Daniel Ricks Email & Phone Number

Sandy, Utah, United States

• Designed and built a solution for scalable software test generation using Python and AWS.
• Created solutions for both anomaly and region detection in data sequences and images, respectively.
• Deployed and maintained models using Kubernetes and Tensorflow Serving.
• Used Langchain and GPT-4/Claude to build a POC for test generation using only images.

Sandy, Utah, United States

• Created POC for software test generation using Tensorflow.

• Designed and created an NLP system for dataset augmentation in Python for AI Dungeon 2.

• Created a recommender system for pairing clinicians with relevant educational courses.
• Constructed pose estimation pipeline for exercise video label automation.

• Weighed pros and cons of implementing a machine learning approach vs. a rule-based system. Decided on a simple solution that met needs and fit the goals of the company.
• Created back-end code for an online analytics platform in JavaScript.
• Implemented automated load testing using AWS RDS, Lambda functions, and loader.io.

• Designed a database schema and automated data transfer using third party APIs.
• Used AWS Aurora DB to set up a permanently accessible solution for the team.

• Amazon Alexa Prize EVE Team Member ---
• Designed and implemented a chatbot for Amazon’s Alexa Prize Competition in 2018 (one ofeight teams in the world chosen). Used Python and AWS.
• Made architectural decisions that improved response relevance by 15%, and reduced relevant code by over 200%.--- Deep Learning Researcher ---
• Created a learning environment for interactive fiction (text-based games), which inspired and was cited by Microsoft’s TextWorld. Used Python. (Hosted at github.com/danielricks)
• Five publications, most about novel uses of high-dimensional embedding spaces for knowledge extraction from text. Notable conferences include IJCAI, and NeurIPS and AAAI workshops.
• Implemented deep neural networks, GANs, RNNs, Siamese residual networks, and styletransfer networks.

• Constructed an automated pipeline to digitize historical documents, reducing the required time by over 75%. Used bash, Python, Java, Indri, Tesseract OCR, OmniPage Pro, Abbyy FineReader, and the Machine Learning for.

• Helped implement a multi-user computer-aided design system for Boeing (Patent #20150120252, CAx Model Synchronization). Used C# and Siemens NX.

Master Of Science - Ms, Computer Science

Specialization: Machine Learning

Bachelor Of Science, Computer Science

Member of the BYU Association for Computing Machinery