Taste of Tech Seminar: Leveraging Test to Improve RF Component Design Time to Market | Community Situated Edge Intelligence Systems for Human-Centered Decision Making
Time and Date
2/09/2026
11:45 AM – 1:00 PM (EST)
Agenda
Lunch: 11:45 – 12:00 Talk 1: 12:00 – 12:20 Talk 2: 12:20 – 12:40 Networking: 12:40 – 1:00
Talk 1: Leveraging Test to Improve RF Component Design Time to Market
Presentation Overview: Time to market for products like RF components continues to decrease while test cases rise. We will discuss core measurements and industry challenges faced, and how test can play an important role in decrease design to release. One area is using a common measurement and optimizing your test equipment to give you the best possible results.
Frank Makal
About the Speaker
Frank has 20+ years in the Test & Measurement industry focused on RF components. He is currently Director of Business Development — Components & Research, leading a team of seven that concentrates on aligning industry needs with short‑ and long‑term test solutions for power electronics, RF components, high‑speed digital design, and AI datacenter applications.
Talk 2: Community Situated Edge Intelligence Systems for Human-Centered Decision Making
Presentation Overview: Current public narratives around AI are dominated by large generative models, often obscuring other forms of intelligence that shape everyday decision making. This talk examines community situated edge intelligence systems that integrate sensors, data pipelines, and on device inference to support human centered decisions in real world contexts. Drawing on deployed systems, the presentation shows how socially grounded AI architectures can increase transparency, participation, and AI literacy by making data collection, model behavior, and system constraints visible and tangible. The talk argues for broadening AI system design beyond generative models to create more inclusive, accountable, and community responsive intelligent infrastructure.
Andrea Ramirez-Salgado
About the Speaker
Dr. Andrea Ramirez-Salgado is an Instructional Assistant Professor in the Department of Engineering Education at the University of Florida’s Herbert Wertheim College of Engineering. She holds degrees in Computer Science Engineering and Curriculum and Instruction and is committed to designing learning experiences that make artificial intelligence accessible, meaningful, and engaging for learners across disciplines and levels of expertise. She teaches in the master’s programs in Artificial Intelligence Systems and Applied Data Science, where she focuses on responsible and human-centered applications of AI. Her research explores the use of AI systems running on edge devices to empower learners—from K–12 to graduate students and lifelong learners—to design community-relevant solutions that integrate sensors, data, and intelligent systems. Her projects are supported by the National Science Foundation and the U.S. Department of State, among other sponsors.