✔️ Design of readout integrated circuits for advanced sensor systems and detector arrays. Research includes low-noise amplification, signal conditioning, and analog-to-digital conversion for accurate acquisition of weak analog signals. Emphasis is placed on scalable circuit architectures and efficient sensor interfacing to support high-performance sensing and imaging applications

✔️ Development of hardware architectures for neuromorphic computing systems inspired by biological neural networks. The research focuses on efficient implementation of synaptic operations using emerging memory devices and analog computing techniques, enabling scalable and energy-efficient neural processing. System-level integration including circuit design, memory interfacing, and hardware implementation is explored to realize practical neuromorphic computing platforms.

✔️ Neuromorphic computing systems require flexible hardware platforms to control and evaluate prototype chips. FPGA and MCU-based controllers provide programmable interfaces for implementing control logic, generating electrical pulses, and acquiring experimental data from integrated circuits.

✔️ The research focuses on developing hardware verification platforms that enable efficient interaction between computing algorithms and neuromorphic hardware. These platforms support real-time control, measurement automation, and system-level evaluation, enabling reliable experimental validation of integrated circuits.