Technology roadmapping is a comprehensive approach for strategic planning that integrates scientific and technological considerations into product development and business strategy. It provides a structured way to identify new opportunities and align innovations with organizational goals.

Roadmaps can take many forms, but they all share a common feature: the use of simple graphical frameworks to support the synthesis, alignment, and communication of complex strategic issues.

At our EMBS + CS Chapter Orange County Kickoff Session and Social Mixer, Chair Gora Datta will explore the rapidly expanding global digital health landscape and the career pathways emerging across this high-impact sector. As healthcare systems adopt AI-enabled tools, interoperable standards such as HL7, and scalable digital infrastructure, demand is growing for professionals in clinical informatics, health data engineering, cybersecurity, implementation science, product innovation, and public health analytics. This session will provide insight into the skills, research directions, and cross-sector opportunities shaping the future workforce—helping attendees position themselves for meaningful, future-ready careers in digital health.

Warm regards,
Pradyumna Kodgi

• Vice Chair, IEEE Engineering in Medicine & Biology Society (EMBS) – Orange County Chapter
• Secretary, IEEE Computer Society Orange County Chapter
• Senior Member, IEEE

Due to recent airport delays from the partial government shutdown, the talk has moved to a virtual format.

IEEE SSCS Oregon Chapter March Meeting and Seminar

Join us for a talk from SSCS Distinguished Lecturer Prof. Vanessa Chen from Carnegie Mellon University on Friday, March 27th, 2026. The seminar will be held from 11:00am to 12:00pm (PST) via a Virtual format. Please register for the meeting link and information.

Topic:

 AI-Enhanced RF/Mixed-Signal Circuits for Reliable Operations

Abstract:

AI-driven design and optimization are revolutionizing RF and mixed-signal circuits for operation in extreme environments, including high radiation and wide temperature ranges. This talk explores the use of reinforcement learning (RL) and generative models to improve circuit robustness and adaptability. RL-based self-healing techniques leverage embedded electromagnetic sensors for real-time monitoring and dynamic fault recovery, while generative models accelerate design space exploration, enabling resilient and efficient circuit topologies. The presentation will highlight AI-enhanced designs such as adaptive power amplifiers, PMICs, and multispectral sensors that enhance performance and reliability in harsh environments.

Speaker Biography:

Vanessa Chen received her Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University in 2013, where she worked on energy-efficient, ultra-high-speed ADCs with real-time calibration and interned at IBM T. J. Watson Research Center. She previously held circuit design roles at Qualcomm in San Diego and Realtek in Taiwan, focusing on self-healing RF and mixed-signal circuits. Her research explores AI-enhanced circuits and systems, including intelligent sensory interfaces, RF/mixed-signal hardware security, and ubiquitous sensing and computing. Dr. Chen is a recipient of the NSF CAREER Award, the CMU College of Engineering Dean’s Early Career Fellowship, Apple NSI Faculty Fellow, and the IBM PhD Fellowship. She has served on program committees for ISSCC, VLSI Symposium, CICC, A-SSCC, and DAC, as an Associate Editor for several IEEE journals, and is currently an IEEE SSCS Distinguished Lecturer for 2025–2026.

Abstract: Agentic AI is rapidly transforming enterprises from reactive chatbot deployments to autonomous, goal-driven systems capable of reasoning, planning, and acting across complex business workflows. In this technical talk, Agentic AI in Enterprises: From Fundamentals to Production Implementation, we move from first principles—agent architectures spanning perception, memory, reasoning, and action; Chain-of-Thought and advanced reasoning patterns such as ReAct and reflection; Retrieval-Augmented Generation (RAG); tool use; and memory hierarchies to real-world production systems delivering measurable ROI. Through three detailed end-to-end case studies in e-commerce customer support, healthcare prior authorization, and autonomous procurement, attendees will see complete workflow breakdowns illustrating how agents integrate with enterprise systems, apply multi-step reasoning, manage long-running context, and operate securely at scale. We will also confront the hard problems: hallucination, prompt injection, observability for non-deterministic systems, governance, cost control, and build-vs-buy strategy. Designed for engineering leaders, AI practitioners, architects, and technical executives, this session connects foundational concepts with real-world operational considerations, providing practical architectural patterns, evaluation frameworks, and implementation guidance to help organizations deploy agentic AI systems that are reliable, secure, and scalable in production environments.