Keynote Speakers

Over the past ten years, mm-wave radars have become entrenched as a key sensor for advanced driver assistance systems (ADAS).  This trend has coincided with the development of highly integrated CMOS radars.  This talk will start with the latest trends in mm-wave sensor hardware and then discuss emerging applications, including robotics, building automation, life signs detection, gesture recognition, and more.

Over the last decade, a convergence of new concepts in materials science, mechanical engineering, electrical engineering and advanced manufacturing has led to the emergence of diverse, novel classes of 'biocompatible' electronic and microfluidic systems with skin-like physical properties and wireless operational capabilities.  A broad range of clinical-grade sensors of physiological health can be deployed into these platforms.  The resulting applications address health care challenges from the earliest to the latest stages of life, with demonstrated uses in both high and low resource settings, at the hospital and in the home.  This talk presents an overview of translational activities in this area of technology, currently in progress at the Querrey-Simpson Institute for Bioelectronics at Northwestern University.

X-rays, high-energy electromagnetic radiation, are often used in medical diagnostics. Medical X-ray detectors such as computed tomography, radiography, and dental X-ray are widely used in our daily lives. In addition, the X-ray detectors are often used in non-destructive testing (NDT) and baggage inspection for security. Therefore, the market size of the X-ray detector has increased in recent years, and its forecast is also very prospective. The size of X-ray detectors must be as large as the target, simply because the X-rays cannot be condensed through a lens.

MEMS inertial sensors are widely used in consumer, healthcare, industrial, automotive, aerospace, and defense applications. In some applications, it is desirable to have wide bandwidth to measure frequency-rich signals such as audio or vibrations. This talk will focus on a circuit technique to increase the bandwidth of low-noise capacitive MEMS accelerometers, called beyond-resonant-frequency sensing. The talk will presents the design of two prototypes: an ±8-g, 4 kHz, 25 g/√Hz accelerometer and a ±30-g, 8 kHz, 60 g/√Hz accelerometer. Their use in various wide-bandwidth applications will also be discussed.

Quantum computing has emerged over the past decade as a practical approach to solving certain classes of problems for which no other tractable approach is known. However, quantum computing technology is still in its infancy—analogous to integrated circuit technology in the early 1960s—and transitioning this technology to the point where large-scale fault-tolerant quantum computing is feasible requires overcoming many daunting engineering challenges.

The intersection of mixed-signal circuits and machine learning (ML) is expected to result in significantly  more intelligent and efficient edge sensing systems.  The main aim of this talk is to point out the possibilities and challenges of using mixed signal circuits in ML accelerators intended for sensor interfaces, and to equip participants with the knowledge needed to evaluate and participate in this rapidly evolving and exciting field.  Current work in this area will be presented, including various analog and digital implementations.  Finally, some of the complex challenges of incorporating mixed signal acceleration into sensor systems will be discussed, as well as future directions.

Many industrial applications rely on off-chip temperature sensors such as diodes, RTDs, thermistors and thermocouples. However, their readout often requires complex external circuitry. This paper describes a readout IC (ROIC) that integrates all the required circuitry in a single chip. It contains current sources for sensor biasing and low-noise buffers that drive three 24-bit delta-sigma ADCs. A novel charge-pump extends the buffers’ input range to ground, while current source rotation eliminates thermocouple effects in RTD and thermistor measurements, as well as current mismatches in 3-wire RTD measurements. The maximum error contribution of the ROIC is 1.6C for thermocouples, 0.25C for diodes and  0.1C for RTDs and thermistors, over each sensor’s specified temperature range.

Implantable neural interfaces hold the promise to offer new therapies for brain disorders that may no longer respond to conventional treatments. Despite significant advances in neural interface microsystems over the past decade, the small number of recording and stimulation channels and limited embedded processing in the existing clinical-grade technologies remain a barrier to their therapeutic potential.