Wilfredo Lugo Beauchamp

Research Expertise

My research bridges the gap between machine learning and edge computing, with a focus on enabling real-world, resource-constrained applications in agriculture, environmental monitoring, and healthcare. Drawing from my background in industry and academia, I lead efforts that emphasize model compression, low-power inference, and system-level integration for embedded and edge devices.

My team and I design multidisciplinary solutions, often collaborating with domain experts to deploy AI at the edge where bandwidth, power, and latency are critical constraints. This includes work on quantization and pruning for medical diagnostics, interoperability testing across IoT platforms, and smart sensing for climate resilience and precision agriculture.

I also pursue partnerships with industry, where my students contribute to documentation, device validation, and module development using company-specific software and hardware. These collaborations not only address technical debt but also give students meaningful industry experience. My long-term goal is to democratize access to intelligent edge technologies through research that is impactful, deployable, and scalable.