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Dr. Ravi V

Professor

Email: ravi.v@vit.ac.in

PhD: Vellore Institute of Technology, Chennai

Research Area: VLSI Design, VLSI Testing & Testability, Deep Learning In VLSI, FPGA based system, Semiconductor Memory Design, Biomedical Signal/Image processing, Machine Learning applications using LabVIEW, and IoT Systems

Employee ID 50583
Salutation (Prof./ Dr.)    Dr
Name Ravi V
Designation Professor Grade 1 & Assistant Director – VIT Chennai Startup and Research Foundation
School/Centre SENSE
Intercom 1494
Educational details (Please mention all the degrees with latest first)
Degree Passed out year Specialization Institute/University/ College
Ph.D 2019 VLSI Design Vellore Institute of Technology
M.E 2004 Medical Electronics College of Engineering, Guindy – Anna University
B.E 1999 ECE University of Madras
Diploma
Post-Doctoral Experience if any
Research Details
Areas of Specialization Neuromorphic Computing, Resistive RAM, Deep Learning in VLSI, Virtual Instrumentation, VLSI Testing & Testability, Deep Learning In VLSI, Semiconductor Memory Design, Biomedical Signal/Image processing using LabVIEW, and IoT Systems
ORCID ID https://orcid.org/0000-0002-5097-6189
Scopus ID https://www.scopus.com/authid/detail.uri?authorId=56825299200
H-index (scopus) 10
Google Scholar ID 10
i10 index 10
On-going Consultancy Project Details
On-going Consultancy Project Title
R&D for Plugin development to detect Energy Smells in Kotlin code Samsung, Bangalore
Completed Consultancy Project Details               
PES Regulations for Electrical Vehicles Valeo, Chennai
Detecting Food Item and Quantity Samsung, Bangalore
 
Patent Published Details
Patent Published Title
De-Attachable 3D Printable Adapter 416159-001
System And Method for Inspecting a Metal Object 202441050014
System For Controlling Corona Virus in A Communal Space and Method Thereof 202341073410
 
Book / Book Chapter Published Details
Title Publisher Year
Intelligent, Automated, and Web Application-Based Cradle Monitoring System Springer 2021
Variation-Tolerant In-Memory Digital Computations Using SRAM Springer 2020
Defect Detection and Defect-Tolerant Design of a Multi-port SRAM Springer 2020
Non-destructive Read Circuit for Memristor-Based Memories. In Nano electronic Materials and Devices Springer 2018
A built-in self-repair architecture for random access memories Springer 2018
Weak Cell Detection Techniques for Memristor-Based Memories Springer 2018

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