enhance model training, including tokenization and domain-specific text cleaning.
- Efficient Local GPU Cluster Setup: Designing and deploying a cost-effective local GPU cluster using RTX 4090s for rapid model training and inference, significantly reducing cloud costs.
- Advanced Model Training and Optimization: Implementing techniques like mixed-precision training and distributed processing to fine-tune Med-BERT for high-accuracy medical text generation.
- Scalable and Secure Model Deployment: Building containerized solutions using Docker and Kubernetes, integrating a FastAPI interface for seamless and scalable predictions.
- Strategic Co-Founder Involvement: Driving discussions on technical roadmaps, equity division, and funding strategies, while aligning the MVP with future integration goals like EMR compatibility (e.g., Epic, Cerner).
- Long-Term Vision in AI and Research: Balancing my role as a technical lead with a commitment to future industry research, aiming to bridge cutting-edge AI solutions with practical healthcare applications.
