Summaries by Inventor Chakrabartty, Shantanu

Energy efficient, scalable neuromorphic computing with Growth Transform Neural Network
Chakrabartty, Shantanu ; Gangopadhyay, Ahana
T-019112

— Technology Description Engineers in Prof. Shantanu Chakrabartty’s laboratory have developed Growth Transform Neural Network (GTNN), a flexible system for designing scalable neuromorphic processors for use in deep learning systems and support vector machines. GTNN frames the neuromorphic syst…

Low-Power, Fast Sensors for Infrastructure‐to‐Vehicle Communications in Autonomous Driving
Aono, Kenji ; Chakrabartty, Shantanu ; Kondapalli, Sri Harsha ; Pochettino, Owen
T-019014

— Engineers in Prof. Shantanu Chakrabarty’s laboratory have developed an RFID embedded sensor system for infrastructure-to-vehicle (I2V) communications that uses near-zero standby energy and offers the robust performance of actively powered communications. This technology is designed to provide …

Self-capacitance Power Transfer for Efficient Wireless Charging of Small Wearables
Alazzawi, Yarub ; Aono, Kenji ; Chakrabartty, Shantanu ; Scheller, Erica
T-018759

— Technology Description Engineers in Prof. Shantanu Chakrabartty’s laboratory have developed a convenient, wireless power transfer system that exploits the body’s self-capacitance to charge small, low power, wearable and minimally-invasive devices. Wearable devices traditionally rely o…

Self-powered, solid-state devices for remote sensing, timing and security of internet-of-things and other passive assets
Chakrabartty, Shantanu ; Zhou, Liang
T-015908

— Technology Description Engineers in Prof. Shantanu Chakrabartty’s laboratory have developed a self-powered, CMOS-based, nano-scale “smart sensor” and timer system that uses quantum-tunneling for reliable, long-lasting memory or authentication. This technology is a floating gate …

Insect-Inspired Electronic-Nose Technology for Reliable, Robust and Real-World Chemical Sensing
Chakrabartty, Shantanu ; Raman, Baranidharan ; Singamaneni, Srikanth
T-020888

— Published Date: 2/14/2025 Value Proposition: Portable and deployable platform that uses an AI-enabled, nanoparticle-based e-nose to sense explosive volatile organic compounds. Technology Description Researchers at Washington University in St. Louis have developed a low-power electronic nose that…

Bio-robotic “artificial nose” system for detecting explosives and other chemicals
Altan, Ege ; Chakrabartty, Shantanu ; Chandak, Rishabh ; Mehta, Darshit ; Raman, Baranidharan ; Saha, Debajit ; Singamaneni, Srikanth ; Tadepalli, Sirimuvva ; Traner, Michael
T-019136

— Technology Description Prof. Barani Raman and colleagues have developed a robust, insect-based, non-invasive sensing system to detect explosives or other chemicals. This “artificial nose” technology includes methods to decode neural signals from the insect’s olfactory system and …