Generative AI: Tech Talk with Henry Ruiz of Google
Sunday, May 14 @ 2:00 pm - 4:00 pm HST
Hosted by: GDG Oahu
Generative AI is a rapidly growing field with the potential to revolutionize many industries. In this talk, Henry Ruiz will discuss the basics of generative AI, including its applications in computer vision, natural language processing, and other areas. He will also share his insights on how engineers can harness the power of generative AI to solve real-world problems.
Henry will cover topics such as:
- The different types of generative AI models
- How generative AI is being used to create new products and services
- The challenges and opportunities of using generative AI in engineering, and the road ahead
Henry is a Google Developer Expert in Machine Learning and a Ph.D. student in Interdisciplinary Engineering at Texas A&M University. His research focuses on using generative AI to solve agriculture problems. He is also a full-stack developer and has experience with a variety of machine learning libraries.
We would love to cover any questions about Generative AI that you might have! Feel free to submit your questions via this Google Form: https://forms.gle/a9ssWK4wo4NBas7q6
Don’t miss out on this exciting opportunity, we hope to see you there!
About Henry Ruiz
As part of my dissertation, I have developed GPR-Studio, user-friendly software that allows users to process and analyze GPR(Ground penetrating radar) data that could be used for several engineering and science applications, including agriculture, geotechnical, transportation, archaeology, geoscience, etc.
Recently we published a paper entitled “The Fortress Beneath: Ground Penetrating Radar Imaging of the Citadel at Alcatraz: 1. A Guide for Interpretation”, where we used GPR studio to analyze the data. This study points to developing a radar facies classification scheme specific to cultural heritage investigations.
My Ph.D. research areas are Geophysics tools (Ground Penetrating Radar), mathematical simulation, electromagnetism, signal processing, Machine Learning, and Deep Learning.