Analog and power management circuits 
Hardware-efficient AI and ML 
Biomedical circuits and sensor interfaces Research goal: Cheap and fast DNA sequencing holds the promise of detecting and curing many diseases. To make this a reality, solid-state nanopores can be utilized to generate an electrical signal correlated to the DNA sequence. However, electrical noise corrupts this small signal which significantly reduces the ability to classify the molecules correctly. Together with the need to scale this approach to large arrays, to achieve the high troughput required for sequencing the human genome, there are many interesting opportunities for integrated circuit design.
Research approach: To overcome the two main problems mentioned above, both integrated circuit and signal processing techniques are utilized. A low noise transimpedance amplifier is necessary to keep the signal to noise ratio high. By using design techniques that have previously been used in other large array applications, such as camera sensors, the sequencing speed is greatly improved. Afterwards, an integrated machine learning model, capable of working with noisy signals, classifies the measured samples to reduce the amount of extracted data while maintaining the information.
