Yogesh Thakare | Engineering | Best Researcher Award
Dr Yogesh Thakare, Ramdeobaba University, Nagpur, India
Dr. Yogesh Thakare ๐ 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 ๐พ. Currently an Assistant Professor at Shri Ramdeobaba College of Engineering & Management, Nagpur ๐จโ๐ซ, he has published in SCIE and Scopus-indexed journals ๐. His research spans FPGA architectures, AI, IoT, and biomedical systems ๐ค. A GATE qualifier (94.92%), he has led government-funded projects ๐ฐ and organized AI & IoT workshops ๐๏ธ. Passionate about innovation, he contributes to cutting-edge electronics and computing technologies โก.
Publication Profile
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 โก๐ฌ. His academic journey reflects excellence, having completed his M.Tech with Distinction (85.10%) ๐๐ and his B.E. with First-Class (72.62%) ๐โจ. 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 ๐ก๐.
Funded Research & Grants
Dr. Yogesh Thakare has demonstrated exceptional research leadership by securing โน24.6 Lakhs from CSIR for developing an automated water distribution system ๐ง๐ฌ. His innovative approach aims to enhance water management efficiency through automation, contributing to sustainable resource utilization ๐ฑ๐ก. This significant funding underscores his expertise in engineering solutions that address real-world challenges ๐๏ธโ๏ธ. With a strong commitment to technological advancement, Dr. Thakare continues to drive impactful research that promotes water conservation and smart distribution systems ๐๐. His work not only fosters scientific progress but also supports community welfare by ensuring efficient and equitable water access ๐ฐโ .
Experience
Dr. Yogesh Thakare is an experienced educator with over 14 years of teaching in top engineering institutes ๐ซ, including Shri Ramdeobaba College of Engineering and Management, Nagpur. As an Assistant Professor, he has played a key role in shaping technical education ๐. His passion for emerging technologies has led him to organize numerous workshops on Artificial Intelligence ๐ค, the Internet of Things ๐, and Machine Learning ๐, 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 ๐.
Research Focus
Dr. Yogesh Thakare’s research spans electronics, artificial intelligence, IoT, and machine learning ๐ค๐ก. His work includes DRAM memory design ๐๏ธ๐พ, FPGA-based cryptography ๐, and deepfake detection using neural networks ๐ต๏ธโโ๏ธ๐ญ. He has contributed to environmental intelligence systems ๐ฑ๐, weather prediction for agriculture ๐ฆ๏ธ๐, and smart monitoring technologies ๐ก๐ . Additionally, he has explored cortisol detection for stress monitoring ๐งชโ๏ธ and crime reporting frameworks ๐๐. His interdisciplinary research integrates hardware and AI-driven solutions, making impactful advancements in computing, security, and human well-being ๐ฌ๐ก. His innovative approach bridges technology and real-world applications, enhancing automation, safety, and intelligence. ๐
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.
Enhancing weather prediction and forecasting for agricultural applications using machine learning
Crafting visual art from text: A generative approach
Cortisol Detection Methods for Stress Monitoring: Current Insight and Future Prospect: A Review