Interacting and extracting information from electromagnetic fields is one of the core foundations of all technologies that involve us interacting and understanding our environment. This extends right from detecting tiniest traces of proteins in body fluids to optical imaging to sending information via wireless communication. Our interest lies in innovating radically new end-to-end technologies that can enable new forms of information extraction through new integrated and chip-scale technologies for communication and imaging to health and diagnostics.



Intelligent, Adpative and Secure millimeter-Wave Sensing and Communication Systems

Wireless communication and sensing are undergoing fundamental changes as spectral ranges in the mm-Wave are opening up (for 5G and beyond) with orders of magnitude larger spectrum than we ever had access to. These new spectrum will serve as the back-bone for the next-generation of wireless networks allowing high-speed, low-latency connecivity to enable the next-generation of autonomous systems. Architectures that can serve future communication needs to be smart, efficient, programmable, be flexible in its frequency of operation and self-correct and self-heal. We are interested in the entire gamut of innovations from programmable transceiver architectures to programmable antennas and electromagnetic interfaces collectively approaching toward universal transceiver front-ends.



Programmable Chip-scale Terahertz Systems

TeraHertz is a wonder spectrum sandwiched between microwave and infrared with incredible properties but with serious lack of technology that plagues the spectrum. Our research is focused on new methods that crosscut circuits, electromagnetics, signal processing and optimization methods that can not only enable efficient chip-scale technology at THz frequencies, but also enable programmability in these systems for a wide range of applications in sensing, communication and imaging. Examples include programmable THz waveform synthesis and radiation, source-free beamforming with sub-wavelength field modulation and exploiting scattering for spectral estimation .


AI for Design Methodologies

This is a collaborative effort where we are exploring radical approaches to design methodologies in integrated systems that takes human intuition out of system design methods through optimization or data-driven learning methods. The questions that we are interested to explore here are the following: Do intuition-based design approaches limit system functionalities? Is the design space constricted as a result? How would a AI-driven architecture look like? While primarily driven by algorithmic fronts, we are interested in exploring the design space and experimental demonstrations of integrated systems in the RF-to-optical spectrum .


Nano-optical Systems, In-vitro and In-vivo Biosensing

Interestingly, at THz frequencies, the dimensions of the chip is comparable to the wavelength which allows interesting electromagnetic properties, while at optical frequencies in the visible range, the wavelength is comparable to the smallest lithographic features. Sub-wavelength interaction of nanoplasmonic metals with light has made tremendous progress in recent years for its ability to confine, concentrate, guide and filter light with nano-scale noble metals, opening up many exciting applications including deep sub-diffraction imaging, significant fluorescence spectroscopy signal enhancement, sub-wavelength optical wave-guiding with extreme mode confinement, extraordinary optical transmission through sub-wavelength hole arrays, and perfect lensing. Combine this with a silicon platform where extremely complex metallic structures with near-arbitrary lithographic patterns for optical field processing and extremely high yield can be integrated with a billion integrated transistors for electronic signal processing. This intersection creates a very powerful platform for future optical systems-on-chip for miniaturized sensing and imaging applications, both in-vitro and in-vivo.

Integrated Micro-systems Reseach Lab
Office: B 216, Equad Princeton University.
Princeton, NJ 08540, USA
Kaushik Sengupta: (609) 258-5250, Fax: (609) 258-3745,
Email: kaushiks at princeton dot edu
Labs: B 217/219.


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