Paul Franzon

Biography

My teaching and research focuses on building microsystems (systems constructed of silicon chips, both analog and digital, and silicon micomachined components) for applications in computing, communications, sensors, robotics, and signal processing.

Education

• Ph.D. 1988
  Electrical Engineering
  University of Adelaide, Australia
• Bachelor's 1984
  Electrical Engineering
  University of Adelaide, Australia
• Bachelor's 1982
  Physics and Mathematics
  University of Adelaide, Australia

Recent Publications

• High-Speed Receiver Transient Modeling with Generative Adversarial Networks (2024)
• RD-FAXID: Ransomware Detection with FPGA-Accelerated XGBoost (2024)
• Solving the B-SAT Problem Using Quantum Computing: Smaller Is Sometimes Better (2024)
• Chiplet Set For Artificial Intelligence (2023)
• Generative Multi-Physics Models for System Power and Thermal Analysis Using Conditional Generative Adversarial Networks (2023)
• System Aware Floorplanning for Chip-Package Co-design (2023)
• Thermal Cycling and Fatigue Life Analysis of a Laterally Conducting GaN-based Power Package (2023)
• Thermal Estimation for 3D-ICs through Generative Networks (2023)
• A Deep Transfer Learning Design Rule Checker With Synthetic Training (2022)
• Design Obfuscation Through 3-D Split Fabrication With Smart Partitioning (2022)

Involvement

• IEEE EPS Society
  Associate Editor