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The title of the thesis: Integrated circuit architectures for time-based intelligent sensor interfaces

Thesis defender: Ahmed M. Mohey
Opponent: Prof. Farshad Moradi, University of Southern Denmark
Custos: Prof. Jussi Ryynänen, Aalto University School of Electrical Engineering

Smart sensory systems have been increasingly adopted in our daily lives, driven by numerous applications and use cases, with billions of sensor nodes serving this purpose. A smart sensor node is typically equipped with interface, communication, and processing (named "in-sensor computing") functions. To realize these functions within a tiny node, the sensor interface must be efficient, compact, and scalable.

This thesis explores time-based architectures to realize scaling-friendly and efficient circuits for smart sensor nodes. Specifically, several time-based blocks for sensing applications are presented: (1) time-based sensor interfaces, with a focus on time-to-digital converter (TDC) architectures, which are core building blocks in these interfaces; (2) time-domain neural network accelerators, which are the main components to realize in-sensor computing for smart applications like human activity recognition (HAR).
The proposed building blocks achieve competitive performance metrics such as small size, low power consumption, high precision, and scalability in deep sub-micron technologies, thus enabling efficient smart sensing applications.

Key words: edge computing, in-sensor processing, multiply-and-accumulate, neural network accelerator, smart sensor, time-based sensor interface, time-of-flight, time-to-digital converter

Thesis available for public display 7 days prior to the defence at .