As the Senior Director of Artificial Intelligence Strategy, I lead the ideation, research, and integration of AI capabilities across WorkWave. This includes identifying AI opportunities, developing innovative concepts, and working cross-functionally with technical teams to bring these ideas to life, both within the company and within customer applications.• Develop and execute a comprehensive AI strategy and vision impacting both internal operations and customer-facing products• Collaborate with cross-functional teams, including product management, engineering, data science, support and marketing to identify opportunities for AI integration• Help build, manage and mentor a team of AI engineers and data scientists to design, develop, and deploy AI-driven solutions• Oversee the development and implementation of AI-powered features such as intelligent route optimization, predictive maintenance, natural language processing, and automated customer service• Establish and maintain strong partnerships with AI technology vendors, research institutions, and other relevant stakeholders• Evaluate the performance and impact of AI implementations on our products and services, making data-driven recommendations for improvement• Foster a culture of innovation and continuous learning within the AI team and across the organization

Wond’ry Mentors are professionals who volunteer to meet with Vanderbilt innovators for one-on-one personalized guidance in their areas of expertise. By encouraging the pursuit of meaningful connections, Mentors provide opportunities for learning outside the classroom and support for independent entrepreneurial and creative endeavors.

• Executive responsible for all artificial intelligence and machine learning activities within the organization• Leading R&D using generative AI, ChatGPT, and other cutting-edge AI for product and operations• Developed and executed strategic roadmaps for product development of the CAVO and APPELLO platforms, as well as for optimization and enhancement of our professional services group• Worked closely with clinical SMES to architect and lead our AI products, including:- Clinical information extraction of diagnoses, medication administration, laboratory test results, and other significant clinical data from unstructured paper medical records using natural language processing (NLP), named entity recognition (NER), and deep-learning- or transformer-based algorithms- Clinical guideline modeling consisting of development of clinical risk models, filtering and applying clinical fact patterns, and interpretation of results- Document classification of paper medical records to recognize common types of documents such as “discharge summaries”, “procedure notes”, “laboratory results”, etc., using embeddings and hierarchical deep networks to analyze multimodal data- Itemized bill prediction to extract itemized bills, map line-items to HCPCS/CPT/revenue codes, and apply both structured business rules and supervised machine learning to detect non-payable items• Participate in high-profile presales activity with C-level customer contacts and assist in identification and scoping of project work• Interviewed, hired, and led all Machine Learning Scientists, Machine Learning Engineers, and Machine Learning Devs• Develop strategies, go-to-market plans, sales enablement, and execution plans for new strategic offerings including: - Generative AI offerings based on ChatGPT, GPT-4, and other open- and closed-source models- Enhanced OCR capabilities based on state-of-the-art computer vision AI- Optimized claim review assignment algorithms based on claim predictive models

• Executive (reporting to the CEO) ultimately responsible for the machine learning line of business, consisting of data science, machine learning engineering, MLOps enablement (including CI/CD for ML, data lineage, and scalability), and managed services• Responsible for setting strategic direction, developing go-to-market plans, sales enablement, and working with marketing on outbound marketing and inbound content marketing (including hands-on development of content and speaking roles)• Provide technical leadership, mentoring, oversight, and recruiting support for advanced data scientists, machine learning engineers, and machine learning solution architects• Participate in high-profile presales activity with C-level customer contacts and assist in identification and scoping of project work• Perform technical AI development and work with delivery team to keep them engaged in marketing content creation and internal strategic IP development activities• Develop strategies, go-to-market plans, sales enablement, and execution plans for new strategic offerings including: MLOps architecture using CI/CD, feature stores, and model registries to enable robust ML Model Development, Deployment, and Monitoring (while under data lineage/governance constraints)MLOps platform implementation on Snowflake, AWS, and other cloud providersAI Strategy Assessment and Roadmap developmentML Model Deployment Architecture assessmentManaged ML and other ARR-based offerings• Practice hands-on leadership, assisting team with project needs as required

• Sole point-of-contact for customers, responsible for ensuring product adoption and satisfaction• Worked with practitioners and senior leadership to establish use-cases, execution plans, and measure ROI• Independently managed entire customer relationship to minimize churn and ensure satisfaction

• Established the first formal Artificial Intelligence and Machine Learning team within the enterprise• Work with C-level executives to establish artificial intelligence strategy within the overall technology road-map for the enterprise• Lead a team of direct reports (within both the US and the UK) and interns• Establish team charter, 3-year strategic plans, and set performance goals for myself and my direct reports • Determine strategic and tactical needs of team, translate into operational and capital budget requirements, and work within the enterprise's budget to balance resource needs with available capital• Act independently to coordinate with senior leadership within all business units, identify needs across the enterprise and apply team resources to deliver work product that produces actionable intelligence• Practice hands-on leadership, assisting team with project needs as required

• Developing strategy and overall direction for the adoption of Artificial Intelligence, Deep Learning, and Machine Learning• Leading team and performing project work, including sales lifecycle classification, computer vision, and advanced analytics• Hiring and managing direct reports for the Artificial Intelligence team• Working with senior leadership to identify business problems, identify relevant data, translate business problems into AI projects, and produce actionable deliverables for the business partners.

• Led small team focused on manufacturing analytics; responsibilities included acting as sole business partner contact, division of labor, validation of work, as well as full-stack development along with the team. This project focused on predictive analytics, visualization of complex data using Tableau, and scheduling optimization.• Developing uniform data collection standards in order to analyze customer behavior across multiple platforms and perform content personalization for construction/do-it-yourself customers.• Performing unstructured analysis and natural language processing of Facebook posts in order to segment posts out by topical content and recommend groups/topics to users.• Used geolocation and clustering of technicians and service tickets in order to identify underserved areas• Analyzed promotional effects in order to detect sales lift.• Located data sources within the enterprise that contained business value, created projects around that data, and delivered projects to business partners.• First senior data scientist hired to help establish the team; performed technical and qualitative interviews.• Hosted training sessions, informal sessions, and spoke at conferences to educate about data science practices.• Advocated for data-driven culture and performed several small prototype projects to raise the visibility of the business unit.• Operated as single contact for VP-level business clients through full project lifecycle, from project inception to development to deployment.• Tools include: Python; Amazon Web Services; SQL; Tableau; Linux scripting; other supporting tools

• Sole instructor of cohort containing 27 students, occasionally teach combined classes containing 54 students• Responsible for teaching students Excel, VBA Scripting, Python, Pandas, Matplotlib, SQL, SQLAlchemy, Flask, JavaScript, D3, R, Tableau, Machine Learning, Social Analytics, and Big Data

• Led team focused on predictive analytics of physical fire-safety audits. Responsibilities included being the sole point-of-contact for the business, development of overall approach (using a random forest model), division of labor, running weekly progress meetings, and overseeing the testing and validation of the model.• Mentored a graduate-level intern and worked together in order to develop a neural network model prototype to determine if claims were handled correctly or needed to be audited. This model used structured and unstructured data, ran on a Hadoop cluster, and is currently going into production.• Analyzed demographic and sales data in order to model the market opportunity available within thousands of micro-markets that completely cover the United States. These models were used to optimize marketing spend and set growth targets for the fire and auto businesses.• Used association rule mining for a pilot project in order to identify common patterns within vehicle repairs, which could then be used to detect commonly-grouped repair parts or identify potentially fraudulent repairs.• Owned entire model lifecycle for each project: working with business partners to develop ideas into prototype models with quantifiable business value, locating and extracting relevant enterprise data, performing work and directing team members, statistically testing product, and showcasing work to executives and end clients.• Presented seminars and tutorials to executives, business partners, and data science teams.• Publicly represented the company and spoke at a number of industry and academic events.• One of first two data scientists hired; helped develop data science program, hiring practices, repeatable project workflows (intake/scoping/etc.), and other practices. During this time our team grew from 2 data scientists to over 20 data scientists and 5 data science team leads.

Doctoral student, computer engineering. Primarily studying artificial intelligence, machine learning, neural networks, genetic algorithms, data mining, robotics. Working in the Machine Intelligence Lab (http://mil.engr.utk.edu/) doing research as well as managing the lab's high-performance computing cluster.

Primary lecturer and teacher for multiple 25-30 person sections each semester. Course title was "Computer Methods in Engineering Problem Solving," and centered around the use of Microsoft Excel and Matlab for solving engineering problems.

Lead developer for simulation development environment, including implementing a discrete event system specification (DEVS) simulator, designing and implementing the development GUI, and implementing a domain-specific language which can be transformed into simulatable model objects.Contract work performed for multiple projects. Projects include: the Complex Event Modeling Simulation &Analysis (CEMSA) architecture developed for Lockheed-Martin under contract from Department of Homeland Security; Distributed Instrumentation Test Environment (DTIE) created for the Joint Interoperability Testing Center (under the Defense Information Systems Agency, Department of Defense)

Worked directly under reseacher Dr. James Nutaro as a researcher on various projects. Projects included: modeling and predicting brain tumor growth using machine learning techniques, discrete event simulations for forest fires, DEVS simulation systems (RTI/HLA based) for military testing purposes, and developing user-friendly applications for modeling industrial processes.Work was completed under the Higher Education Research Experience (HERE) program and the Advanced Short-Term Research Opportunity (ASTRO) program

Provided first-level troubleshooting and miscellaneous assistance to computer lab users (for both Redhat/Ubuntu Linux and Windows labs). Responded to troubleshooting e-mail address as first-level support. Performed basic maintenance for lab equipment (printers, etc.). Opened and closed lab.

Performed research tasks for the University of Tennessee Machine Intelligence Laboratory. Tasks included programming Sony AIBO robots to navigate mazes (using MATLAB and Java), implementing and investigating neural network training algorithms and architectures, and maintaining lab server and website (Ubuntu server and Ruby on Rails-based website).

Only on-site IT employee, responsible for all support and training, as well as hardware configuration and maintenance. Responsible for new technology product purchases, such as phone and print systems. Created and maintained Microsoft Access databases for storing and analysing research data.