Sydney’s research includes the design, fabrication, and characterization of multiferroic microelectromechanical systems (MEMS) sensors for sensing magnetic fields in biomedical and navigation applications. Magnetic field sensors are often large, requiring cooling systems, which increases the amount of power consumed. Utilizing MEMS sensors minimizes their power consumption while maintaining high levels of sensitivity.

A.J. works on photonic deep neutral network, specifically for image classification. He designs chips that capture light and utilizes electro-optic modulators for computations on photons. This work enables image classification approaching the speed of light.

Christopher is studying wave-matter interaction in metamaterials and metasurfaces with the goal of enhancing communication, computation, and sensing devices. He is applying Inverse-Design methods to develop metamaterial analog computers and spatiotemporal metasurfaces. These technologies hold promise to revolutionize the way devices process information by allowing them to solve complex problems at near the speed of light while consuming a fraction of the energy of conventional methods.

Keshava currently uses mathematical neuron models to build networks that can learn from event volumes, which are streams of spiking information generated by event cameras from visual stimuli. These networks are then applied to robotics tasks such as pose and depth estimation. He plans to design a physical substrate for ensemble-based neural computation with non-volatile memory devices that could more closely emulate self-organization of the mammalian visual cortex.

Henry focused on mixed-signal integrated photonic and electronic co-design. Specifically, he focused on two areas: 1) creating stable electro-optical references for multi-phase clocking applications, and 2) techniques for laser wavelength stabilization. For 1, the creation of stable optical clock signals facilitates low-loss, high bandwidth clock distribution across mm-sized chips. While for 2, laser wavelength stabilization is important for optical communication, metrology, and spectroscopy, to name a few.

Zac’s research aims to provide robots with the contextual reasoning abilities needed to achieve complex tasks such as disaster response. Zac is particularly interested in a robot’s ability to understand language and sensory information, in order to interpret and react to its environment for a given task. This research applies to single-and multi-robot planning domains in large scale environments.

Raha hopes to apply her background in integrated electronics and chip design to the emerging field of silicon photonics, which combines optics and circuit design principles to address a myriad of problems that currently plague silicon electronics. Specifically, Raha is interested in using electronic-photonic co-design to enable low-power, high-speed data transfer and communication.