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)

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Manuel Morales-Serazzi | Data strategy | Best Researcher Award

Dr. Manuel Morales-Serazzi | Data strategy | Best Researcher Award

PHD at University of Salamanca, Chile

๐ŸŒฆ๏ธ๐Ÿ“šย  Dr. Manuel Morales-Serazzi, an esteemed academic and researcher at Austral University of Chile, Puerto Montt, is a seasoned professional in business economics. Holding a Doctorate and Masters in the field from the University of Salamanca, his expertise extends to management control and entrepreneurship. With a rich academic background, he contributes significantly to the Institute on Management and Industry. Recognized for achieving Cum Laude distinction at the University of Salamanca, Morales-Serazzi’s commitment is evident through his membership as an Adjunct Professor and impactful research on data analytics strategy. His publications delve into information quality and marketing analytics, showcasing his dedication to advancing knowledge..๐ŸŒ

Professional Profiles:

Scopus profile

orcid profile

Researchgate profile

LinkedInย 

 

๐ŸŽ“Education and Qualifications:

๐Ÿ’ผUniversity of Salamanca, Salamanca, Castilla y Leรณn, IS Doctor in Business Economics (IME) Duration: October 1, 2016, to Date University of Salamanca, Salamanca, Castilla y Leรณn, IS Master Research in Eco Business Economy (IME) Duration: October 1, 2016, to July 30, 2017 University of Chile, Santiago de Chile, Metropolitana, CL Master in Management Control (Faculty of Economics and Business) Duration: March 10, 2013, to December 14, 2015ย ย ๐ŸŒ๐Ÿ‘ฉโ€๐Ÿ”ฌ

Employment:

Austral University of Chile, Puerto Montt, Los Lagos, CL Position: Academic – Researcher Universidad Austral de Chile

Research Focus:

Manuel Morales-Serazzi’s research focus centers on the intersection of Business Data Analytics (BDA) and information quality, employing a multifaceted approach. As evidenced by publications like “A New Perspective of BDA and Information Quality” and “Achieving Useful Data Analytics for Marketing,” co-authored with ร“. Gonzรกlez-Benito and M. Martos-Partal, his work delves into the complexities of information utilization and quality within marketing analytics. Additionally, his expertise extends to knowledge integration and organizational performance, particularly in the context of data analytics within family businesses. Morales-Serazzi’s research illuminates crucial insights for practitioners and scholars navigating the evolving landscape of data-driven decision-making.โšก๐Ÿ”ฌ

Peer Reviewer & Academic Engagements:

Citations by 6 documents

3 Documents

2 h-index

Publications (TOP NOTES)

 

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