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Space Situational Awareness

Our research in this area exploits informative measurement system in both quantum and classical domains to enhance imaging capabilities, showcasing a smooth integration of theory and practical applications in astronomy and beyond. We can broadly categorize our work in the following categories. Click...

Thermal Night Vision

Machine perception uses advanced sensors to collect information about the surrounding scene for situational awareness. State-of-the-art machine perception using active sonar, radar and LiDAR to enhance camera vision faces difficulties when the number of intelligent agents scales up. Exploiting...

Quantum Detectors & Sensors

Our work in the field of quantum science & engineering spans from theoretical investigations to experimental demonstrations of quantum effects in various light-matter interactions. Following are some of our key contributions to this field. Click on each tile to know more!

Machine Perception

Machine perception uses advanced sensors to collect information about the surrounding scene for situational awareness. State-of-the-art machine perception using active sonar, radar and LiDAR to enhance camera vision 9 faces difficulties when the number of intelligent agents scales up. Exploiting...

Latest Paper in Physical Review B

We are delighted to share our recent work on "First-principles study of large gyrotropy in MnBi for infrared thermal photonics", published in Physical Review B. It talks about how nonreciprocal gyrotropic materials have attracted significant interest recently in material physics, nanophotonics, and...

Invited talk in MRS Boston 2023

Dr. Zubin Jacob Presents "Heat-Assisted Detection and Ranging (HADAR)" in MRS Boston 2023. He will talk about how machine perception uses advanced sensors to collect information about the surrounding scene for situational awareness. State-of-the-art machine perception using active sonar, radar, and...

Latest Paper Published in IEEE Xplore

This article proposes circular hidden quantum Markov models (c-HQMMs), which can be applied for modeling temporal data. We show that c-HQMMs are equivalent to a tensor network (more precisely, circular local purified state) model. This equivalence enables us to provide an efficient learning model...