Late Breaking Research

Authors are invited to submit original, unpublished manuscripts in IEEE proceedings format (4 Pages). To enable blind review, the author information should be omitted from the submission.

The manuscript as a single PDF is to be submitted online through Easychair. The IEEE Manuscript Template for Conference Proceedings should be used, which can be found here.

Authors can submit their papers for the main track of IEEE ISVLSI 2025, via EasyChair.

Topics of Interest for Late Breaking Research papers include:

• Circuits, Reliability, and Fault-Tolerance (CRT):
  Analog/mixed-signal circuits design and testing, RF and communication circuits, adaptive circuits and interconnects, design for testability, online testing techniques, static and dynamic defect- and fault- recoverability, variation aware design, VLSI aspects of sensor and sensor network.
  
• Computer-Aided Design and Verification (CAD):
  Hardware/software co-design, logic and behavioral synthesis, simulation and formal verification, physical design, signal integrity, power and thermal analysis, statistical approaches.
  
• Digital Circuits and FPGA based Designs (DCF):
  Digital circuits, chaos/neural/fuzzy-logic circuits, high speed/low-power circuits, energy efficient circuits, near and sub-threshold circuits, memories, FPGA designs, FPGA based systems.
  
• Emerging and Post-CMOS Technologies (EPT):
  Nanotechnology, molecular electronics, quantum devices, optical computing, spin-based computing, biologically-inspired computing, CNT, SET, RTD, QCA, reversible logic, and CAD tools for emerging technology devices and circuits.
  
• System Design and Security (SDS):
  structured and custom design methodologies, microprocessors/micro-architectures for performance and low power, embedded processors, analog/digital/mixed-signal systems, NoC, power and temperature aware designs, hardware security, cryptography, watermarking, and IP protection, TRNG and security-oriented circuits, PUF circuits.
  
• VLSI for Applied and Future Computing (AFC):
  Neuromorphic and brain-inspired computing, quantum computing, circuits and architectures for machine learning and artificial intelligence, methodologies for on-chip learning, deep learning acceleration techniques, applications for and use-cases of learning systems, sensor and sensor network, electronics for Internet of Things and smart medical devices.