sandeep rawat | Technologies | Best Scholar Award

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.

 

HaiTian Chen | Computer Science | Best Researcher Award

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

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]