I give many presentations throughout the year at various universities, companies, workshops, and conferences. All of our conference papers have their video linked on the publications page. Due to COVID-19, many of these presentations were presented asynchronously and/or recorded, so I am putting links to the videos here for broader dissemination.

The Internet-of-Medical Things (IoMT): An opportunity for ubiquitous health monitoring

Short Course at CICC 2021 as part of an Educational Session on “Low Power Wireless for Biomedical Sensing and IoT”
Abstract: With increases in healthcare costs, a constantly growing population, and a limited supply of physicians, radical changes must be made for the healthcare system to remain sustainable. Consumer electronics are ubiquitous and inexpensive today, whereas most medical devices are costly, and access is primarily limited to hospitals. A compelling solution is to alleviate some of the burden on the healthcare system by equipping the general population with tools to track and monitor their own health. Just as miniaturization of computers, which once filled large rooms, into the microprocessor revolutionized the computer industry, miniaturization of medical tools has the potential to restructure our healthcare system in a similar fashion. This talk will start by introducing biosensors and the challenges in designing power efficient analog front-ends. The second part will describe examples of low power MedRadio transmitters. Case studies will be provided with a focus on the circuit and system-level challenges.

Getting the Most Out of a Little:
Ultra-low Power Circuit Techniques for the IoT

Short Course at VLSI 2021 as part of an Educational Session titled “Advanced Circuits and Systems for IoT Sensors”

Abstract: Advances in semiconductor technology over the last several decades have caused an influx of electronic devices into our daily lives, leading to the emergence of the Internet-of-Things (IoT) era. The IoT is a cluster of many miniaturized devices (also called sensor nodes) that unobtrusively capture data from our lives and the surrounding environment. The IoT will have a transformative impact on a wide variety of applications ranging from biological sensing such as wearable sensors to track our well-being, to physical sensors for industrial and environmental monitoring, to entertainment and infrastructure-related devices for smart-homes and smart-cities.
From a circuit design perspective, enabling the IoT requires overcoming a significant technological hurdle: maximizing energy efficiency. This has steered the focus of research towards sub-µW operation to extend the battery life or support wireless/harvested power for long-term continuous monitoring. Unfortunately, ultra-low-power consumption often comes at the expense of temperature robustness. Techniques to reduce power consumption while maintaining robustness to temperature variation will be covered in this talk. Emphasis is placed on analog front-ends, oscillators, and RF transmitters with examples of each.

Note: This talk derives the noise efficiency factor (NEF) and power efficiency factor (PEF) from first principles. It also discusses techniques that can be used to overcome these “fundamental” limits through gm-boosting/OTA-stacking.

Hitting the diagnostic sweet spot: Point-of-care SARS-CoV-2 salivary antigen testing with an off-the-shelf glucometer

Abstract: Significant barriers to the diagnosis of latent and acute SARS-CoV-2 infection continue to hamper population-based screening efforts required to contain the COVID-19 pandemic in the absence of effective antiviral therapeutics or vaccines. This talk describes an aptamer-based SARS-CoV-2 salivary antigen assay employing only low-cost reagents ($3.20/test) and an off-the-shelf glucometer. The test was engineered around a glucometer as it is quantitative, easy to use, and the most prevalent piece of diagnostic equipment globally making the test highly scalable with an infrastructure that is already in place. In clinical testing, the developed assay detected SARS-CoV-2 infection in patient saliva across a range of viral loads – as benchmarked by RT-qPCR – within one hour, with 100% sensitivity (positive percent agreement) and distinguished infected specimens from off-target antigens in uninfected controls with 100% specificity (negative percent agreement).