Mr. Md Tanvir rahman Tarafder | Information Technology | Best Researcher Award

Posted on by sciencefather

Mr. Md Tanvir rahman Tarafder | Information Technology  | Best Researcher Award

Data analysis, Westcliff university, United States

Tanvir Rahman Tarafder is a passionate and results-driven cloud computing professional with a strong foundation in software development and IT solutions. With expertise in AWS services, including EC2, S3, Lambda, and RDS, he thrives in building scalable and efficient cloud-based architectures. His journey from a Computer Science graduate to a cloud enthusiast reflects his commitment to innovation and problem-solving. Beyond his technical expertise, Tanvir is a team player and excellent communicator, always eager to explore new technological advancements and contribute to impactful projects.

Publication Profile

Google Scholar

Academic Background 🎓

Tanvir is currently pursuing a Master’s in Information Technology (Cloud Computing) at Westcliff University, USA, maintaining an impressive CGPA of 3.96 (expected 2025). He earned his Bachelor of Science in Computer Science & Engineering from American International University-Bangladesh (AIUB) with a CGPA of 3.23 (2018-2021). His strong academic performance is complemented by a solid foundation in programming, databases, and cloud infrastructure. His early education includes a Higher Secondary Certificate from Dhaka City College and a Secondary School Certificate from Bogura Cantonment Public School & College, where he excelled with top grades.

Professional Experience 💼

Tanvir has gained diverse industry experience in various technical and consultancy roles. As an IT Officer at SM Fintech Technologies Ltd., he managed website maintenance, configured email servers, reviewed vendor contracts, and coordinated IT purchases to optimize business operations. His passion for academia led him to work as a Teaching Assistant at AIUB, where he supported students in Computer Graphics courses. Additionally, his role as an International Student Consultant at Revolution Student Consultancy allowed him to guide over 50 students in securing admissions to American universities. His expertise spans cloud computing, software development, and IT consultancy, making him a versatile professional.

Awards and Honors 🏆

Tanvir has demonstrated his technical excellence through multiple industry-recognized certifications. He holds the AWS Certified Solutions Architect Associate (Valid till 2030) and AWS Certified Cloud Practitioner (Valid till 2029), showcasing his deep expertise in cloud computing. Additionally, he has earned certifications in Python programming and front-end web development from prestigious platforms. These achievements highlight his continuous learning mindset and dedication to staying ahead in the tech industry.

Research Focus 🔬

Tanvir’s research focuses on leveraging Artificial Intelligence (AI) and Machine Learning (ML) in cloud computing, predictive analytics, and smart systems. His work includes forecasting Electric Vehicle adoption, AI-driven smart grid optimization, and transformative AI applications in healthcare. His passion for exploring AI’s role in solving real-world problems reflects his commitment to advancing technology for societal benefits. He has contributed to multiple peer-reviewed publications, addressing challenges in water quality analysis, synthetic e-commerce data insights, and medical imaging advancements.

Conclusion 🌟

With a strong technical foundation, hands-on cloud computing experience, and a keen research interest in AI-driven solutions, Tanvir Rahman Tarafder stands out as a forward-thinking innovator in the field of cloud technology and AI. His ability to bridge academic knowledge with practical applications makes him a valuable asset in any technology-driven organization. His continuous pursuit of excellence and eagerness to contribute to groundbreaking research and development mark him as a promising professional in the ever-evolving tech landscape.

Top Publications 📚

Forecasting Electric Vehicle Adoption in the USA Using Machine Learning Models
Published in: Journal of Computer Science and Technology Studies (2024)
Cited by: 12 articles

Discoverable Hidden Patterns in Water Quality through AI, LLMs, and Transparent Remote SensingPublished in: 2024 17th International Conference on Security of Information and Networks (2024)
Cited by: 9 articles

Integrating Transformative AI for Next-Level Predictive Analytics in Healthcare
Published in: IEEE Conference on Engineering Informatics (ICEI) (2024)
Cited by: 9 articles

Optimizing Load Forecasting in Smart Grids with AI-Driven Solutions
Published in: IEEE International Conference on Data and Software Engineering (ICoDSE) (2024)
Cited by: 7 articles

A Novel Diagnostic Framework with an Optimized Ensemble of Vision Transformers and Convolutional Neural Networks for Enhanced Alzheimer’s Disease Detection in Medical Imaging
Published in: Diagnostics Journal (2025)
Cited by: (Pending)

Leveraging Machine Learning for Insights and Predictions in Synthetic E-commerce Data in the USA: A Comprehensive Analysis
Published in: (Journal details pending)
Cited by: (Pending)

Zhe PENG | Data Analytics | Best Researcher Award

Posted on by sciencefather

Prof. Zhe PENG | Analytics | Best Researcher Award

Assistant Professor, The Hong Kong Polytechnic University, Hong Kong

Dr. Zhe Peng  is a dedicated Research Assistant Professor at the Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University. With a strong background in computer science and engineering, he specializes in intelligent supply chains, AI for manufacturing, and blockchain technologies. His contributions to blockchain, federated learning, and decentralized identity systems have earned him global recognition. With extensive academic and industry experience, Dr. Peng has made a significant impact on cutting-edge technological advancements.

Publication Profile

🎓 Education

Dr. Peng holds a Ph.D. in Computer Science from The Hong Kong Polytechnic University (2018), under the supervision of Prof. Bin Xiao (IEEE Fellow). He earned his M.E. in Information and Communication Engineering from the University of Science and Technology of China (2013) and a B.E. in Communication Engineering from Northwestern Polytechnical University (2010). His academic journey reflects his deep expertise in computing, communication, and AI-driven systems.

💼 Experience

Dr. Peng has held multiple research and industry positions. He is currently a Research Assistant Professor at The Hong Kong Polytechnic University. Previously, he served as a Research Assistant Professor at Hong Kong Baptist University (2020-2023) and as an R&D Manager at the Blockchain and FinTech Lab. In the industry, he worked as the Blockchain Technical Director at SF Technology in Shenzhen (2018-2019). Additionally, he was a Visiting Scholar at Stony Brook University, USA, working under Distinguished Prof. Yuanyuan Yang (IEEE Fellow).

🏆 Awards and Honors

Dr. Peng has received several prestigious awards, including the World’s Top 2% Scientists by Stanford University (2024) and the Award for High SFQ Score at PolyU ISE (2024). He was recognized with an ESI Highly Cited Paper (2023) and received the DASFAA-MUST Best Paper Award (2021). His work was also nominated for THE Awards Asia – Technological or Digital Innovation of the Year (2021). His numerous accolades highlight his contributions to academia, research, and technological innovation.

🔬 Research Focus

Dr. Peng’s research revolves around intelligent supply chains, AI-driven manufacturing, blockchain applications, and autonomous systems. His work on verifiable decentralized identity management, privacy-aware federated learning, and blockchain security has set new benchmarks in these fields. He continues to explore innovative solutions to improve efficiency, transparency, and security in digital ecosystems.

🔚 Conclusion

Dr. Zhe Peng is a visionary researcher at the intersection of AI, blockchain, and smart logistics. His groundbreaking research, academic excellence, and industry experience make him a leading expert in his field. Through his contributions to intelligent systems, federated learning, and blockchain security, he continues to shape the future of technological innovation. 🚀

🔗 Publications 

Lightweight Multimodal Defect Detection at the Edge via Cross-Modal Distillation

VDID: Blockchain-Enabled Verifiable Decentralized Identity Management for Web 3.0 

SymmeProof: Compact Zero-Knowledge Argument for Blockchain Confidential Transactions 

The Impact of Life Cycle Assessment Database Selection on Embodied Carbon Estimation of Buildings 

EPAR: An Efficient and Privacy-Aware Augmented Reality Framework for Indoor Location-Based Services

VFChain: Enabling Verifiable and Auditable Federated Learning via Blockchain Systems 

VQL: Efficient and Verifiable Cloud Query Services for Blockchain Systems 

Chunling Bao | Data Science | Best Researcher Award

Posted on by sciencefather

Ms. Chunling Bao | Data Science | Best Researcher Award

PhD Candidates, Shanghai Normal University, China

Chunling Bao is a dedicated Ph.D. candidate at Shanghai Normal University, specializing in environmental and geographical sciences 🌍. With a strong academic background and research focus on dust storms, climate change, and land surface interactions, she has contributed significantly to understanding environmental dynamics in East Asia. Her scholarly work is widely recognized, with multiple publications in high-impact journals 📚.

Publication Profile

ORCID

🎓 Education

Chunling Bao embarked on her academic journey at Inner Mongolia Normal University, earning her undergraduate degree (2014-2018) and later obtaining her master’s degree (2018-2021) 🎓. She expanded her expertise through an exchange program at the Center for Agricultural Resources Research, Chinese Academy of Sciences (2023), before pursuing her doctoral studies at Shanghai Normal University (2023-present) 🏫.

💼 Experience

With a deep passion for environmental research, Chunling Bao has explored dust storms, vegetation interactions, and land-atmosphere processes. Her experience includes field studies, satellite data analysis, and interdisciplinary research collaborations 🌪️. Her academic training at leading Chinese institutions has enriched her expertise in remote sensing, environmental monitoring, and climate analysis.

🏆 Awards and Honors

Chunling Bao has been recognized for her outstanding research contributions in environmental science 🏅. Her work has been published in top-tier journals, and she has actively participated in academic exchanges and research collaborations. Her efforts in studying dust storm dynamics have positioned her as an emerging scholar in the field 🌿.

🔬 Research Focus

Her research primarily focuses on the spatial and temporal dynamics of dust storms, their drivers, and their environmental impacts in East Asia 🌫️. Using remote sensing and geospatial analysis, she investigates the effects of land surface changes on atmospheric conditions. Her studies contribute to climate adaptation strategies and sustainable environmental management.

📌 Conclusion

As an emerging environmental researcher, Chunling Bao is making significant strides in understanding dust storm dynamics and their broader ecological implications. With her growing academic contributions and research excellence, she continues to shape the field of environmental science and atmospheric studies 🌏.

📚 Publications

Dust Intensity Across Vegetation Types in Mongolia: Drivers and Trends. Remote Sensing, 17(3), 410. 🔗 DOI

Analyses of the Dust Storm Sources, Affected Areas, and Moving Paths in Mongolia and China in Early Spring. Remote Sensing, 14, 3661. 🔗 DOI

Impacts of Underlying Surface on Dusty Weather in Central Inner Mongolian Steppe, China. Earth and Space Science, 8, e2021EA001672. 🔗 DOI

Regional Spatial and Temporal Variation Characteristics of Dust in East Asia. Geographical Research, 40(11), 3002-3015. 🔗 DOI (in Chinese)

Analysis of the Movement Path of Dust Storms Affecting Alxa. Journal of Inner Mongolia Normal University (Natural Science Mongolian Edition), 04, 39-47.

Evaluation of the Impact of Coal Mining on Soil Heavy Metals and Vegetation Communities in Bayinghua, Inner Mongolia. Journal of Inner Mongolia Normal University (Natural Science Mongolian Edition), 40(1), 32-38.

 

 

Isabel de la Torre | Computer Science | Women Researcher Award

Posted on by sciencefather

Prof Dr. Isabel de la Torre | Computer Science | Women Researcher Award

Catedrática, Universidad de Valladolid, Spain

Isabel de la Torre Díez, born in 1979 in Zamora, Spain, is a renowned Full Professor at the University of Valladolid. She received her M.S. and Ph.D. degrees in Telecommunication Engineering from the same university in 2003 and 2010, respectively. Isabel’s expertise lies in telemedicine, e-health, m-health, and related fields. She has authored over 250 papers and played a significant role in numerous research projects. Isabel leads the GTe Research Group and is a key figure in the field of telemedicine and e-health. 🌐👩‍🏫

Publication Profile

 

Strengths for the Award

  1. Significant Research Contributions: Isabel de la Torre Díez has published over 250 papers in SCI journals, peer-reviewed conferences, and books. This extensive publication record highlights her impactful research in telemedicine, e-health, and related fields.
  2. Leadership and Innovation: She leads the GTe Research Group at the University of Valladolid and has been involved in creating and coordinating innovative software. Her leadership in advancing telemedicine and e-health applications demonstrates her commitment to improving healthcare through technology.
  3. Research Impact and Recognition: She has been involved in over 100 international conference program committees and has participated in numerous funded research projects. Her involvement as a reviewer for well-known SCI journals further underscores her expertise and influence in her field.
  4. Research and Teaching Excellence: With two research sexenios, she has demonstrated consistent research excellence. Her role in guiding doctoral theses and her contributions to high-impact journals and conferences reflect her high standing in the academic community.
  5. International Collaboration: Her postdoctoral research experiences in Portugal, Spain, and France highlight her international collaboration and mobility, enhancing her global research network and exposure.

Areas for Improvement

  1. Broader Recognition: While her research is extensive, further highlighting any awards or recognitions she has received could strengthen her application. Emphasizing awards or honors related to her research could enhance her candidacy.
  2. Diversity of Research Interests: While her focus is on telemedicine and e-health, demonstrating how her research contributes to a broader range of applications or interdisciplinary areas might strengthen her profile.
  3. Detailed Impact Metrics: Providing specific metrics, such as citation counts, h-index, and impact factors of the journals where she has published, could offer a clearer picture of her research impact.

Conclusion

Isabel de la Torre Díez is a highly qualified candidate for the Research for Women Researcher Award. Her extensive research contributions, leadership in innovative projects, and active participation in international research communities position her as a leading figure in her field. Enhancing her application with additional recognitions and detailed impact metrics could further bolster her candidacy. Overall, her achievements and ongoing contributions to the field of telemedicine and e-health make her a strong contender for the award.

Education 🎓

Isabel de la Torre Díez earned her M.S. and Ph.D. degrees in Telecommunication Engineering from the University of Valladolid, Spain, in 2003 and 2010, respectively. Her education laid a strong foundation for her prolific career in telemedicine and e-health. 🏫📜

Experience 👩‍💼

Isabel de la Torre Díez is a Full Professor in the Department of Signal Theory and Communications and Telematics Engineering at the University of Valladolid. She has authored over 250 papers and coauthored 16 registered innovative software. Isabel has been involved in more than 100 international conference program committees and has participated in 44 funded research projects. She is also a reviewer for renowned journals like the International Journal of Medical Informatics. 🏫📚

Research Focus 🔬

Isabel’s research focuses on the development and evaluation of telemedicine applications, e-health, m-health, EHRs (Electronic Health Records), machine and deep learning, privacy and security, biosensors, QoS (Quality of Service), and QoE (Quality of Experience) in the health field. She has significantly contributed to these areas, particularly in telepsychiatry, teleophthalmology, and telecardiology. 🧠💻

Awards and Honors 🏆

Isabel de la Torre Díez has received numerous accolades throughout her career. She has two research sexenios and coordinates the GTe Research Group and the GIR “Society of Information” group. She has also been recognized for her contributions as a reviewer for prestigious journals and her leadership in various research projects and collaborations. 🌟🏅

Publications 📄

  1. Novel model to authenticate role-based medical users for blockchain-based IoMT devices
    PLOS ONE
    2024-07-10
    DOI: 10.1371/journal.pone.0304774
  2. A Digital Mental Health Approach for Supporting Suicide Prevention: A Qualitative Study
    International Journal of Mental Health and Addiction
    2024-06-21
    DOI: 10.1007/s11469-024-01347-4
  3. A deep learning approach for Named Entity Recognition in Urdu language
    PLoS ONE
    2024
    DOI: 10.1371/journal.pone.0300725
    Cited by 1 article
  4. A Detectability Analysis of Retinitis Pigmentosa Using Novel SE-ResNet Based Deep Learning Model and Color Fundus Images
    IEEE Access
    2024
    DOI: 10.1109/ACCESS.2024.3367977
    Cited by 1 article

 

HaiTian Chen | Computer Science | Best Researcher Award

Posted on by sciencefather

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

Posted on by sciencefather

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]

Jihyeon Ryu | Computer Science | Best Researcher Award

Posted on by sciencefather

Assist Prof Dr. Jihyeon Ryu | Computer Science | Best Researcher Award

Professor, Kwangwoon University, South Korea

👩‍🏫 Jihyeon Ryu is an Assistant Professor at the School of Computer and Information Engineering, Kwangwoon University. She specializes in split learning, convolutional neural networks, and user authentication, contributing significantly to the field of computer science with her extensive research and numerous publications.

Profile

Google Scholar

 

Education

Ph.D. in Software (Integrated Master’s and Doctorate Course) from Sungkyunkwan University (Mar. 2018 – Feb. 2023), advised by Prof. Dongho Won and Prof. Hyoungshick Kim. B.S. in Mathematics and Computer Science and Engineering from Sungkyunkwan University (Mar. 2013 – Feb. 2018). Early Graduation from Sejong Science High School (Mar. 2011 – Feb. 2013).

 

Research Interests:

Split Learning. Convolutional Neural Networks. User Authentication

Awards

Family Company Workshop Lecture, Hoseo University (Feb. 2022). Invited Lecturer, Mental Women’s High School (Nov. 2021). Excellence Prize, Software Department Excellence Research Awards (Feb. 2021). Graduate Merit Scholarship, Sungkyunkwan University (Mar. 2018 – Feb. 2021). SimSan Scholarship, Multiple instances (Mar. 2018 – Sep. 2020). Excellence Award, 국가 암호기술 전문인력 양성과정 (Nov. 2019). Grand Prize, Software Department Excellence Research Awards (Feb. 2019). Samsung Science Scholarship (Mar. 2013 – Feb. 2018)

Publications

Lightweight Hash-Based Authentication Protocol for Smart Grids. Sensors, 2024. Sangjin Kook, Keunok Kim, Jihyeon Ryu, Youngsook Lee, Dongho Won.

Enhanced Lightweight Medical Sensor Networks Authentication Scheme Based on Blockchain. IEEE ACCESS, 2024. Taewoong Kang, Naryun Woo, Jihyeon Ryu.

Secure and Anonymous Authentication Scheme for Mobile Edge Computing Environments. IEEE Internet of Things Journal, 2024. Hakjun Lee, Jihyeon Ryu, Dongho Won.

Distributed and Federated Authentication Schemes Based on Updatable Smart Contracts. Electronics, 2023. Keunok Kim, Jihyeon Ryu, Hakjun Lee, Youngsook Lee, Dongho Won.

An Improved Lightweight User Authentication Scheme for the Internet of Medical Things. Sensors, 2023. Keunok Kim, Jihyeon Ryu, Youngsook Lee, Dongho Won.