My research combines microelectronics and nanotechnology into hybrid or integrated, self-powered, systems. There is a growing need for these types of autonomous devices as more and more intelligence is embedded in the world around us. They serve on the front-lines of the Internet-of-Things (IoT), linking the physical world with the virtual. My research is aimed at exploring a variety of technological challenges that enable autonomous systems including energy supply, energy efficiency, system integration/packaging, miniaturization, and of course application specific transducers that interact with their environment.

Applications in healthcare and neuroscience

SEAM_illustration One of the few remaining truly great mysteries is the specific functionality of the brain and the central and peripheral nervous systems. Better understanding of the underlying mechanisms will one day lead to more effective therapies for a host of neurological conditions. Due to the fragile and inaccessible nature of the central nervous system micro- and nano-systems can play an important role in both fundamental science as well as therapeutics. I am working to develop sophisticated electrophysiological interfaces for extracellular recording and stimulation. Enabled by direct integration with advanced CMOS technologies we are able to achieve a high degree of information parallelism so that neuroscientists can better elucidate network dynamics. In turn, this research directly fuels our development of Smart Energy-Autonomous Micronodes (SEAMs) that record and stimulate in closed-loop to mitigate neurological conditions like Epilepsy and Parkinson's. Ideally these devices will reach a level of sophistication that will enable them to be unperceived by the user, much like a pacemaker for the brain.

Ultra low-power electronics and power management

mEDC_front_end Autonomous systems, whether embedded within the IoT or a singular medical application need end-to-end optimization that includes the electronic interface. A new energy-centric design paradigm is needed in order to optimize the energy consumption on one hand, and the energy supply on the other. My research focus is on developing ultra-low power mixed-signal microelectronic systems that enable system autonomy. In order to achieve this goal innovation is needed not only on key building blocks, but also on how those components interact at the system level. I am working on developing ultra-low power precision instrumentation for neuroscience relying on new architectural designs as well as effectively exploiting the full range of MOSFET operational regimes (weak to strong inversion) in order to optimally extract key benefits along the way. Additionally, in the area of power management I am looking into techniques to maximize the power extracted/transferred from energy harvesters and receivers, as well as how to optimally transfer this energy to storage and/or to supply variable loads. For the most part this involves developing extremely efficient active adaptive circuits that can effectively deal with the dynamics on both the input and load side, minimizing components and increasing integration (especially in medical applications), and effectively dealing with multiple supply rails and high dynamic range on the supply side.

Energy harvesting and wireless energy transmission

PFIG_generations Current energy sources for mobile and distributed applications are clearly limiting. Energy supply has to become a more seamless aspect of mobile devices. One of the most ubiquitous sources of renewable energy is found in the motion of structures, nature, and humans. My focus is on developing technologies that can efficiently harvest motional energy while remaining insensitive to the specific application. The main problem with kinetic energy harvesters is that they need customization for specific environments and that limits their usability. However, in many applications like use on body-worn or implantable devices this is not possible because the energy is intermittent and has variable characteristics. During my doctoral work I developed a patented technology to harvest energy efficiently in these types of scenarios. I am currently developing approaches to extend motion harvesting to multiple axes. However, energy harvesters are not effective in many applications due to their size or availability of energy. Neuroscience, where size is critical, is a good example. I am developing electromagnetic and acoustic methods to transmit energy deep inside human tissue. These technologies will play an important future role in the general area of mobile electronics and autonomous systems.

Nanofabrication and packaging

I am developing new process technology innovations as needed to support the development of new transducers and components as well as system integration issues like packaging. Examples include high-aspect ratio silicon processes that can support a wide array of geometries, etch shapes, and openings, hermetic wafer-level packaging that allows for the integration of polymer waveguides for optical neural stimulation electrodes, low-temperature wafer bonding, sputter deposition of high coupling-factor piezoelectrics, and others. A large part of my research involves developing methods to combine standard CMOS through either homogenous or heterogenous integration with a variety of substrates including thin polymers, in order to develop flexible and mechanically matched intelligent systems for implantation.