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.

 

 

sajjad qureshi | Artificial Intelligence Award | Computer Vision Contribution Award

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Dr. sajjad qureshi | artificial intelligence award | Computer Vision Contribution Award

deputy Director (IT), multan electric power company, Pakistan

📘 Dr. Sajjad Hussain Qureshi is a seasoned professional with over 21 years of experience in Information Technology. Currently serving as the Deputy Director (IT) at Multan Electric Power Company for the past two decades, Dr. Qureshi has established expertise in system analysis and design, machine learning, cybersecurity, IT auditing, and project management. His multidisciplinary educational background, including a Ph.D. in Computer Science, Ph.D. in Agriculture, and an MBA in Human Resource Management, has enabled him to excel in IT-based quality assurance, data analysis, and human resource management. He is passionate about utilizing cutting-edge technologies to create impactful solutions in diverse domains.

Publication Profile

ORCID

Education

🎓 Dr. Qureshi holds a Ph.D. in Computer Science, a Ph.D. in Agriculture, and an MBA in Human Resource Management. His diverse academic achievements reflect his commitment to integrating IT with interdisciplinary knowledge for impactful research and practical solutions.

Experience

💼 Dr. Qureshi has an extensive career spanning over 21 years in the IT field. For the last 20 years, he has been a cornerstone of the Multan Electric Power Company, where he serves as the Deputy Director (IT). His experience covers IT infrastructure development, LAN networks, client/server environments, cybersecurity, and customer billing systems. He also excels in IT-based quality assurance and control, project management, and data management.

Research Interests

🔍 Dr. Qureshi’s research interests lie at the intersection of machine learning, deep learning, cybersecurity, data management, and agriculture technology. He is particularly interested in applying advanced computational techniques to solve real-world problems, such as disease detection in crops and classification of linguistic data.

Awards

🏆 Dr. Qureshi has been recognized for his contributions to IT and interdisciplinary research, achieving notable academic and professional milestones. His work continues to inspire innovation and collaboration across diverse fields.

Publications

Classification of English Words into Grammatical Notations Using Deep Learning Technique (2024)
Imran, M., Qureshi, S. H., Qureshi, A. H., & Almusharraf, N.
Published in Information, 15(12), 801.
DOI: 10.3390/info15120801

Rational Study Of The Use Of Computer-Aided Softwares By The Composers (2024)
Qureshi, S. H., Javaid, S., & Javaid, M. A.
Published in Pakistan Journal of Society, Education and Language, 10(2), 213–219.

Comparison of Conventional and Computer-Based Detection of Severity Scales of Stalk Rot Disease in Maize (2024)
Qureshi, S.H., Khan, D.M., Razzaq, A., Baig, M.M., & Bukhari, S.Z.A.
Published in SABRAO Journal of Breeding and Genetics, 56(1), 292–301.
DOI: 10.54910/sabrao2024.56.1.26

Intelligent Resistant Source Detection Against Stalk Rot Disease of Maize Using Deep Learning Technique (2023)
Qureshi, S.H., Khan, D.M., & Bukhari, S.Z.
Published in SABRAO Journal of Breeding and Genetics, 55(6), 1972–1983.

soheila nazari | neural network | Best Researcher Award

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Assist Prof Dr. soheila nazari | neural network | Best Researcher Award

university faculty, shahid beheshti university, Iran

🎓 Dr. Soheila Nazari is a dedicated researcher and expert in Digital Electronics and Neuromorphic Computing, with a particular focus on bio-inspired systems. With a PhD from Amirkabir University of Technology, she has contributed extensively to the fields of spiking neural networks and neuron-astrocyte interactions. Dr. Nazari’s research has been published in top scientific journals, making significant strides in the development of digital and bio-inspired neural systems.

Publication Profile

Google scholar

Strengths for the Award:

  1. Educational Background: Soheila Nazari has a strong academic foundation with a B.Sc., M.Sc., and Ph.D. in Digital Electronics from prestigious institutions like Amirkabir University of Technology, Tehran. Her high GPAs and excellent thesis scores (19.5, 20, and 20) demonstrate her commitment and expertise in her field.
  2. Innovative Research: Her Ph.D. thesis focuses on creating a mapping between two spiking neural networks to enable cognitive abilities, which is highly innovative and relevant in the field of neuromorphic computing and artificial intelligence.
  3. Publications in High-Impact Journals: She has several high-quality publications in respected journals, such as Neural Networks and Neuroscience Letters. Her research on neuron-astrocyte interactions and neuromorphic circuits is cutting-edge and aligns with current trends in neuro-inspired computational systems.
  4. Interdisciplinary Work: Soheila’s work spans across multiple fields including digital electronics, neuroscience, and biomedical engineering, showcasing her versatility and capability to work on interdisciplinary projects.
  5. Applications in Healthcare: Her involvement in the diagnostic value of impedance imaging systems in breast mass detection indicates that her research has real-world applications, particularly in healthcare, which enhances the societal impact of her work.

Areas for Improvement:

  1. Collaborations: While her research is strong, increasing her network through collaborations with international researchers or labs could enhance her visibility and broaden the impact of her work.
  2. Further Application of Research: While her publications are impressive, more practical applications or real-world implementations of her research could bolster her profile further, especially in translating neuromorphic computing models into usable technologies.
  3. Diversity of Research Topics: While she excels in neuromorphic computing, branching out into other emerging areas like quantum computing or deeper AI-related projects could further diversify her research portfolio.

Education

📚 Dr. Soheila Nazari holds a B.Sc. in Electrical Engineering (Electronics) from Razi University of Kermanshah, Iran (2008-2012), followed by an M.Sc. and Ph.D. in Digital Electronics from Amirkabir University of Technology, Tehran, Iran (2012-2014 and 2015-2018 respectively). Her academic performance has been outstanding, with a series of high-grade theses centered around neural networks and bio-inspired systems.

Experience

💻 Throughout her academic and professional career, Dr. Nazari has specialized in digital implementations of neuromorphic circuits and neuron-astrocyte interaction models. Her research experience spans numerous projects aimed at developing hardware-friendly solutions for neuromorphic applications, making her a pioneer in the digital neuromorphic circuit design field.

Research Focus

🧠 Dr. Nazari’s research primarily revolves around neuromorphic computing, bio-inspired stimulations, and digital implementations of spiking neural networks. Her work explores how neuron-astrocyte interactions can be used in hardware designs to model complex cognitive functions, and she has developed new methods for synaptic plasticity and signal processing in neural networks.

Awards and Honours

🏆 Dr. Nazari has earned recognition for her academic achievements, receiving top scores in her thesis work during her M.Sc. and Ph.D. studies. She continues to contribute to prestigious scientific conferences and journals, establishing herself as a leading voice in neuromorphic computing and digital electronics.

Publication Top Notes

📄 Dr. Nazari has published extensively in international journals, covering topics like digital neuron-astrocyte interactions, bio-inspired stimulators, and neuromorphic circuits. Her work is highly cited, reflecting its impact in the field.

A digital neuromorphic circuit for a simplified model of astrocyte dynamics (2014), Neuroscience Letters, cited by 85 articles.

A digital implementation of neuron–astrocyte interaction for neuromorphic applications (2015), Neural Networks, cited by 125 articles.

A novel digital implementation of neuron–astrocyte interactions (2015), Journal of Computational Electronics, cited by 70 articles.

Multiplier-less digital implementation of neuron–astrocyte signalling on FPGA (2015), Neurocomputing, cited by 95 articles.

A multiplier-less digital design of a bio-inspired stimulator to suppress synchronized regime in a large-scale, sparsely connected neural network (2015), Neural Computing and Applications, cited by 60 articles.

Conclusion:

Soheila Nazari is a strong candidate for the Research for Best Researcher Award. Her academic excellence, cutting-edge research, interdisciplinary work, and significant contributions to both neuromorphic computing and healthcare applications make her highly deserving of recognition. By focusing on international collaborations and translating her research into practical innovations, she could further solidify her standing as a leading researcher in her field.

Muhammad Sajjad | Computer Science | Best Researcher Award

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 Dr.  Muhammad Sajjad | Computer Science | Best Researcher Award

Faculty (Visiting), Quaid-I-Azam University Islamabad, Pakistan

Muhammad Sajjad is a Pakistani mathematician specializing in cybersecurity and cryptography. With a Ph.D. from Quaid-i-Azam University, his research focuses on advanced coding and cryptographic schemes, published extensively in renowned journals. He’s received numerous awards, including the International Research Award on Cybersecurity and Cryptography. Sajjad’s expertise extends to teaching and international collaborations, contributing significantly to academia. 🎓 His innovative work bridges theoretical mathematics with practical applications, ensuring data security in the digital age. 🛡️

Profile 

ORCID

🎓 Education

Muhammad Sajjad holds a Doctor of Philosophy (Ph.D.) in Mathematics from Quaid-i-Azam University, Islamabad. He also completed his Master of Philosophy (M.Phil.) and Master of Science (M.Sc.) degrees from the same institution.

💼 Experience

He has significant experience in academia, having taught various mathematics courses at Quaid-i-Azam University, National University of Modern Languages, Bahria University, and FG Sir Syed College. He has also been involved in research conferences and international collaborations.

🔍 Research Interests

Sajjad’s research interests span across several areas including Mathematics, Electrical Engineering, Vector Algebra, Non-commutative Algebra, Number Theory, Coding Theory, Channel Coding, and Cryptography.

🏆 Awards

He has received numerous awards and scholarships throughout his academic journey, including the International Research Award on Cybersecurity and Cryptography and being a finalist for PakCrypto by the National Centre for Cyber Security (NCCS).

📚 Publications

Sajjad, M., Shah, T., Haq, T.U., Almutairi, B., & Xin, Q., “SPN based RGB Image Encryption over Gaussian Integers,” Heliyon, vol. 10, 2024. Link (Cited by: 0)

Sajjad, M., & Shah, T., “Decoding of cyclic codes over quaternion integers by modified Berlekamp–Massey algorithm,” Computational and Applied Mathematics, 43(2), 2024. Link (Cited by: 0)

Sajjad, M., Shah, T., Alsaud, H., & Alammari, M., “Designing pair of nonlinear components of a block cipher over quaternion integers,” AIMS Mathematics, vol. 8, 2023. Link (Cited by: 0)

Sajjad, M., Shah, T., Xin, Q., & Almutairi B., “Eisenstein field BCH codes constructions and decoding,” AIMS Mathematics, vol. 8. Link (Cited by: 0)

Sajjad, M., Shah, T., Alammari, M., & Alsaud, H., “Construction and Decoding of BCH-Codes Over the Gaussian Field,” IEEE Access, vol. 11, 2023. Link (Cited by: 0)