All papers must be original and not simultaneously submitted to another journal or conference. Authors are invited to submit PDF files of full-length, original, unpublished manuscripts in IEEE proceedings format (no more than 6 pages). To enable blind review, the author list should be omitted from the main document. All submissions should be in PDF format through the online submission system:

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Contributions are sought in, but not limited to, the following areas:

1. Circuits, Reliability, and Fault-Tolerance (CRT): Analog/mixed-signal circuits design and testing, RF and communication circuits, design for testability and reliability, adaptive circuits, interconnects, static and dynamic defect-and fault-recoverability, and variation-aware design.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.