Thomas Cooper Email & Phone Number

Ocala, FL, US

• Led the design and implementation of machine learning models to optimize predictive maintenance for manufacturing clients, reducing production line defects by 20% and saving $2M annually in operational costs.
• Developed deep learning models integrated with Altair's simulation tools, increasing engineering design efficiency by 25% for automotive and aerospace clients.
• Built and deployed AI-powered optimization algorithms for product development simulations, enabling faster prototyping and reducing time-to-market by 15%.
• Managed the deployment of AI models using Kubernetes and Docker on cloud platforms (AWS, GCP), scaling predictive analytics solutions to meet global enterprise demands.
• Spearheaded the creation of an anomaly detection system for real-time IoT data processing, improving predictive monitoring of industrial equipment and reducing unplanned downtime by 30%.
• Collaborated with cross-functional teams (data scientists, engineers, and product managers) to integrate machine learning models with Altair’s engineering software suite, driving AI adoption and increasing revenue by.

• Developed and deployed machine learning models to analyze multi-modal healthcare data, achieving a 95% accuracy rate in predicting treatment outcomes for cancer patients.
• Built models to interpret genomic data, improving the identification of actionable mutations by 20%.
• Collaborated with clinicians and data scientists to integrate AI-driven decision support tools into hospital workflows, reducing treatment planning time by 30%.
• Led the development of explainable AI models, increasing adoption of AI tools among physicians by 25%.
• Deployed machine learning models on Google Cloud Platform (GCP), ensuring scalable and secure data processing across healthcare providers.

• Built and optimized backend services in Python and Java to support real-time event detection from large-scale data streams, improving data ingestion efficiency by 20%.
• Implemented core components of the data pipeline using Apache Kafka and Spark, processing millions of data points daily to support real-time alerting.
• Integrated early-stage natural language processing (NLP) models to classify and prioritize important breaking news events.
• Worked on scaling the infrastructure on AWS using EC2, Lambda, and S3, resulting in a 20% cost reduction.
• Collaborated with the machine-learning team to enhance the classification models used for detecting high-priority events.

• Developed backend services in Python and Java to support large-scale document processing systems, improving system throughput by 25%.
• Integrated RESTful APIs that allowed clients to submit documents and retrieve processed data, enhancing the platform's usability.
• Worked with data scientists to deploy OCR (Optical Character Recognition) models, which increased document processing accuracy by 20%.
• Refactored backend code for scalability, reducing document processing time by 15%.
• Automated deployment pipelines using Jenkins and Docker, reducing deployment times by 30%.

Bachelor Of Science - Bs, Computer Science

Human Computer Interaction