DN
Dr. Yashwanth N
Manipal Institute of Technology, Nagarjuna College of Engineering and Technology, Visvesvaraya Technological University - Malnad College of Engineering, Rajeev Institute of Technology
Employment
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Manipal Institute of Technology Associate Professor2024 - Present
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Manipal Institute of Technology Assistant Professor - Senior Scale2021 - 2024
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Nagarjuna College of Engineering and Technology Associate Professor2021 - 2021
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Rajeev Institute of Technology Assistant Professor2012 - 2021
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Rajeev Institute of Technology Lecturer2012 - 2012
Education
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Visvesvaraya Technological University - Malnad College of Engineering Doctor of Philosophy - PhD2015 - 2020
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Jain University - School of Engineering and Technology M.Tech.,2010 - 2012
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Visvesvaraya Technological University - Kalpataru Institute of Technology B.E.,2006 - 2010
Projects & Funding
Projects & funding information is unavailable.
Publications (53)
- Recital investigation of a fibre reinforced plastic rod in a 11 kV composite insulator using signal processing techniques Save
- A Review of Engineered Ferroelectric Materials: Synthesis Approaches, Physical Properties, and Technological Applications Save
- Highly sensitive differential bilayer (BL)-MoS2 MEMS piezoresistive pressure sensor: multi-domain design and simulation with ML-based performance analysis Save
- Double differential MEMS piezoresistive sub-µN force sensor with pentacene TFT readout circuit: multidomain design and analysis Save
- Multi-domain gate-engineered pentacene OFET for hydrogen detection: design, modeling, and simulation Save
- A modular and scalable BIST–BISR framework for reliable testing and self-repair of synchronous SRAM arrays Save
- 4H-SiC MEMS Accelerometer with Integrated SiC-FET Readout for High Temperature Harsh Environment: Design and System-Level Simulation Save
- Cylindrical FE–FE–DE heterostructure-assisted MOSFET for improved ON/OFF ratio and subthreshold swing Save
- Negative Capacitance Behavior in Cylindrical Ferroelectric-Dielectric Heterostructure Save
- Synergistic medical genetic evolutionary optimization and deep convolutional generative augmentation with SHAP-driven interpretability for precise Alzheimer's disease severity grading Save