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• Constructed an automated pipeline to digitize historical documents, reducing the required time by over 75%.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 Language Toolkit.

• 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