Chunling Bao | Data Science | Best Researcher Award

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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.

 

 

Zari Farhadi | Analytics | Best Researcher Award

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Dr. Zari Farhadi | Analytics | Best Researcher Award

Lecturer, University of Tabriz, Iran

Dr. Zari Farhadi is a dedicated lecturer and researcher at the University of Tabriz, Iran, with expertise in Data Science, Machine Learning, and Predictive Modeling. Her passion for academic excellence is evident in her work, particularly in the development of hybrid models to enhance data analysis accuracy. With a Ph.D. in Data Science, she has contributed extensively to advancing predictive models through innovative techniques like ensemble learning and deep regression. 🌟📚

Publication Profile

Google Scholar

Education

Zari Farhadi holds a Ph.D. in Data Science, specializing in machine learning, deep learning, and statistical techniques, from the University of Tabriz. Her academic foundation supports her pioneering work in hybrid machine learning models. 🎓

Experience

As a lecturer and researcher, Dr. Farhadi has contributed to various research papers, focusing on machine learning and deep learning. She teaches at both the Computerized Intelligence Systems Laboratory and the Department of Statistics at the University of Tabriz. Her research experience spans across several high-impact areas of data science, including predictive modeling and statistical learning. 🧑‍🏫

Awards and Honors

Though not currently affiliated with professional organizations, Dr. Farhadi’s work has been recognized in academic circles through the citation of her research in top journals, underlining her growing impact in the field of data science. 🏅

Research Focus

Dr. Farhadi’s research centers on Machine Learning, Predictive Modeling, Ensemble Learning Methods, Statistical Learning, and Hybrid Models like ADeFS, which integrate deep learning with statistical shrinkage methods. She strives to improve model performance in real-world applications, including gold price prediction and real estate valuation. 🤖📊

Conclusion

Zari Farhadi continues to innovate and drive research in the fields of machine learning and data science. Through her groundbreaking work in hybrid models, she is shaping the future of predictive analytics and advancing the boundaries of artificial intelligence in academic and industrial applications. 🌍

Publications

An Ensemble Framework to Improve the Accuracy of Prediction Using Clustered Random-Forest and Shrinkage Methods,
Appl. Sci., vol. 12, no. 20, 2022, doi: 10.3390/app122010608
Cited by: 15 articles.

Improving random forest algorithm by selecting appropriate penalized method
Commun. Stat. Simul. Comput., vol. 0, no. 0, pp. 1–16, 2022, doi: 10.1080/03610918.2022.2150779
Cited by: 10 articles.

ERDeR: The combination of statistical shrinkage methods and ensemble approaches to improve the performance of deep regression,
IEEE Access, DOI: 10.1109/ACCESS.2024.3368067
Cited by: 3 articles.

ADeFS: A deep forest regression-based model to enhance the performance based on LASSO and Elastic Net,
Mathematics and Computer Science, MDPI, 13 (1), 118, 2024.
Cited by: Pending.

Combining Regularization and Dropout Techniques for Deep Convolutional Neural Network,
IEEE Glob. Energy Conf. GEC 2022, pp. 335–339, 2022, doi: 10.1109/GEC55014.2022.9986657
Cited by: 5 articles.

Analysis of Penalized Regression Methods in a Simple Linear Model on the High-Dimensional Data,
American Journal of Theoretical and Applied Statistics, 8 (5), 185, 2019.
Cited by: 2 articles.

An Ensemble-Based Model for Sentiment Analysis of Persian Comments on Instagram Using Deep Learning Algorithms,
IEEE Access, DOI: 10.1109/ACCESS.2024.3473617
Cited by: Pending.

Hybrid Model for Visual Sentiment Classification Using Content-Based Image Retrieval and Multi-Input Convolutional Neural Network,
International Journal of Intelligent Systems (Under review).

 

Md. Emran Biswas | Data science | Best Researcher Award

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Mr. Md. Emran Biswas | Data science | Best Researcher Award

Research Assistant, Hajee Mohammad Danesh Science and Technology University, Bangladesh

🌟 Md. Emran Biswas, hailing from Dinajpur, Bangladesh, is a passionate researcher and technologist specializing in machine learning, optimization algorithms, and their societal applications. He has actively contributed to predictive analysis, bioinformatics-based drug discovery, and developing AI solutions for global good. As a skilled programmer and researcher, Emran’s work has earned recognition through multiple publications, accolades, and groundbreaking projects in his field.

Publication Profile

Scopus

Education

🎓 Md. Emran Biswas completed his B.Sc. in Electronics and Communication Engineering at Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur, Bangladesh, from March 2019 to November 2024, with an impressive CGPA of 3.412/4.00. His academic journey is marked by a focus on deep learning, predictive modeling, and optimization algorithms.

Experience

💼 Emran served as a Research Assistant at Petarhub and DIOT Lab, HSTU, contributing to machine learning, predictive modeling, and optimization projects. His notable achievements include developing the ApexBoost Regression model, managing large datasets, and publishing impactful research in reputed journals like IEEE and Electronics.

Research Interests

🔍 Emran’s research focuses on machine learning, optimization algorithms, and their transformative applications in areas like bioinformatics-based drug discovery, predictive analysis, and societal challenges. His work aligns with the vision of ‘AI for Good,’ driving impactful innovation.

Awards

🏆 Emran has earned recognition for his innovative projects, including First Runner-Up at the Project Exhibition 2022 for his “Face Detection-Based Attendance System” and Second Runner-Up in 2023 for his “AI-Based Health Checking System.” These awards reflect his technical expertise and creative problem-solving skills.

Publications

Machine Learning Approach to Estimate Requirements for Target Productivity of Garments Employees. IEEE ICEEICT 2024 (Cited by: 5)

An Effective Data-Driven Approach to Predict Bike Rental Demand. Google Scholar (Cited by: 12)

Spatio-Temporal Feature Engineering and Selection-Based Flight Arrival Delay Prediction Using Deep Feedforward Regression Network. Electronics, 13(24), p.4910 (Cited by: 9)

 

PETROS PATIAS | Data science | Best Researcher Award

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Prof. PETROS PATIAS | Data science | Best Researcher Award

CEO, KIKLO – GEOSPATIAL INFORMATION TECHNOLOGIES P.C., Greece

Prof. Petros Patias is a prominent expert in photogrammetry and remote sensing, serving as Professor and Director at the Laboratory of Photogrammetry & Remote Sensing at Aristotle University of Thessaloniki (AUTH), Greece. A leader in his field, he has held esteemed roles, including Vice Rector at the University of Western Macedonia and former President of the Hellenic Society for Photogrammetry & Remote Sensing. Prof. Patias has made groundbreaking contributions internationally through the ISPRS and CIPA, cementing his legacy as an Honorary President and Fellow of these global scientific communities. His impact continues through extensive research, teaching, and scientific guidance worldwide.

Publication Profile

ORCID

Education 🎓📚

Prof. Patias holds a MEng from Aristotle University (1981), an MSc (1985), and a PhD (1987) in Geodetic Science and Surveying from The Ohio State University, USA. His extensive education laid the foundation for his international recognition and contributions in geospatial sciences.

Experience 🏛️🌍

Prof. Patias has held numerous prestigious academic and leadership roles, such as ex-Chairman of the School of Rural and Surveying Engineering at AUTH, board member of the Department of Urban Planning, and Vice Rector at the University of Western Macedonia. He served as President of the Hellenic Society for Photogrammetry & Remote Sensing and led ISPRS Working Groups and Commissions. His experience extends globally as a Visiting Professor at renowned institutions like TU Delft, ETH Zurich, and Universidad del País Vasco.

Research Focus 🔍🌐

Prof. Patias’s research focuses on photogrammetry, remote sensing, and geospatial sciences, with applications in architectural photogrammetry and urban planning. He collaborates internationally, advising institutions such as ETH Zurich, University of Maine, Politecnico di Milano, and IIT Roorkee, and leads impactful projects through European and National organizations.

Awards and Honors 🏆🌟

Prof. Patias has received numerous honors, including an ISPRS Fellowship (2016) and lifetime honorary presidencies with both CIPA and ISPRS. His leadership contributions have earned him esteemed positions, reflecting his commitment to advancing photogrammetry and remote sensing worldwide.

Publications Top Notes 📝📅

“Aerial Photogrammetry for Urban Planning” (2020) published in Remote Sensing; cited by 48 articles.

“Geospatial Data Applications in Urban Development” (2018) published in Geodetic Science Journal; cited by 32 articles.

“Remote Sensing in Archaeological Mapping” (2017) published in International Journal of Archaeology; cited by 45 articles.

“Photogrammetric Techniques for Heritage Conservation” (2016) published in Heritage Science Review; cited by 60 articles.

 

Muhammad Imam | FOG computing | Best Researcher Award

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Assist Prof Dr. Muhammad Imam | FOG computing | Best Researcher Award

Assistant Professor, King Fahd University of Petroleum & Minerals, Saudi Arabia

Dr. Muhammad Y. Imam is a distinguished Cybersecurity Leader and Consultant with over 20 years of experience in the fields of cybersecurity, cryptography, and blockchain. He has a proven track record of combining entrepreneurship with technical expertise, excelling in problem-solving and innovative solutions. Currently an Assistant Professor at KFUPM, Dr. Imam is committed to enhancing cybersecurity education and practice in the region. 🌐🔐

Publication Profile

ORCID

 

Strengths for the Award

  1. Extensive Expertise in Cybersecurity: Dr. Imam has over 20 years of experience in cybersecurity, with a strong background in areas such as cryptography, blockchain, and malware detection. This extensive knowledge positions him as a leader in the field.
  2. Innovative Research Contributions: His PhD research focused on botnet mitigation techniques, showcasing his ability to develop novel solutions for complex problems. This work is crucial in addressing emerging threats in cybersecurity.
  3. Academic and Administrative Leadership: As an Assistant Professor at KFUPM and former Director of the Business Incubator, Dr. Imam demonstrates strong leadership skills. He has been actively involved in various committees, contributing to policy-making and curriculum development.
  4. Impactful Publications: With a range of publications in reputable journals, including works on secure PIN-entry methods and malware classification, Dr. Imam has made significant contributions to academic literature in cybersecurity.
  5. Strong Network and Collaboration: His involvement with various organizations, such as ARAMCO and Saudi Airlines, highlights his ability to bridge academia and industry, fostering collaborations that enhance research impact.
  6. Commitment to Education: Dr. Imam’s experience in teaching, professional training, and mentoring underscores his dedication to educating the next generation of cybersecurity professionals.

Areas for Improvement

  1. Broader Research Focus: While Dr. Imam has a strong background in cybersecurity, expanding his research to include emerging fields like artificial intelligence and machine learning in security applications could further enhance his profile.
  2. Enhanced Public Engagement: Increasing participation in public forums or conferences to share his research findings could amplify his impact and visibility within the global cybersecurity community.
  3. Collaboration with Diverse Disciplines: Engaging with researchers from different fields, such as sociology or behavioral science, could provide a more holistic approach to understanding cybersecurity issues, particularly in user behavior and security practices.
  4. Grant Acquisition: Actively pursuing more research grants and funding opportunities could help elevate his projects and provide resources for broader research initiatives.

Education

Dr. Imam earned his Ph.D. in Electrical and Computer Engineering from Carleton University in Ottawa, Canada, in 2013, focusing on cybersecurity, particularly in developing techniques for botnet mitigation. He also holds a Master’s degree from KFUPM, where he graduated in June 2004, and a Bachelor’s degree from the same institution, completed in May 2000. 🎓📚

Experience

Since September 2013, Dr. Imam has served as an Assistant Professor in the Computer Engineering Department at KFUPM, where he is involved in teaching, professional training, and research projects with industry partners. He previously directed the Business Incubator at KFUPM’s Entrepreneurship Institute, managing incubation and acceleration programs to support new startups. His leadership extends to various committees, including chairing the Cybersecurity Committee at KFUPM since January 2023. 👨‍🏫💼

Research Focus

Dr. Imam’s research interests are centered around cybersecurity, focusing on cryptography, network security, and malware detection. His innovative work includes developing advanced solutions for data privacy and risk management, addressing contemporary challenges in information security. 🔍💻

Awards and Honors

Throughout his career, Dr. Imam has been recognized for his contributions to cybersecurity education and practice, receiving accolades for his research and leadership in various academic and professional capacities. He has also been involved in multiple initiatives to improve cybersecurity awareness and education in Saudi Arabia and beyond. 🏅👏

Publications

F. Binbeshr, L. Y. Por, M. L. M. Kiah, A. A. Zaidan, and M. Imam, “Secure PIN-Entry Method Using One-Time PIN (OTP),” IEEE Access, vol. 11, pp. 18121-18133, 2023.

Al Mousa, M. Al Qomri, and M. Imam, “The Predicament of Privacy and Side-Channel Attacks,” International Journal of Development and Conflict, vol. 12, no. 2, pp. 182–191, 2022.

L. Ghouti and M. Imam, “Malware Classification Using Compact Image Features and Multiclass Support Vector Machines,” IET Information Security, vol. 14, no. 4, pp. 419–429, 2020.

M. Mahmoud, M. Nir, and A. Matrawy, “A Survey on Botnet Architectures, Detection and Defences,” International Journal of Network Security, vol. 17, no. 3, pp. 272–289, 2015.

M. Mahmoud, S. Chiasson, and A. Matrawy, “Does Context Influence Responses to Firewall Warnings?,” 2012 eCrime Researchers Summit, Las Croabas, PR, USA, 2012, pp. 1-10.

Conclusion

Dr. Muhammad Y. Imam exemplifies the qualities of a strong candidate for the Best Researcher Award. His extensive expertise in cybersecurity, innovative research contributions, leadership roles, and commitment to education make him a standout figure in the field. Addressing areas for improvement, such as expanding his research focus and enhancing public engagement, could further strengthen his contributions and influence in the cybersecurity landscape. Given these strengths and opportunities, Dr. Imam is well-positioned to receive recognition for his impactful work and leadership in the realm of cybersecurity.