sandeep rawat | Technologies | Best Scholar Award

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Mr. sandeep rawat | Technologies | Best Scholar Award 

JRF, UPES Dehradun, India

🌟 Sandeep Rawat is an accomplished academic and researcher specializing in electrical engineering, energy storage systems, and renewable energy technologies. Currently pursuing a Ph.D. at UPES, he has a solid foundation in Power Systems and Electrical and Electronics Engineering. With extensive teaching experience at Uttaranchal University and active participation in various professional roles, Sandeep has made significant contributions to research in lithium-ion batteries and solar PV systems. 📚💡

Publication Profile

Google Scholar

 

Strengths for the Award

  1. Relevant Research Experience:
    • Sandeep Rawat has focused on cutting-edge areas in renewable energy, including lithium-ion batteries and solar PV systems. His research on energy storage systems and the effects of shading on solar panels is highly relevant and timely.
  2. Academic Background:
    • His educational qualifications include a PhD in progress, an M.Tech in Power Systems, and a B.Tech in Electrical and Electronics Engineering, providing a strong technical foundation.
  3. Research Publications:
    • He has authored and contributed to several publications in reputable journals and conferences, such as Springer and IEEE, showcasing his active involvement in the research community. The variety and relevance of his publications reflect a deep engagement with current issues in his field.
  4. Teaching and Mentoring Experience:
    • Sandeep has significant teaching experience as a Senior Lecturer and has supervised multiple academic projects. His role as a coordinator and NAAC criteria member highlights his leadership and organizational skills.
  5. Professional Development:
    • His participation in various seminars, webinars, and faculty development programs demonstrates a commitment to ongoing professional growth and staying updated with advancements in his field.

Areas for Improvement

  1. Research Impact and Recognition:
    • While he has published several papers, increasing the impact and visibility of his research could enhance his profile. Greater focus on high-impact journals or more collaborative projects with renowned researchers might be beneficial.
  2. Awards and Honors:
    • The CV does not mention any significant awards or recognitions received. Gaining such accolades or achieving notable milestones in research could strengthen his application.
  3. Publication Diversity:
    • Expanding the diversity of publication venues, including higher-impact journals and international collaborations, could further enhance his academic profile.

 

Education

🎓 Sandeep Rawat is currently pursuing his Ph.D. at the University of Petroleum and Energy Studies (UPES), focusing on Lithium-ion battery safety characterization. He holds an M.Tech in Power Systems from Kurukshetra University (2020) and a B.Tech in Electrical and Electronics Engineering from Uttarakhand Technical University (2013). His earlier education includes CBSE certifications in PCMB and Science with notable academic performance. 📊🔋

Experience

👨‍🏫 Sandeep Rawat is a Senior Lecturer in the Electrical Department at University Polytechnic, Uttaranchal University, where he has been shaping young minds since 2014. He is also the Department Coordinator, a Member of the Board of Studies, a NAAC Coordinator for Criteria 1, and a Member of the University Alumni Association. His expertise spans over a decade in academia, project supervision, and research. 🏆📈

Research Focus

🔬 Sandeep’s research interests encompass Lithium-ion batteries, the effects of electrical abuses on battery performance, and innovative configurations for optimizing solar PV panels under partial shading. His studies aim to enhance the efficiency and safety of energy storage systems and solar energy applications. ☀️🔋

Awards and Honors

🏅 Sandeep Rawat has supervised projects that have won accolades, such as the First Prize in Innovative Technology at SIT College, Dehradun. His active involvement in various academic and research committees demonstrates his commitment to advancing education and technology. 🏆🎓

Publications Top Notes

📑 Sandeep has published several notable research papers, including studies on solar PV configurations and advancements in lithium-ion batteries. His work has been featured in reputable conferences and journals, contributing valuable insights to the fields of renewable energy and battery safety. 🌍🔋

“Experimental study of solar PV array configuration under Partial Shading Effects,” published in the Springer Conference (HSFEA) at UPES Dehradun.

“Shade dispersion using TCT configuration in Solar PV array under non-uniform irradiation,” published in IEEE Conference (ICACSE) at KNIT Sultanpur UP.

“Development of IoT based data acquisition system for real-time monitoring of solar PV system,” published as a book chapter in Taylor and Francis (CRC), in the book Applied Soft Computing and Embedded System Applications in Solar Energy.

“PV module Reconfigurable approach using SM for Power loss reduction under Detrimental Shadowing Conditions.”

“Advancements and Current Developments in Integrated System Architectures of Lithium-Ion Batteries for Electric Mobility,” Published in WEVJ, 2022.

“Advanced Monitoring and Real-Time State of Temperature Prediction in Lithium-Ion Cells under Abusive Discharge Conditions using Data-Driven Modeling,” accepted in the Future Transportation Journal.

Conclusion

Sandeep Rawat is a strong candidate for the Research for Best Scholar Award due to his relevant research focus, substantial academic experience, and active involvement in teaching and professional development. His research in renewable energy, especially in lithium-ion batteries and solar PV systems, is both pertinent and impactful. To further bolster his candidacy, increasing the visibility and impact of his research, seeking prestigious awards, and diversifying publication venues could be advantageous. Overall, his dedication and contributions to the field make him a noteworthy contender for the award.

 

Jinwei Bu | Engineering | Best Researcher Award

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Dr. Jinwei Bu | Engineering | Best Researcher Award

Master Supervisor, Kunming University of Science and Technology, China

👨‍🏫  Dr. Jinwei Bu, a dedicated researcher and member of IEEE, is currently a Master Supervisor at the Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming, China. With a robust academic and research background, Dr. Bu has significantly contributed to the fields of geodesy and surveying engineering through his extensive publications and active involvement in the scientific community.

Profile

Google Scholar

 

Strengths for the Award

  1. Strong Academic Background: Jinwei Bu has a solid educational foundation in surveying and mapping engineering, geodesy, and surveying engineering, which are crucial for research impacting communities through environmental and spatial informatics.
  2. Extensive Research Experience: With over 50 refereed journal articles authored or coauthored, Dr. Bu has made significant contributions to his field. His publications indicate a robust research portfolio.
  3. International Collaboration: His experience as a Visiting Ph.D. Student at the Universitat Politècnica de Catalunya (UPC) in Spain highlights his international research exposure and collaboration.
  4. Leadership in Academia: Currently serving as a Master Supervisor at Kunming University of Science and Technology, Dr. Bu is in a position to mentor the next generation of researchers, amplifying his impact on the community.
  5. Reviewer for Prestigious Journals: Serving as a reviewer for over 10 international journals underscores his expertise and recognition in the academic community.
  6. Research Interests with Community Impact: His focus on Global Navigation Satellite Systems (GNSS) reflectometry, atmospheric remote sensing, precision positioning, and machine/deep learning has direct applications in improving navigation, environmental monitoring, and disaster management, all of which have significant community impacts.

Areas for Improvement

  1. Direct Community Engagement: While his research has potential community impact, there could be more direct evidence of engagement with community projects or initiatives that translate his research into tangible community benefits.
  2. Interdisciplinary Collaborations: Increasing collaborations with experts from other fields such as public health, urban planning, and environmental science could broaden the application of his research and enhance its community impact.
  3. Public Outreach and Education: Engaging in more public outreach, workshops, and educational programs to disseminate his research findings to a broader audience, including policymakers and community leaders, could increase the practical application and visibility of his work.

🎓 Education:

Dr. Jinwei Bu received his B.S. degree in Surveying and Mapping Engineering (2016) and his M.S. degree in Geodesy and Surveying Engineering (2018) from Kunming University of Science and Technology, Kunming, China. He earned his Ph.D. degree in Geodesy and Surveying Engineering from the School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China, in 2022.

💼 Experience:

Dr. Bu has held various academic positions, including a Visiting Ph.D. Student role at the Department of Signal Theory and Communications, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, from November 2021 to November 2022. Currently, he is serving as a Master Supervisor with the Faculty of Land Resource Engineering at Kunming University of Science and Technology. He has authored or coauthored over 50 refereed journal articles and serves as a reviewer for more than 10 international journals.

🔬 Research Interests:

Dr. Jinwei Bu’s research interests include Global Navigation Satellite Systems (GNSS) reflectometry, GNSS atmospheric remote sensing, GNSS precision positioning, and the application of machine/deep learning techniques in these areas. He is particularly focused on developing and testing models for sea surface wind speed estimation with GNSS-R delay Doppler maps and delay waveforms.

🏆 Awards:

Dr. Bu’s excellence in research and contributions to the field have earned him recognition and accolades within the scientific community, underscoring his commitment and impact in geodesy and surveying engineering.

Publications

  1. An indoor Wi-Fi localization algorithm using ranging model constructed with transformed RSSI and BP neural network – IEEE Transactions on Communications, 2022. Cited by: 29
    • Prompt: An innovative approach to indoor Wi-Fi localization using RSSI and neural networks.
  2. Developing and testing models for sea surface wind speed estimation with GNSS-R delay Doppler maps and delay waveforms – Remote Sensing, 2020. Cited by: 25
    • Prompt: Breakthrough in sea surface wind speed estimation using GNSS-R technology.
  3. Multi-classification of UWB signal propagation channels based on one-dimensional wavelet packet analysis and CNN – IEEE Transactions on Vehicular Technology, 2022. Cited by: 23
    • Prompt: Cutting-edge multi-classification of UWB signals utilizing wavelet analysis and CNN.
  4. Performance assessment of positioning based on multi-frequency multi-GNSS observations: signal quality, PPP, and baseline solution – IEEE Access, 2020. Cited by: 20
    • Prompt: Comprehensive evaluation of multi-GNSS positioning performance and solutions.
  5. Sea surface rainfall detection and intensity retrieval based on GNSS-reflectometry data from the CYGNSS mission – Publication details pending.
    • Prompt: Novel methodology for sea surface rainfall detection and intensity estimation using GNSS-reflectometry.

Hui Peng | Engineering | Best Researcher Award

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Dr. Hui Peng | Engineering | Best Researcher Award

Professor, Central South University, China

👨‍🏫 Hui Peng is a distinguished Professor in the School of Automation at Central South University, Changsha, China. With a prolific career spanning over two decades, he has authored more than 70 papers in international journals and co-invented a patent in Japan. His expertise lies in various aspects of control engineering and statistical science, making significant contributions to industrial process control projects globally.

Profile

ORCID

 

Education

🎓 Hui Peng earned his B.Eng. and M.Eng. degrees in Control Engineering from Central South University, Changsha, China, in 1983 and 1986, respectively. He obtained his Ph.D. in Statistical Science from the Graduate University for Advanced Studies, Hayama, Japan, in 2003.

Experience

💼 Hui Peng has been a Professor at the School of Automation, Central South University, since 1998. He served as a Visiting Professor at the Institute of Statistical Mathematics, Tokyo, Japan, from 2000 to 2004 and again from 2009 to 2010. Since 2010, he has also been a Foreign Cooperative Professor at the Graduate University for Advanced Studies, Japan. His work includes successfully completing over ten industrial process control projects involving diverse systems like marine ships, thermal power plants, and quadrotor helicopters.

Research Interests

🔬 Hui Peng’s research interests are extensive and include nonlinear system modeling, statistical modeling, system identification, nonlinear optimization, signal processing, predictive control, robust control, process control, financial process modeling, and portfolio optimization.

Awards

🏆 Hui Peng has not only authored numerous papers but also co-invented a patent in Japan, reflecting his significant contributions to control engineering and statistical science.

Publications

Market price, excess demand and liquidity dynamics modeling and application to investment decision optimization

Research on Time Varying Variance Financial Time Series Modeling and Portfolio Optimization Methods

State-dependent ARX model-based nonlinear system modeling and robust predictive control

 

HaiTian Chen | Computer Science | Best Researcher Award

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Ms. HaiTian Chen | Computer Science | Best Researcher Award

College of Science, North China University of Science and Technology, China

Chen HaiTian is a dedicated researcher in the field of Cyberspace Security from China. Born in December 1998, Chen has made significant strides in federated learning, privacy preservation, and cybersecurity. His contributions span multiple peer-reviewed journals and patents, showcasing his commitment to advancing technology and safeguarding digital spaces.

Profile

ORCID

 

Education

Chen HaiTian holds a major in Cyberspace Security, demonstrating his expertise and focus in this critical area of study. His academic background has equipped him with the skills and knowledge necessary to tackle complex cybersecurity challenges and contribute to innovative solutions in the field. 🎓

Research Interests

Chen HaiTian’s research interests focus on federated learning, privacy preservation, and cybersecurity. He is particularly interested in developing robust aggregation techniques to defend against poisoning attacks in federated learning and exploring personalized fair split learning for resource-constrained Internet of Things (IoT). 🔍

Awards

Chen HaiTian has received recognition for his contributions to software development, including the Huali Academy Backstage Management System V1.0 and the DC Early Warning System V1.0. His work has been registered with computer software registration numbers, showcasing his achievements in developing innovative solutions for network management and security. 🏆

Publications

Chen, H.; Chen, X.; Peng, L. (2023). FLRAM: Robust Aggregation Technique for Defense Against Byzantine Poisoning Attacks in Federated Learning. Electronics. Cited by Electronics.

Chen, H.; Chen, X.; Peng, L. (2024). Personalized Fair Split Learning for Resource-Constrained Internet of Things. Sensors, 24, 88. Cited by Sensors.

Chen, H., Chen, X., Ma R., et al. (2024). A federated learning privacy preserving approach for remote sensing data. Computer Applications. Cited by Computer Applications.

Chen, H., Chen, X. (2023). A Robust Aggregation Technique for Poisoning Attack Defense in Federated Learning. Cited by Journal.

Xu C., Zhang S., Chen H., et al. (2024). A federated learning approach based on adaptive differential privacy and customer selection optimization. Computer Applications. Cited by Computer Applications.

Peng L., Zhang S., Chen H., et al. (2023). Clustered federated learning based on improved CFSFDP algorithm. Journal of North China University of Science and Technology (Natural Science Edition). Cited by NCUST.

Qiang Li | Computer Science | Best Researcher Award

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Mr. Qiang Li | Computer Science | Best Researcher Award

Lecturer, Qingdao University, China

Dr. Li Qiang is an experienced lecturer in computer science with a PhD in Engineering. He specializes in high-performance computing and has a strong background in both teaching and research. Committed to fostering academic excellence and technological innovation, Dr. Li has been a dedicated educator and researcher at Qingdao University since 2015.

Profile

ORCID

 

Education 🎓

PhD in Engineering: University of the Chinese Academy of Sciences, Computer Network Information Center (2010-2014), Advisor: Lu Zhonghua. Master’s in Information Science and Engineering: Shandong University of Science and Technology (2007-2010), Advisor: Zhao Maoxian. Bachelor’s in Education: Qingdao University (2003-2007).

Experience 👨‍🏫

Lecturer at Qingdao University, School of Computer Science and Technology (January 2015-Present). Teaching undergraduate and graduate courses in computer science. Supervising student research projects and theses. Conducting research in high-performance computing. Published 12 research papers in journals and conferences. Granted 2 patents.

Research Interests 🔬

Dr. Li Qiang’s research interests lie in high-performance computing, particularly in the optimization and parallel implementation of numerical simulations and the development of new computational frameworks. His work focuses on enhancing computational efficiency and scalability in large-scale scientific computations.

Awards 🏆

Dr. Li Qiang has been recognized for his contributions to the field of high-performance computing through multiple publications and patents. His innovative work has led to advancements in computational methods and has garnered attention in the academic community.

Publications 📄

Optimization Research of Heterogeneous 2D-Parallel Lattice Boltzmann Method Based on Deep Computing Unit. Appl. Sci. 2024, 14, 6078.

Heterogeneous Parallel Implementation of Large-Scale Numerical Simulation of Saint-Venant Equations. Appl. Sci. 2022, 12, 5671. Cited by 6

The Study of Parallelization of SWAT Hydrology Cycle. The 32nd ACM International Conference on Supercomputing, Beijing, 2018. [Cited by 3]

A New Parallel Framework of Distributed SWAT Calibration. Journal of Arid Land, 2015, 7(1): 122-131. [Cited by 7]

Parallel Simulation of High-Dimensional American Option Pricing Based on CPU VS MIC. Concurrency and Computation: Practice and Experience, 2014, 27(5): 1110-1121. [Cited by 5]