Upendra K Singh | Deep Machine Learning | Best Researcher Award 8068

Prof. Upendra K Singh | Deep Machine Learning | Best Researcher Award

Professor at the Department of Applied Geophysics, IIT(ISM), Dhanbad, India

๐ŸŒฆ๏ธ๐Ÿ“šย  Prof. Upendra K. Singh, a distinguished geophysicist at IIT(ISM) Dhanbad, specializes in cutting-edge geophysical optimization and inversion techniques. With a Ph.D. focused on DC resistivity data using Neural Networks, his research spans seismic parameter estimation, innovative global optimization, and joint inversion methodologies. Presented at international conferences, his work leverages metaheuristic algorithms like Particle Swarm Optimization and Gibbโ€™s Sampler. Prof. Singh’s multifaceted expertise covers sensitivity analysis, uncertainty assessment, and the application of advanced techniques in geophysical exploration. A prominent figure in the field, he continues to contribute significantly to the evolving landscape of geophysics. ย ๐ŸŒ

Professional Profiles:

Scopus profile

googlescholar profile

LinkedIn profile

 

๐Ÿ‘จโ€๐ŸŽ“ย Education & Position:

๐Ÿ’ผ ย Prof. Upendra K. Singh, a Geophysics expert, currently serves as a Professor at the Department of Applied Geophysics, IIT(ISM), Dhanbad, India. His journey began as a Junior Research Fellow, progressing to Scientist ‘B’ at the National Centre for Antarctic & Ocean Research.ย ย ๐ŸŒ๐Ÿ‘ฉโ€๐Ÿ”ฌ

๐Ÿ†ย Awards & Recognitions:

Acknowledged for his outstanding contributions, Prof. Singh participated in the 24th Indian Antarctic Expedition and received the Van Weelden Award for a research paper in Geophysical Prospecting.

๐Ÿ“šย Academic & Professional Journey:

From a Senior Lecturer at Kurukshetra University to his current role as a Professor at IIT(ISM), Dhanbad, Prof. Singh has enriched his academic and professional profile. His expertise spans exploration geophysics, marine geophysics, and legal continental shelf delineation.

๐Ÿ”ย Research Work & Technical Reports:

Prof. Singh’s research involves developing and applying Neural Networks for the analysis and interpretation of DC resistivity data. He has contributed to diverse projects, such as deep resistivity sounding studies, integrated geophysical studies, and legal continental shelf projects.

Research Focus:

His research centers on geophysical exploration methods, specializing in gravity, magnetic, electrical, and electromagnetic techniques. Prof. Singh is also involved in global optimization studies.โšก๐Ÿ”ฌ

Prof. Upendra K. Singh’s research revolves around innovative approaches in geophysical optimization and inversion techniques. His work, presented at various international conferences, delves into cutting-edge methods such as Time Varying Inertia Weight-Particle Swarm Optimization, Two-Dimensional inversion, and Joint Inversion of MT and DC Resistivity. With a strong emphasis on metaheuristic algorithms like Gibbโ€™s Sampler and Particle Swarm Optimization, Prof. Singh’s expertise lies in resolving seismic and resistivity data. His contributions span diverse areas, from seismic parameter estimation to uncertainty analysis and sensitivity assessment, showcasing a multifaceted research focus in the field of geophysics.

๐ŸŒŠย Marine Geophysics:

With extensive experience in marine data acquisition, processing, and analysis, Prof. Singh has actively contributed to delineating the legal continental shelf around the East Coast, Andaman-Nicobar, and West Coast.

 

๐ŸŒย Professional Associations:

A dedicated member of professional organizations like IEEE, Prof. Singh continues to leave a lasting impact on the field of geophysics through his research, teaching, and international collaborations.

 

Peer Reviewer & Academic Engagements:

Prof. Upendra K. Singh’s, citation metrics and indices from Google Scholar are as follows:

Citations: 1909 (All), 1382 (Since 2019)
h-index: 25 (All), 20 (Since 2019)
i10-index: 67 (All), 55 (Since 2019)

 

Publications (TOP NOTES)

.

Sujatha Moorthy | Artificial Intelligence | Most Cited Article Award

Dr. Sujatha Moorthy | Artificial Intelligence | Most Cited Article Award

PHD at Sathyabama University, India

๐ŸŒฆ๏ธ๐Ÿ“šย  Dr. M. Sujatha is a seasoned professional with 22 years of experience, specializing in Wireless Sensor Networks and RF Antenna technology. Holding a Ph.D. from Sathyabama University, Chennai, her research focuses on developing and validating antenna models to enhance the efficiency of wireless sensor applications. As a Professor at KL University, Vijayawada, she has contributed significantly to academia, with numerous publications in reputable international journals. Driven by a passion for innovation, she is actively involved in cutting-edge projects, showcasing her expertise in machine learning, robotics, and high-resolution satellite remote sensing. A dedicated scholar, she continues to shape the future of technology. ๐ŸŒ

Professional Profiles:

Orcid profile

googlescholar profile

Researchgate profile

LinkedIn

 

๐ŸŽ“Education:

๐Ÿ’ผ Ph.D., Sathyabama University, Chennai (July 2017) Faculty of Electronics Engineering, Highly Recommended M.E., Sathyabama University, Chennai (May 2006) Applied Electronics, I Class with Distinction B.E., Adhiparasakthi Engg. College, Madras University (May 1999) Electronics and Communication Engineering, I Classย  ๐ŸŒ๐Ÿ‘ฉโ€๐Ÿ”ฌ

Professional Experience:

Total 22 years of experience, with 16 years post M.E. Professor, KL University, Vijayawada, Andra Pradesh (December 2020-Till date) Professor, Saveetha School of Engineering, SIMATS (April 2019-December 2020) Professor, KL University, Vijayawada, Andra Pradesh (January 2017-March 2019) Associate Professor, Prathyusha Institute of Technology and Management (December 2003 โ€“ June 2016) Lecturer, Sri Ram Engineering College (June 2000-December 2003)

Professional Qualification:

FPGA Based Industrial Robotic Arm Controller, Design Engineering (Toronto), ISSN: 0011-9342 | Year 2022, Issue: 1, Pages: 2209 โ€“ 2215. Maze Solver Using Webots, Design Engineering (Toronto), ISSN: 0011-9342 Year 2022, Issue: 1, Pages: 2563 โ€“ 2568.

Research Focus:

Dr. M. Sujatha’s research spans varmetamaterialsious domains, primarily focusing on Wireless Sensor Networks (WSN), RF Antennas, and their applications in cutting-edge technologies. Her work includes the development of high-performance grouping schemes for WSN, innovative antenna designs inspired by metamaterials, and hardware design for biomedical video compression. Additionally, she explores AI-based traffic flow prediction models for connected and autonomous electric vehicles. Dr. Sujatha’s research extends to biometric voting systems, electronic voting machines, and the detection of fake news, showcasing a diverse expertise in wireless communication, IoT applications, and information security. Her multidisciplinary contributions demonstrate a holistic approach to technological advancements.โšก๐Ÿ”ฌ

Peer Reviewer & Academic Engagements:

Dr. M. Sujatha, citation metrics and indices from Google Scholar are as follows:

Citations: 115 (All), 93 (Since 2018)
h-index: 6 (All), 6 (Since 2018)
i10-index: 4 (All), 3 (Since 2018)

Publications (TOP NOTES)

 

Metamaterial Inspired Circular Antenna with DGS for Tetra Band Application, cited by 8, publication date: 2020/3/25

 

AI Based Traffic Flow Prediction Model for Connected and Autonomous Electric Vehicles, cited by 7, publication date: 2021/11.

 

AR-ESIHE and ARS-ESIHE-based image enhancement methods on 9oba pure and nano dispersed liquid crystalline compound, cited by 5, publication date: 2020/8

 

Design of Reconfigurable Integrated patch antenna in ISM band for IoT applications, cited by 5, publication date: 2020/7/23

 

Unconstrained Global Optimization Base Partial Transmit Sequence for OFDM PAPR Reduction, cited by 4, publication date: 2020/4/15.

 

Image enhancement using wavelet based image fusion and power law transform, cited by 2, publication date: 2020/5/15

.

.

 

.