Juan D. Castro

Background

About Juan D. Castro

Driving innovation at the intersection of wireless communications, AI/ML, and cloud computing to tackle the world’s toughest challenges in science and technology. As a Lead Application Engineer at Ansys, I work at the convergence of RF/microwave simulations, AI-driven radar processing, and HPC/cloud-based workflows. Collaborating with high-tech clients across North America, I leverage HFSS, RF Channel Modeler, AEDT Icepak, and Ansys Cloud services to develop solutions that meet performance and reliability standards. My work bridges RF engineering with AI/ML, driving next-generation connectivity, radar perception, and AI-enhanced RF signal processing. Exploring AI/ML in RF simulations, digital twins, and radar intelligence. I aim to develop AI-powered frameworks that optimize product design, sustainability, and mobility while advancing real-time RF perception and intelligent wireless systems. Core Expertise • RF Engineering – Designing and optimizing antennas, RF circuits, and RF systems for 5G, radar, ADAS, IoT, and emerging wireless technologies. • Cloud and HPC Integration – Streamlining simulations with AWS/Azure cloud solutions, data lake architectures, and HPC workflows for scalability and efficiency. • AI/ML for RF and Simulations – Applying deep learning (DNNs, generative models, SSL) to accelerate RF workflows and optimize radar intelligence. • Interdisciplinary Solutions – Merging electromagnetics, computational science, and AI to drive transformative, future-ready innovations. Technical Proficiencies • Tools – Ansys HFSS, RF Channel Modeler, AGI STK, Keysight ADS. • Programming – Python, MATLAB, C/C++ for scientific computing and AI-driven automation. • AI/ML Frameworks – TensorFlow, PyTorch, Keras, generative AI, & LLMs for RF/AI applications. • Cloud and HPC – Skilled in AWS, Azure, and high-performance computing integrations for RF simulations at scale. • Leadership – AI strategy, entrepreneurship and business foundations from Wharton, enabling strategic decision-making in AI-driven industries. Research and Interests • AI-Driven Wireless Ecosystems – Advancing mmWave, 5G/6G, IoT, AI Radios, and next-gen connectivity solutions with deep learning to optimize performance. • Generative AI and Digital Twins – Revolutionizing RF design and engineering workflows with AI-driven modeling and simulation frameworks. • AI in Finance – Applying ML-based predictive modeling for market dynamics and smarter investment strategies. Let’s collaborate to drive breakthroughs in AI, RF/microwave engineering, and cloud-driven wireless innovation.