Eric King of Cirrus Logic

Mixed-signal integrated circuits are among the most complex products in semiconductor design. A single device may integrate analog circuits, digital processing, power conversion, embedded software, and system-level control. As this complexity has grown, development
processes have often evolved toward a production-line model in which architects define specifications and responsibilities are divided into specialized engineering “silos,” connected primarily through documents and phase-gate handoffs. While this approach improves organizational scalability, it can unintentionally constrain system-level innovation by limiting designers’ visibility into the broader system behavior.

A system, however, is not merely a collection of parts but a set of interacting elements whose value emerges from the relationships between them. Systems architecture focuses on understanding and shaping these relationships across the development process. Systems architects act as mentors, cultivating a shared understanding across the design team. Additionally, by maintaining continuity across organizational and design boundaries, systems architects help the team understand how their contributions impact subsystem and overall performance, and ultimately the value delivered to the customer.

This talk explores this philosophy of systems architecture in mixed-signal semiconductor development using mobile audio amplifiers and inductive sensing ICs as case studies. Systems thinking results in collaboration and reasoning about complex engineering problems that enabling technical clarity and sustained innovation across the entire team. As mixed-signal SoCs continue to grow in complexity, this approach becomes increasingly essential.

Biography:

Eric King is an Engineering Fellow at Cirrus Logic in Austin, Texas, with more than 30 years of experience in mixed-signal IC design, audio systems, and power management. His work focuses on high-eQiciency audio architectures and multi-level power conversion for mobile and automotive systems, including architecting a flagship mobile audio amplifier that has shipped more than four billion units worldwide. In addition to audio amplifiers, Eric has contributed to the development of a broad range of high-volume mixed-signal products, including battery-management and Li-ion fuel gauge systems, power-factor-correction controllers, TRIAC-dimmable LED drivers, inductive sensing technologies, and wireless communication chipsets. Over the course of his career, he has also worked on cellular and WLAN transceivers and advanced system architectures spanning audio, power, sensing, and connectivity. Eric holds more than 130 U.S. patents and was named Inventor of the Year (2024) by the Austin Intellectual Property Law Association. He received his M.S. from the University of Texas at Austin and B.S. from the University of Tennessee.

Karen Panetta of Tufts University School of Engineering

Digital Twin technology has been a foundational technology for accelerating product development across all manufacturing environments. Meanwhile, Artificial Intelligence (AI) has opened new avenues to model and experiment across every discipline. This talk will present the evolution of the digital twin and explore the symbiotic relationship of the Digital Twin and AI as well as some of the most exciting fields of use or this “power couple”

Biography:

Dr. Karen Panetta received the B.S. degree in computer engineering from Boston University, Boston, MA, USA, and the M.S. and Ph.D. degrees in electrical engineering from Northeastern University, Boston. She is a Distinguished Professor and the Dean of graduate engineering education and a Professor with the Department of Electrical and Computer Engineering at Tufts University, Medford, MA, USA. She holds secondary appointments in Computer Science, Mechanical Engineering and the Tufts School of Dental Medicine.  She is the Director of the Panetta Vision and Sensing System Laboratory. She is the Co-inventor of the first Digital Twin. Her algorithms are widely used in Artificial Intelligence, simulation, modeling, and image processing systems deployed around the world. Her work has spanned every arena including health, safety, security, ocean and wildlife conservation applications to protect and save lives. IEEE-USA  awarded her the 2026 Robert S. Walleigh Distinguished Contributions to Engineering Professionalism Award. She is the  2026 recipient of the IEEE Mildred Dresselhaus Medal and recipient of the IEEE Ethical Practices Award and the Harriet B. Rigas Award for Outstanding Educator. Karen serves as Editor-in-Chief of the award-winning IEEE Women in Engineering Magazine. Her leadership roles include President of the IEEE-HKN honor society and IEEE Awards Board Chair, Vice-President of the IEEE Systems, Man and Cybernetics Society and IEEE-USA Vice-President of communications and public affairs. She served as the Chair for the IEEE Women in Engineering, overseeing the world’s largest professional organization supporting women in technology.  Karen is the CEO and Co-founder of Tessera Intelligence Inc., Co-founder of Sea Deep Inc. She is a member of the National Academy of Engineers, and a Fellow of the National Academy of Inventors, IEEE, European Academy of Sciences and Arts, AAIA, NASA JOVE and AAAS. U.S. President Obama awarded her the Presidential Award for Engineering and Science Education and Mentoring for her Nerd Girls program for empowering young women in STEM.

Balakrishnan Prabhakaran of AI Plus Institute - U at Albany SUNY

Advances in AI, especially for Agentic AI, are disruptively transforming many walks of like including research and development in science and engineering. These AI systems can process enormous amounts of data quickly for reasoning, planning, and autonomous decision-making. This powerful capability makes AI an excellent companion for scientists to perform literature review, generate hypotheses, conduct experiments, and analyze results.

This talk examines current research in AI and Agentic AI for literature review, categorizing existing systems and tools, and highlighting their integration across fields such as chemistry, biology, and materials science, and explores related questions: (a) What are the critical challenges for AI-based scientific discoveries in terms of literature review automation, system reliability, and ethical concerns? (b) What could be key evaluation metrics and implementation frameworks for AI-based scientific discoveries? (c) How do we address the key aspect of Human-AI alignment so that researchers – and AI – understand each other’s requirements and work together as a team?

Biography:

Prof. Balakrishnan Prabhakaran is the Director of the AI Plus Institute and an Empire Innovation Professor in the faculty of Computer Science Department, University at Albany (State University of New York, Albany). Dr. Prabhakaran also served as program director for the National Science Foundation’s Human-Centered Computing Program in the Information and Intelligent Systems Division from 2019-23 and as “theme lead” for the NSF AI Institute on Human-AI Interaction. He received the prestigious NSF CAREER Award FY 2003 for his proposal on Animation Databases. He was selected as an ACM Distinguished Scientist in 2011. He has been serving in the steering committees for several top research conferences, including the IEEE International Conference on Health Informatics (ICHI). Prabhakaran is serving on the editorial boards of high-impact journals such as Elsevier’s Artificial Intelligence in Medicine and Springer’s Journal of Health Informatics Research. He is currently serving as the Editor-in-Chief for IEEE MultiMedia. Prabhakaran has also served as General Chair and Technical Program Committee Chair for several important research conferences in health informatics and multimedia. Prof Prabhakaran’s research has been funded by Federal Agencies such as the National Science Foundation (NSF), the USA Army Research Office (ARO), and the US-IGNITE Program. Dr. Prabhakaran works in the broad area of collaborative, mixed reality systems for healthcare and STEM education. These systems involve multi-modal devices, such as haptic devices giving force feedback and body sensors, integrated with mixed reality. Some of these systems have undergone clinical trials for use by amputees to manage phantom pain and for remote evaluation of stroke patients in a clinical setting, as well as in a home setting without expert guidance.