Fatemeh Barati | Computer Science | Innovative Research Award

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Innovative Research Award

Fatemeh Barati
Kharazmi University, Iran

Fatemeh Barati
Affiliation Kharazmi University
Country Iran
Scopus ID Not provided
Google Scholar ID QCQGhrgAAAAJ
Documents 1
Subject Area Computer Science
Event International Academic Achievements & Awards
ORCID 0009-0005-2611-3016

Fatemeh Barati is a researcher associated with Kharazmi University, Iran, with an academic profile identified in the field of Computer Science. Her available researcher information includes a Google Scholar profile and an ORCID identifier, providing persistent scholarly identity markers for research discovery and attribution. The available institutional and researcher information also associates her with computational and bioinformatics-oriented academic activity. [1] [2]

Abstract

The Innovative Research Award recognizes researchers whose scholarly activities demonstrate originality, methodological development, and potential contribution to the advancement of knowledge. Fatemeh Barati, affiliated with Kharazmi University in Iran, is presented in the Computer Science area on the basis of the available academic profile information, researcher identifiers, and documented scholarly record. Her profile is associated with computer science and computational research interests, including bioinformatics-related academic activity. [1] The available profile information records one scholarly document and provides persistent identifiers through Google Scholar and ORCID. [2]

Keywords

  • Fatemeh Barati
  • Innovative Research Award
  • Computer Science
  • Kharazmi University
  • Bioinformatics
  • Computational Research
  • Research Innovation

Introduction

Computer Science encompasses computational theory, algorithms, software systems, artificial intelligence, data analysis, information processing, and interdisciplinary computational methods. Contemporary research increasingly connects computer science with biological sciences, engineering, health, and other knowledge domains. Within this environment, researchers contribute by developing computational approaches capable of addressing complex analytical and practical problems.

Barati’s academic profile is associated with Kharazmi University and the Computer Science subject area. A publicly available researcher profile identifies her as holding an M.Sc. in Computer Science from Kharazmi University and describes participation in a bioinformatics research environment. [4]

Research Profile

The available evidence places Barati within an interdisciplinary computational research context. Bioinformatics is an area in which computer science techniques are applied to biological data, requiring knowledge of algorithms, data processing, computational modelling, and scientific interpretation. Such interdisciplinary work illustrates the role of computing methodologies in contemporary research environments. [4]

Her scholarly identity is further supported by an ORCID record and a Google Scholar author profile. These identifiers provide mechanisms for distinguishing researchers, connecting publications, and improving the discoverability of scholarly contributions. [2]

Research Contributions

The documented research record available for this profile is limited, and therefore specific contribution claims should be interpreted conservatively. A scholarly work indexed under the name Fatemeh Barati addresses integrated generation, transmission, and natural-gas network expansion planning, demonstrating the application of computational optimization and engineering analysis to complex infrastructure planning problems. The work describes a multi-period framework and computational methodology for large-scale systems. [5]

This type of research illustrates how computational methods can support decision-making in complex systems. The broader significance of such work lies in combining mathematical modelling, algorithmic techniques, and domain-specific knowledge to address practical research questions.

Publications

The supplied academic profile records 1 document. Because publication attribution should be based on verified researcher identifiers and bibliographic records, the available publication information should be considered alongside the researcher’s Google Scholar and ORCID profiles. [2]

Research Impact

The potential impact of computer science research is often measured not only through publication output but also through methodological usefulness, reproducibility, interdisciplinary application, and contribution to practical problem solving. Barati’s documented association with computational research provides a basis for considering her work within this broader framework. The combination of computer science training and interdisciplinary research activity is relevant to modern data-intensive and computationally supported scientific investigation.

Award Suitability

The Innovative Research Award is intended to recognize research demonstrating innovation, scholarly relevance, and potential contribution to a field. The International Academic Achievements & Awards program identifies innovation and research excellence among its recognition objectives. Barati’s academic association with Kharazmi University, Computer Science subject area, documented researcher identifiers, and available scholarly record provide relevant evidence for consideration within this recognition category.

Final assessment of award suitability should remain based on the complete nomination materials, publication evidence, research contributions, and supporting documentation reviewed by the appropriate award committee.

Conclusion

Fatemeh Barati is an academic researcher associated with Kharazmi University and the Computer Science field. Her available profile information indicates an interdisciplinary computational orientation, supported by Google Scholar and ORCID identifiers. The documented scholarly record provides a foundation for recognizing her engagement with computational research, while additional verified publications and research evidence can further establish the breadth and impact of her academic contributions. [2] [3]

References

  1. Google Scholar. (n.d.). Fatemeh Barati, author profile.
    https://scholar.google.com/citations?hl=en&user=QCQGhrgAAAAJ
  2. ORCID. (n.d.). Fatemeh Barati, ORCID record.
    https://orcid.org/0009-0005-2611-3016
  3. Rayazi. (n.d.). Fatemeh Barati — bioinformatics research group profile.
  4. Barati, F., Nateghi, A., Seifi, H., & Sepasian, M. S. (2013). Generation and transmission expansion planning with considering natural gas network. Iranian Conference on Electrical Engineering. DOI: 10.1109/IranianCEE.2013.6599577.
    https://doi.org/10.1109/IranianCEE.2013.6599577
  5. Barati, F., Seifi, H., Sepasian, M. S., Nateghi, A., & Catalão, J. P. S. (2014). Multi-Period Integrated Framework of Generation, Transmission, and Natural Gas Grid Expansion Planning for Large-Scale Systems. IEEE Transactions on Power Systems. DOI: 10.1109/TPWRS.2014.2365705.
    https://doi.org/10.1109/TPWRS.2014.2365705

Kashif Mazhar | Computer Science | Research Excellence Award

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Mr. Kashif Mazhar | Computer Science | Research Excellence Award

Mr. Kashif Mazhar | Computer Science | Research Scholar at Motilal Nehru National Institute of Technology Allahabad | India

Computer Science professional Mr. Kashif Mazhar is an accomplished Assistant Professor and Doctoral Researcher recognized for his strong academic foundation and impactful research in Artificial Intelligence and Data Science. Mr. Kashif Mazhar currently serves as an Assistant Professor in the School of Computer Science (Data Science Cluster) at the University of Petroleum and Energy Studies (UPES), Dehradun, while pursuing his Ph.D. at Motilal Nehru National Institute of Technology (MNNIT) Allahabad, where his doctoral research focuses on Explainable Artificial Intelligence (XAI) for brain tumor MRI classification and segmentation using advanced deep learning models integrated with LIME, SHAP, and Grad-CAM. Mr. Kashif Mazhar holds an M.Tech and B.Tech from the University of Allahabad and has over five years of combined teaching and research experience, including roles as Teaching Assistant at MNNIT Allahabad, Researcher at IIM Jammu, and Data Science Instructor at Simplilearn. His research interests span Explainable AI, Medical Imaging, Social Network Analysis, and AI-driven financial analytics, supported by strong research skills in Python, data analysis, supervision, and scientific reporting. Mr. Kashif Mazhar has published in high-impact Q1 journals and is UGC-NET qualified and GATE certified, reflecting his academic excellence and competitive merit. In conclusion, Mr. Kashif Mazhar exemplifies a forward-looking academic whose interdisciplinary expertise, teaching leadership, and commitment to trustworthy AI position him as a promising contributor to future advancements in Computer Science.

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Featured Publications

Model-agnostic explainable artificial intelligence methods in finance: a systematic review, recent developments, limitations, challenges and future directions
– Artificial Intelligence Review, 2025
Decoding the black box: LIME-assisted understanding of Convolutional Neural Network (CNN) in classification of social media tweets
– Social Network Analysis and Mining, 2024
A survey on methods for explainability in deep learning models
– International Conference on Machine Intelligence, Tools, and Applications, 2024

Harry Moongela | Computer Science | Young Scientist Award

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Dr. Harry Moongela | Computer Science | Young Scientist Award

Wits University, South Africa

Harry Moongela is a skilled IT professional with a strong background in Information Technology, including teaching, research, and development roles. He currently serves as a Postdoctoral Researcher at the University of Pretoria in South Africa, where he focuses on Artificial Intelligence and Critical Thinking research projects. Fluent in English and with basic knowledge of German, Harry has a rich academic and professional background that spans over a decade in various IT roles, ranging from academic positions to industry-specific consultancy.

Profile

Scopus

Education🎓

Harry holds a PhD in Information Technology from the University of Pretoria (2022), following a Master’s Degree in Information Systems from Rhodes University (2017). His undergraduate studies in Computer Science & Information Technology were completed at the University of Namibia in 2013. Additionally, Harry holds several certifications, including Cisco CCNA and a Certificate in Basic Telkom Network from Huawei University, providing him with a broad technical skill set.

Experience💼

Harry’s professional career began with roles such as a Web Developer and IT Technician. He has since advanced to academic roles, serving as a Lecturer, Course Coordinator, and Researcher at the University of Pretoria. He has also held various IT consultancy and development positions, including at Derivco Pty Ltd and Kanuga Auto Parts SA. Harry has extensive experience in IT teaching, course design, software development, and system administration.

Research Interests🔬

Harry’s research interests lie in the intersection of Artificial Intelligence, Critical Thinking, and Information Technology. His work includes publishing academic research in AI applications, computer networks, and the integration of innovative technologies in IT systems. His goal is to continue advancing research in AI to solve real-world problems and improve educational systems in IT.

Awards🏆

Harry has received multiple accolades throughout his academic journey, including being named Best IT Student at the University of Namibia (2010-2013), Best Postgraduate Student at Rhodes University (2017), and being a member of the prestigious Future Africa Futures Literacy Masterclass (2023). These awards reflect his dedication to excellence in both his studies and professional life.

Publications📚

Harry has contributed to various conference and journal publications in the field of Information Technology. Some of his notable works include research on AI in education, network security, and critical thinking in IT systems.
For detailed reading, please refer to the following articles:

A framework for using social media for organisational learning: An empirical study of South African companies”

  • Authors: Moongela, H., Hattingh, M.
  • Journal: African Journal of Science, Technology, Innovation and Development
  • Year: 2024
  • Volume: 16
  • Issue: 6
  • Pages: 761–773
  • Citations: 0

“Healthcare Supply Chain Efficacy as a Mechanism to Contain Pandemic Flare-Ups: A South Africa Case Study”

  • Authors: Maramba, G., Smuts, H., Hattingh, M., Mawela, T., Enakrire, R.
  • Journal: International Journal of Information Systems and Supply Chain Management
  • Year: 2023
  • Volume: 17
  • Issue: 1
  • Article ID: 333713
  • Citations: 3

“Perceptions of social media on students’ academic engagement in tertiary education”

  • Authors: Moongela, H., McNeill, J.
  • Conference: ACM International Conference Proceeding Series
  • Year: 2017
  • Part: F130806
  • Article ID: a23
  • Citations: 2

Conclusion🚀

Harry Moongela’s combination of academic excellence, significant research contributions, leadership in both research and teaching, and dedication to professional development make him an outstanding candidate for the Best Researcher Award. His wide-ranging expertise in information technology and commitment to advancing knowledge through research and teaching solidify his qualifications for this prestigious recognition.

Javed Rashid | Computer Science | Best Researcher Award

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Dr. Javed Rashid | Computer Science | Best Researcher Award 

Network Administrator | University of Okara | Pakistan

Research for Best Researcher Award

Strengths for the Award

Dr. Javed Rashid has demonstrated exceptional capabilities in both research and practical application, making him a strong candidate for the Best Researcher Award. His extensive experience as a Network Administrator and educator at reputable institutions like the University of Okara and University of Education showcases his ability to manage and innovate in complex technical environments. Dr. Rashid’s academic achievements, including a Ph.D. in Computer Science with a GPA of 3.58/4 from Islamic International University, underscore his deep knowledge and dedication to the field.

His research contributions are particularly noteworthy. Dr. Rashid’s publications cover a broad spectrum of computer science topics, from deep learning and computer vision to medical disease diagnosis. His work on deep learning models for potato leaf disease recognition and skin cancer detection highlights his expertise in leveraging cutting-edge technologies to address real-world problems. The diversity and impact of his research make him a standout in the field.

Areas for Improvement

While Dr. Rashid’s research portfolio is robust, there are areas where he could enhance his profile further. Interdisciplinary collaboration could be one avenue for growth, as integrating insights from other fields could lead to novel approaches and innovations. Expanding his international collaborations and partnerships might also help in gaining broader recognition and influence in global research circles.

Additionally, Dr. Rashid might consider engaging more actively in public science communication and outreach. By presenting his work at international conferences and participating in public forums, he could increase the visibility of his research and its applications. Fostering a stronger online presence through platforms like academic social networks or personal research blogs could also help in showcasing his contributions and engaging with a wider audience.

Short Bio

Dr. Javed Rashid is an accomplished scholar and professional with a diverse background in computer science and IT management. Currently serving as a Network Administrator at the University of Okara, he has extensive experience in both administrative and academic roles. Dr. Rashid is recognized for his significant contributions to research in computer vision, deep learning, and disease detection, demonstrating his commitment to advancing technology and its practical applications.

Profile

ORCID

Education

Dr. Rashid holds a Ph.D. in Computer Science from Islamic International University, Islamabad, where he achieved a commendable GPA of 3.58/4. He is also a gold medalist in both his MSCS/MPhil and MCS degrees from Superior University Lahore and Hajvery University, respectively. His academic journey includes a Bachelor of Laws from Punjab University and a Bachelor of Computer Sciences from Allama Iqbal Open University, reflecting his well-rounded educational background.

Experience

Dr. Rashid has a robust professional history, including roles as a Network Administrator, Deputy Registrar-IT, and Assistant Network Administrator at the University of Okara. His prior experience includes positions at the University of Education, Okara Campus, and Government Degree College Chichawatni. He has also contributed as a visiting lecturer and has extensive experience in both practical IT management and academic instruction.

Research Interest

Dr. Rashid’s research interests are centered on advanced topics in computer science, including computer vision, deep learning, and pattern recognition. His work explores applications in areas such as smart cities, medical disease diagnosing, and plant leaf diseases. He is particularly focused on leveraging deep learning techniques to enhance disease detection and classification systems.

Awards

Dr. Rashid has been recognized for his academic excellence and research contributions. Notable awards include gold medals for his MCS and MSCS degrees, acknowledging his outstanding academic performance. His research achievements continue to gain attention and impact in the field of computer science.

Publications

Rashid, J., Khan, I., Ali, G., Almotiri, S.H., AlGhamdi, M.A., Masood, K. “Multi-Level Deep Learning Model for Potato Leaf Disease Recognition,” Electronics, 2021, 10(17), 2064. Link
Cited by: 20

Rashid, J.; Ishfaq, M.; Ali, G.; Saeed, M.R.; Hussain, M; Alkhalifah, T.; Alturise, F.; Samnd N. “Skin Cancer Disease Detection Using Transfer Learning Technique,” Appl. Sci., 2022, 12, 5714. Link
Cited by: 35

Rashid, J., Khan, I., Ali, G., Rehman, S.U., Alkhalifah, T., Alturise, F. “Real-Time Multiple Guava Leaf Disease Detection from a Single Leaf Using Hybrid Deep Learning Technique,” Computers, Materials & Continua, 2023, 74(1), 1235-1257. Link
Cited by: 18

Sohail, M.; Ali, G.; Rashid, J.; Ahmad, I.; Almotiri, S.H.; AlGhamdi, M.A.; Nagra, A.A.; Masood, K. “Racial Identity-Aware Facial Expression Recognition Using Deep Convolutional Neural Networks,” Appl. Sci., 2022, 12, 88. Link
Cited by: 27

H. Chu, M. R. Saeed, J. Rashid, M. T. Mehmood, I. Ahmad et al. “Deep learning method to detect the road cracks and potholes for smart cities,” Computers, Materials & Continua, 75(1), 1863–1881, 2023. Link
Cited by: 22

Rehan Ahmad, Javaid Rashid, Suhail Iqbal, Khurshid Asghar “Evaluation of Multi-Channel Wireless Network Using Performance Metrics,” Journal of Basic and Applied Scientific Research., 4(8), 36-44, 2014. Link
Cited by: 10

Rashid, J., Khan, I., Abbasi, I., A.; Saeed M.R., Saddique, M., Abbas, M., A. “A Hybrid Deep Learning Approach to Classify the Plant Species,” Computers, Materials & Continua, 76 (3), 3897–3920, 2023. Link
Cited by: 19

Afzal, M., F.; Khan, I., Rashid, J.; Saddique, M., Gaber, H. “Binary Oriented Feature Selection with Crosstree Constraints for Valid Product Derivation in Software Product Line,” Computers, Materials & Continua, 76 (3), 3653–3670, 2023. Link
Cited by: 16

Conclusion

Dr. Javed Rashid is a distinguished researcher whose work has made significant contributions to the field of computer science, particularly in the areas of deep learning, computer vision, and disease diagnosis. His strengths lie in his extensive experience, impactful research, and academic achievements. By focusing on interdisciplinary collaborations, expanding international networks, and enhancing public engagement, Dr. Rashid could further elevate his profile and influence in the research community. For these reasons, he is a highly deserving candidate for the Best Researcher Award.