EDBT 2026 Demo / reviewers in the wild / expert
Shuanghua Liu
dblp:370/6492
· DBLP profile ↗
4ranked-venue papers
3as first author
4since 2021 · last 2026
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 4 · 3 first-author · 4 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | A Low-Power Tunable Dynamic-Range ISFET Sensor with In-Pixel Incremental Σ∆ Quantisation
Shuanghua Liu, Pantelis Georgiou |
ISCAS | 1 |
| 2026 | An ISFET based Multi-Modal Low-Power Chopper-Stabilised Analogue Front-End for Wearable Physiological and Sweat Monitoring
Shuanghua Liu, Haotian Yuan 0003, Junming Zeng, Pantelis Georgiou |
ISCAS | 1 |
| 2026 | FPGA-Accelerated Real-Time Image Reconstruction For CMOS Electrochemical Sensing Arrays
Tom Zhou, Shuanghua Liu, Pantelis Georgiou |
ISCAS | 2 |
| 2024 | A Low Power Analogue Compressed Sensing Approach for CMOS ISFET ArraysabstractIn this work, we propose a novel approach to integrate a scalable compressed sensing methodology in the analogue domain with a CMOS ISFET array. A current conveyor is employed with a switched capacitor to encode the output current from each ISFET sensor to a corresponding charge onto a capacitor, following by a pseudo-random non-zero diagonal sampling matrix that is generated by Linear Feedback Shift Registers (LSFR) for array sampling. The design also features a 12-bit Successive Approximation Register (SAR) ADC, enabling power efficient conversions at 50 KSamples/s using a 1.25 MHz clock, with an ENOB of 10.3. The 32 × 32 array is divided into 16 clusters, each containing 64 pixels arranged in an 8 × 8 configuration serving as a compressed sensing unit block. The overall system is designed under a 65 nm process occupying a silicon area of 0.375 mm2. It operates at a programmable frame rate of 30 - 240 fps, with an overall power consumption of 17.13 -117.23 μW, and a lowest energy per pixel of 394 pJ in compressed sensing mode. We verify the performance of the system with a PSNR comparison for image quality under two scenarios where CS is either enabled or disabled. Shuanghua Liu, Junming Zeng, Pantelis Georgiou |
ISCAS | 1 |