VLSI Design: ASIC and FPGA design, microprocessors/micro-architectures, embedded processors, analog/digital/mixed-signal systems, NoC, SoC, IoT, interconnects, memories, bio-inspired and neuromorphic circuits and systems, BioMEMs, lab-on-a-chip, biosensors, implantable and wearable devices.
VLSI Circuits and Power Aware Design: analog/digital/mixed-signal circuits, RF and communication circuits, chaos/neural/fuzzy-logic circuits, high-speed/low-power circuits, temperature estimation/optimization, power estimation/optimization, machine-learning for design and optimization of analog/digital/mixed-signal circuits, clock and power network optimization through applied machine-learning.
Computer-Aided Design (CAD): hardware/software co-design, high-level synthesis, logic synthesis, simulation and formal verification, layout, design for manufacturing, CAD tools for biology and biomedical systems, algorithms and complexity analysis.
Testing, Reliability, Fault-Tolerance: digital/analog/mixed-signal testing, reliability, robustness, static and dynamic defect- and fault-recoverability, variation-aware design.
Emerging Computing & Post-CMOS Technologies: nanotechnology, molecular and quantum computing, approximate and stochastic computing, sensor and sensor networks, post CMOS VLSI.
Hardware Security: trusted IC, IP protection, hardware security primitives, reverse engineering, hardware Trojan, side-channel analysis, CPS and IoT security.
VLSI for Machine Learning and Artificial Intelligence: hardware accelerators for machine learning, computer architectures for machine learning, deep learning, brain-inspired computing, big data computing, cloud computing for Internet-of-Things (IoT) devices.
Microelectronic Systems Education: pedagogical innovations using a wide range of technologies such as ASIC, FPGA, multicore, GPU, educational techniques including novel curricula and laboratories, assessment methods, distance learning, textbooks, and design projects, Industry and academic collaborative programs and teaching.