Yogesh Thakare | Engineering | Best Researcher Award

Yogesh Thakare | Engineering | Best Researcher Award

Dr Yogesh Thakare, Ramdeobaba University, Nagpur, India

Dr. Yogesh Thakare πŸŽ“ is an accomplished researcher and educator in Electronics and Communication Engineering. He earned his Ph.D. (2020) from SGB Amravati University, specializing in DRAM design using submicron technology πŸ’Ύ. Currently an Assistant Professor at Shri Ramdeobaba College of Engineering & Management, Nagpur πŸ‘¨β€πŸ«, he has published in SCIE and Scopus-indexed journals πŸ“‘. His research spans FPGA architectures, AI, IoT, and biomedical systems πŸ€–. A GATE qualifier (94.92%), he has led government-funded projects πŸ’° and organized AI & IoT workshops πŸ—οΈ. Passionate about innovation, he contributes to cutting-edge electronics and computing technologies ⚑.

Publication Profile

Google Scholar

Academic Excellence

Dr. Yogesh Thakare earned his Ph.D. in Electronics Engineering from SGB Amravati University in 2020, focusing on Dynamic Random Access Memory (DRAM) design using submicron technology βš‘πŸ”¬. His academic journey reflects excellence, having completed his M.Tech with Distinction (85.10%) πŸŽ“πŸ† and his B.E. with First-Class (72.62%) πŸ“šβœ¨. With a strong foundation in electronics and a passion for advanced semiconductor technologies, Dr. Thakare has made significant contributions to memory design and innovation. His expertise in microelectronics and circuit design continues to drive advancements in the field, shaping the future of high-performance computing and digital storage solutions πŸ’‘πŸ”.

Funded Research & Grants

Dr. Yogesh Thakare has demonstrated exceptional research leadership by securing β‚Ή24.6 Lakhs from CSIR for developing an automated water distribution system πŸ’§πŸ”¬. His innovative approach aims to enhance water management efficiency through automation, contributing to sustainable resource utilization πŸŒ±πŸ’‘. This significant funding underscores his expertise in engineering solutions that address real-world challenges πŸ—οΈβš™οΈ. With a strong commitment to technological advancement, Dr. Thakare continues to drive impactful research that promotes water conservation and smart distribution systems πŸŒπŸ“Š. His work not only fosters scientific progress but also supports community welfare by ensuring efficient and equitable water access πŸš°βœ….

Experience

Dr. Yogesh Thakare is an experienced educator with over 14 years of teaching in top engineering institutes 🏫, including Shri Ramdeobaba College of Engineering and Management, Nagpur. As an Assistant Professor, he has played a key role in shaping technical education πŸ“š. His passion for emerging technologies has led him to organize numerous workshops on Artificial Intelligence πŸ€–, the Internet of Things 🌐, and Machine Learning πŸ“Š, empowering students with cutting-edge knowledge. Through his dedication to academic excellence and innovation, Dr. Thakare continues to inspire the next generation of engineers and researchers πŸš€.

Research Focus

Dr. Yogesh Thakare’s research spans electronics, artificial intelligence, IoT, and machine learning πŸ€–πŸ“‘. His work includes DRAM memory design πŸ—οΈπŸ’Ύ, FPGA-based cryptography πŸ”, and deepfake detection using neural networks πŸ•΅οΈβ€β™‚οΈπŸŽ­. He has contributed to environmental intelligence systems πŸŒ±πŸ“Š, weather prediction for agriculture 🌦️🚜, and smart monitoring technologies πŸ“‘πŸ . Additionally, he has explored cortisol detection for stress monitoring πŸ§ͺβš•οΈ and crime reporting frameworks πŸš”πŸ“œ. His interdisciplinary research integrates hardware and AI-driven solutions, making impactful advancements in computing, security, and human well-being πŸ”¬πŸ’‘. His innovative approach bridges technology and real-world applications, enhancing automation, safety, and intelligence. πŸš€

Publication Top Notes

Intelligent Life Saver System for People Living in Earthquake Zone.

An Effect of Process Variation on 3T-1D DRAM

Analysis of power dissipation in design of capacitorless embedded DRAM

IoT-Enabled Environmental Intelligence: A Smart Monitoring System

Detection of Deepfake Video Using Residual Neural Network and Long Short-Term Memory.

A Read-out Scheme of 1T-1D DRAM Design with Transistor Assisted Decoupled Sensing Amplifier in 7 nm Technology

Enhancing weather prediction and forecasting for agricultural applications using machine learning

FPGA Implementation of Compact Architecture for Lightweight Hash Algorithm for Resource Constrained Devices

Crafting visual art from text: A generative approach

Cortisol Detection Methods for Stress Monitoring: Current Insight and Future Prospect: A Review

An Ensemble Learning with Deep Feature Extraction Approach for Recognition of Traffic Signs in Advanced Driving Assistance Systems

Development and design approach of an sEMG-based Eye movement control system for paralyzed individuals