At Vital Audio, I lead the development of cutting-edge AI-driven digital voice biomarker software aimed at transforming healthcare through advanced audio signal processing. As CTO, I oversee the entire lifecycle of our technology, from research and development to product deployment, ensuring scalability and security while upholding our commitment to accessibility and equitable care.Key Responsibilities:• Spearheading the design, development, and implementation of Sauti v1.0, an AI-powered platform that extracts clinical insights from short voice clips during phone calls.• Overseeing a multidisciplinary team of engineers and researchers working on machine learning (ML), artificial intelligence (AI), and signal processing to innovate novel healthcare solutions.• Leading the cloud infrastructure design for secure and scalable deployment of healthcare technologies while ensuring HIPAA compliance.• Driving the application of deep learning techniques to improve voice biomarker extraction, leveraging neural networks and NLP (Natural Language Processing).• Collaborating closely with backend developers to optimize system performance and integrate API-based architectures for seamless user experiences.• Employing containerization technologies like Docker for developing and deploying our AI models, ensuring rapid iteration and efficient scaling.• Establishing rigorous DevOps pipelines to automate testing, deployment, and monitoring of our AI models, improving time-to-market.• Managing the integration of secure data pipelines for processing and analyzing protected health information (PHI) in compliance with industry standards.At Vital Audio, we are not just pushing the boundaries of what’s possible in healthcare—we are redefining them. Through our innovative use of AI, we’re building a future where voice can transform health outcomes and make quality care accessible to all.

• Constructed an algorithm to scan infant faces in real time and provide a heart rate for a single user• Provided an ECG strip for every infant along with their respective heart rate allowing room to obtain vitals remotely.• Obtained an accuracy of over 95% by testing the algorithm on 284 infants in the the NICU.

• Developing a generic script for the regulatory documents.• Data which is stored in sqlite3 datafile(DB.) were accessed using the python and extracted the metadata,tables,and data from tables and converted the tables to respective CSV tables.• Used Text Mining and NLP techniques find the sentiment about the organization.• Developed and implemented predictive models of user behavior data on websites, URL categorical, social network analysis, social mining and search content based on large-scale Machine Learning.• Deployed a spam detection model and performed sentiment analysis of customer product reviews using NLP techniques.• Developed predictive models on large-scale datasets to address various business problems through leveraging advanced statistical modeling, machine learning, and deep learning.