Best Paper Award at FAIEMA 202

Vasileios Moustakas, PhD student at the School of Electrical and Computer Engineering - NTUA and Academic Fellow at Archimedes, Athena Research Center, Greece, Konstantinos Cheliotis and Anna Mylona, both MEng students at the School of Electrical and Computer Engineering - NTUA and interns at Archimedes, Athena Research Center, Vassilis Alimisis, Postdoctoral Researcher at Archimedes, Athena Research Center, and Paul Sotiriadis, Lead Researcher at Archimedes, Athena Research Center, and a Professor at the School of Electrical and Computer Engineering - NTUA, received the Best Paper Award (PhD Symposium) at the

3rd International Conference on Frontiers of Artificial Intelligence, Ethics, and Multidisciplinary Applications (FAIEMA 2025), which took place on 18-19 September in 2025 at Stavanger, Norway.

The paper is titled "An Analog Low-Power Decision Tree Classifier Architecture for Parkinson’s Disease Prediction" and its abstract can be found below.

Abstract: This work presents a low-power analog integrated decision tree classifier for real-time Parkinson’s disease prediction. To achieve exceptionally low power consumption of 833 nW and a classification speed of 640 K inferences per second, the proposed design utilizes sub-threshold analog circuitry, including a ReLU circuit, sigmoid function circuit, tunable current mirrors, and a current comparator. It is implemented using the TSMC 90nm CMOS process. When tested on a Parkinson’s disease dataset, the classifier consistently maintained high performance despite variations in process, voltage, and temperature, achieving an average accuracy of 93.65%. Monte Carlo analysis and Process-Voltage-Temperature corner testing confirm its robustness and high accuracy, making it well-suited for low-power biomedical engineering applications as a front-end processor.