Seyed Abolfazl Aghili | Deep Learning | Best Review Paper Award

Posted on by Computer Scientists Awards

Dr. Seyed Abolfazl Aghili | Deep Learning | Best Review Paper Award

lecturer, iran university of science and technology, Iran

Seyed Abolfazl Aghili is a passionate civil engineer with a strong focus on construction engineering and management. With a Ph.D. in Civil Engineering from the prestigious Iran University of Science and Technology (IUST), he specializes in using artificial intelligence for enhancing the resilience of HVAC systems in hospitals. His research integrates cutting-edge technologies such as machine learning and deep learning to optimize building systems and improve decision-making in construction projects. Seyed’s dedication to his field has earned him a reputation as a driven academic and professional in the civil engineering community. 🏗️🤖

Publication Profile

ORCID

Education Background

Seyed Abolfazl Aghili completed his Ph.D. in Civil Engineering with a specialization in Construction Engineering and Management from Iran University of Science and Technology (IUST) between 2019 and 2024. His doctoral thesis focused on developing a framework to assess the long-term resilience of hospital air conditioning systems using artificial intelligence. Prior to that, he earned his M.Sc. in Civil Engineering with a focus on Construction Engineering and Management at IUST, where he investigated employee selection methods in construction firms. He also holds a B.Sc. in Civil Engineering from Isfahan University of Technology (IUT). 🎓📚

Professional Experience

Seyed Abolfazl Aghili has extensive experience in both academic research and practical applications of civil engineering, particularly in construction management. He has worked on various projects involving energy management, risk management, and resilience within the construction industry. His academic journey has seen him contribute significantly to the research community, particularly in the areas of AI in construction systems and HVAC performance. Furthermore, he has been an integral part of various conferences and publications, sharing his insights on improving construction management processes through technology. 💼🏢

Awards and Honors

Seyed Abolfazl Aghili has earned several prestigious awards throughout his academic journey. He was ranked 5th among 2200 participants in the Nationwide University Entrance Exam for the Ph.D. program in Iran in 2019. Additionally, he ranked 2nd among all construction management students at Iran University of Science and Technology during his M.Sc. studies. He was also ranked in the top 1% (220th out of 32,663) in the Nationwide University Entrance Exam for the M.Sc. program in Iran in 2013. 🏆🥇

Research Focus

Seyed’s primary research interests lie in the application of machine learning and deep learning techniques in construction engineering. His work focuses on enhancing the resilience of building systems, especially HVAC systems in healthcare settings. He also explores risk management, sustainability, lean construction, and decision-making systems for project managers. His interdisciplinary research combines civil engineering with advanced AI methodologies, driving innovations in construction management and systems optimization. 🔍💡

Conclusion

Seyed Abolfazl Aghili’s academic and professional journey reflects his commitment to advancing civil engineering through innovative solutions. His focus on integrating artificial intelligence into construction systems is helping to create smarter, more sustainable, and resilient built environments. Through his work, he continues to contribute valuable insights to both the academic world and the practical sector of construction engineering. 🌍🔧

Publications Top Notes

Artificial Intelligence Approaches to Energy Management in HVAC Systems: A Systematic Review. Journal of Buildings, 15.7 (2025).

Data-driven approach to fault detection for hospital HVAC system. Journals of Smart and Sustainable Built Environment, ahead-of-print (2024).

Feasibility Study of Using BIM in Construction Site Decision Making in Iran. International Conference on Civil Engineering, Architecture and Urban Infrastructure, July 2015.

Review of digital imaging technology in safety management in the construction industry. 1st National Conference on Development of Civil Engineering, Architecture, Electricity and Mechanical in Iran (December, 2014).

The role of insurance companies in managing the crisis after earthquake. 1st National Congress of Engineering, Construction, and Evaluation of Development Projects, May 2013.

The need for a new approach to pre-crisis and post-crisis management of earthquake. 1st National Conference on Seismology and Earthquake, February 2013.

Dr. Aiai Wang | Machine Learning | Best Researcher Award

Posted on by Computer Scientists Awards

Dr. Aiai Wang | Machine Learning | Best Researcher Award

Doctoral student, University of Science and Technology Beijing, China

Ai-Ai Wang is a passionate and dedicated young researcher born in March 1998 in Langfang, Hebei Province, China. A proud member of the Communist Party of China (CPC), she is currently based at the University of Science and Technology Beijing (USTB), where she serves as the Secretary of the 16th Party Branch, 4 Zhaizhai. With a solid academic foundation in mining and civil engineering, Ai-Ai has excelled in both academic and research spheres, contributing significantly to digital and intelligent mining technologies. Her work emphasizes physical dynamics in tailings sand cementation and filling, showing strong potential for innovation in sustainable mining practices.

Publication Profile

Scopus

🎓Education Background:

Ai-Ai Wang completed her Bachelor of Science in Mining Engineering from North China University of Science and Technology in 2021. She further pursued her Master’s degree in Civil Engineering at the University of Science and Technology Beijing (2021.09–2024.06), affiliated with the School of Civil and Resource Engineering.

🛠️Professional Experience:

Alongside her academic journey, Ai-Ai has undertaken significant responsibilities, currently serving as Secretary of the Party Branch at USTB. Her leadership extends beyond administration into collaborative research projects, software development, and patent contributions under renowned mentors such as Prof. Cao Shuai. She has played vital roles in developing intelligent systems for mining operations, reinforcing her multidisciplinary strengths.

🏅Awards and Honors:

Ai-Ai Wang has been recognized extensively for her academic and research excellence. Notable accolades include the “Top Ten Academic Stars” at USTB (2023), a National Scholarship for Master’s Degree Students (2022), the prestigious Taishan Iron and Steel Scholarship (2023), and multiple First-Class Academic Scholarships from USTB. She was twice named an Outstanding Three-Good Graduate Student and honored by her school as an outstanding individual. Moreover, she has received scientific awards such as the First Prize from the China Gold Association and the Second Prize from the China Nonferrous Metals Industry for her impactful contributions to green and safe mining.

🔬Research Focus:

Ai-Ai Wang’s research is rooted in advanced techniques of tailings sand cementation, intelligent filling systems, and digital mining. She explores the structural stability of backfills, application of nanomaterials, and CT-based 3D modeling of internal structures. Her work blends civil engineering, environmental safety, and digital innovation, aiming to enhance sustainability and efficiency in modern mining. She also contributes to cutting-edge software systems and patented technologies for mining design and operation support.

📝Conclusion:

Ai-Ai Wang stands out as a promising engineer and researcher whose academic achievements, professional dedication, and innovative research in intelligent mining set a high standard for future civil and mining engineers. Her trajectory reflects not just technical mastery but a deep commitment to sustainable and smart engineering solutions in the mining industry.

📚Top Publications with Details

Effect of height to diameter ratio on dynamic characteristics of cemented tailings backfills with fiber reinforcement through impact loading – Construction and Building Materials, 2022
Cited by: 26 articles
Influence of types and contents of nano cellulose materials as reinforcement on stability performance of cementitious tailings backfill – Construction and Building Materials, 2022
Cited by: 20 articles
Quantitative analysis of pore characteristics of nanocellulose reinforced cementitious tailings fills using 3D reconstruction of CT images – Journal of Materials Research and Technology, 2023
Cited by: 12 articles

 

Dr. Saikat Gochhait | Artificial Intelligence | Best Researcher Award

Posted on by Computer Scientists Awards

Dr. Saikat Gochhait | Artificial Intelligence | Best Researcher Award

Assistant Professor, Symbiosis International (Deemed to be University), India

Dr. Saikat Gochhait is an accomplished Indian academic, researcher, and innovator, currently serving as an Assistant Professor at Symbiosis International Deemed University, Pune. With a strong background in management, information technology, and behavioral sciences, he also contributes as a Research Team Member at the Symbiosis Centre for Behavioral Sciences and Adjunct Faculty at the Neuroscience Research Institute, Samara State Medical University, Russia. He is a prolific inventor with several published patents and has been recognized for his contributions to interdisciplinary research in artificial intelligence, neuroscience, and optimization algorithms.

Publication Profile

🎓 Education Background

Dr. Gochhait earned his Doctor of Philosophy (Ph.D.) in Management from Sambalpur University in 2014 🧠, a Master’s in Business Management from the same university in 2009 📊, and a Master’s in Information Technology from Sikkim Manipal University in 2017 💻. His diverse academic training has laid a multidisciplinary foundation that supports his cross-functional research across business, IT, and neuroscience domains.

💼 Professional Experience

With over two decades of experience spanning academia and industry, Dr. Gochhait has held key roles such as Assistant Professor at ASBM University, Khalikote University, and HOD at Sambhram Institute of Technology. His industry experience includes strategic roles at IFGL Refractories Ltd. and Tata Krosaki Refractories Ltd. Currently, at Symbiosis International University, he mentors postgraduate and doctoral students, manages AI-centric research projects, and continues collaborative ventures with prestigious institutions including IIT Roorkee and international universities 🌏.

🏆 Awards and Honors

Dr. Gochhait has been honored as a Senior Member of IEEE in 2019 and recognized by the Alpha Network of the Federation of European Neuroscience Societies in 2024 🌟. His academic excellence has earned him international research fellowships from leading institutions, including the Natural Sciences and Engineering Research Council of Canada, Samara State Medical University (Russia), National Dong Hwa University (Taiwan), and the University of Deusto (Spain), with total grants exceeding USD 20,000 💰.

🔬 Research Focus

Dr. Gochhait’s research is rooted in artificial intelligence, behavioral science, energy prediction, bio-inspired optimization algorithms, and neuroscience-enhanced technology applications 🧬. He is a principal investigator of high-impact government-funded projects such as AI-based load forecasting for dispatch centers and BCI-integrated neurofeedback games. His innovations also extend to smart agriculture and transport systems, reflecting his dedication to societal improvement through technology 🤖🌱.

✅ Conclusion

Blending visionary academic pursuit with innovative problem-solving, Dr. Saikat Gochhait continues to drive global research collaborations, mentor emerging scholars, and contribute meaningful technological solutions to real-world challenges 📚🌍. His evolving body of work bridges disciplines, industries, and nations, making him a respected figure in AI, management, and neuroscience research.

📚 Top Publications

Pufferfish Optimization Algorithm: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems
Biomimetics, 2024 – Indexed in Scopus/WoS
Cited by: 12 articles

Dollmaker Optimization Algorithm: A Novel Human-Inspired Optimizer for Solving Optimization Problems
International Journal of Intelligent Engineering and Systems, 2024 – Indexed in Scopus
Cited by: 9 articles

Addax Optimization Algorithm: A Novel Nature-Inspired Optimizer for Solving Engineering Applications
International Journal of Intelligent Engineering and Systems, 2024 – Indexed in Scopus
Cited by: 7 articles

Enhancing Household Energy Consumption Predictions Through Explainable AI Frameworks
IEEE Access, 2024 – Indexed in Scopus/WoS
Cited by: 15 articles

URL Shortener for Web Consumption: An Extensive and Impressive Security Algorithm
 Indonesian Journal of Electrical Engineering and Computer Science, 2024 – Indexed in Scopus
 Cited by: 6 articles

Dr. Jiaheng Peng | Data Science | Best Researcher Award

Posted on by Computer Scientists Awards

Dr. Jiaheng Peng | Data Science | Best Researcher Award

PhD Candidate, East China Normal University, China

Jiaheng Peng is a dedicated Ph.D. candidate at East China Normal University, specializing in Open Source Ecosystem, Natural Language Processing, and Evaluation Science. With a strong academic record and a passion for research, he has contributed significantly to understanding Open Source dataset evaluation. His work bridges the gap between academic research and real-world Open Source applications, earning him recognition in the field.

Publication Profile

Google Scholar

🎓 Academic Background

Jiaheng Peng is pursuing his Ph.D. at East China Normal University, focusing on innovative methods to assess Open Source datasets. His research emphasizes citation network analysis, evaluating long-term dataset usage, and developing advanced Natural Language Processing (NLP) models. His academic journey is marked by high-impact publications in top-tier journals and international conferences, reflecting his expertise in computational analysis and data evaluation.

👨‍💼 Professional Experience

Although Jiaheng does not have industry consultancy or ongoing research projects, his scholarly contributions have made a substantial impact on Open Source ecosystem analysis. He actively publishes in high-impact scientific journals and conferences, ensuring that his findings help enhance dataset evaluation metrics. His commitment to advancing data-driven methodologies sets a solid foundation for future research in Open Source analysis.

🏆 Awards and Honors

Jiaheng Peng’s research excellence has been acknowledged with the Best Paper Award at the 1st Open Source Technology Academic Conference (2024). His publications in Q1-ranked journals further highlight his academic impact. His continuous contributions to the Open Source community demonstrate his dedication to advancing research and innovation in Open Source evaluation.

🔬 Research Focus

Jiaheng’s research primarily addresses the limitations of traditional Open Source data insight metrics. His work connects Open Source datasets with their corresponding academic papers, evaluating their significance through citation network mining. By bridging Open Source data with academic insights, he introduces novel evaluation methodologies that enhance dataset usability and long-term impact analysis. His research also extends into Aspect-Based Sentiment Classification, employing advanced Graph Attention Networks and NLP models to extract meaningful insights.

📌 Conclusion

Jiaheng Peng is a rising scholar in the Open Source and NLP domains, with a keen focus on dataset evaluation, citation network analysis, and sentiment classification. His academic contributions, recognized through prestigious awards and top-tier publications, establish him as a promising researcher dedicated to advancing Open Source dataset analytics. With a commitment to scientific excellence, his work continues to influence the global research community.

📚 Publication Top Notes

Evaluating long-term usage patterns of open source datasets: A citation network approach
BenchCouncil Transactions on Benchmarks, Standards and Evaluations (2025)
Cited by: Pending

DRGAT: Dual-relational graph attention networks for aspect-based sentiment classification
Information Sciences (2024)
Cited by: Pending

Data Driven Visualized Analysis: Visualizing Global Trends of GitHub Developers with Fine-Grained Geo-Details
International Conference on Database Systems for Advanced Applications (2024)
Cited by: Pending

ASK-RoBERTa: A pretraining model for aspect-based sentiment classification via sentiment knowledge mining”
Knowledge-Based Systems (2022)
Cited by: Multiple researchers in NLP and sentiment analysis

Chunling Bao | Data Science | Best Researcher Award

Posted on by Computer Scientists Awards

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

Posted on by Computer Scientists Awards

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

Posted on by Computer Scientists Awards

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

Posted on by Computer Scientists Awards

 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)