Zinah Saeed | Deep Learning | Best Researcher Award

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Ms. Zinah Saeed | Deep Learning | Best Researcher Award

Universiti Sains Malaysia | Iraq

Saeed ZR is a dedicated researcher and academic with a strong background in computer science, networking technology, and innovative applications of artificial intelligence, currently pursuing his doctoral studies in computer science at the School of Computer Sciences, Universiti Sains Malaysia, after completing a master’s degree in networking technology at Universiti Teknikal Malaysia Melaka and a bachelor’s degree in computer science at Mustansiriyah University in Baghdad, building his academic journey on a foundation of technical expertise and analytical thinking, his research interests cover metaheuristic algorithms, artificial intelligence, deep learning, gesture recognition, assistive technologies, human–computer interaction, and networking security, he has contributed to the academic community with impactful publications including a hybrid improved IRSO–CNN algorithm for accurate recognition of dynamic gestures in Malaysian sign language, a systematic review on systems-based sensory gloves for sign language pattern recognition, and research on improving cloud storage security using three layers of cryptography algorithms, his professional journey includes significant teaching experience as a lecturer at the Iraqi Police Academy where he worked to advance education and training, and his ongoing research and doctoral studies have strengthened his ability to design, implement, and test intelligent systems addressing real-world challenges, his technical skills encompass proficiency in computer software, Microsoft Office applications, and operating systems across Windows and Mac environments, alongside practical programming expertise in Python for scripting and data processing, he is also experienced with widely used research and software tools such as Jupyter, Colab, Git, SPSS, and basic MATLAB, beyond his professional life he nurtures a passion for reading, research, and continuous learning, qualities that support his growth as a thoughtful academic and innovative researcher, his multidisciplinary focus, combined with a strong commitment to impactful scientific contributions, reflects a future-oriented career in advancing artificial intelligence and human-centered technologies.

Profile: Google Scholar

Featured Publications:

Saeed, Z. R., Ibrahim, N. F., Zainol, Z. B., & Mohammed, K. K. (2025). A hybrid improved IRSO–CNN algorithm for accurate recognition of dynamic gestures in Malaysian sign language. Journal of Electrical and Computer Engineering, 2025(1), 6430675.

Saeed, Z. R., Zainol, Z. B., Zaidan, B. B., & Alamoodi, A. H. (2022). A systematic review on systems-based sensory gloves for sign language pattern recognition: An update from 2017 to 2022. IEEE Access, 10, 123358–123377.

Saeed, Z. R., Zakiah Ayop, N. A., & Baharon, M. R. (2018). Improved cloud storage security using three layers cryptography algorithms. International Journal of Computer Science and Information Security, 16(10), 11–18.

 

Abebaw Agegne | Deep Learning | Best Researcher Award

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Mr. Abebaw Agegne | Deep Learning | Best Researcher Award

Debark University | Ethiopia

Abebaw Agegne Engda is an Ethiopian scholar and academic who has devoted his professional career to the advancement of computer science education and research while fostering strong community engagement and service. He earned his Bachelor of Science degree in Computer Science from Debre Tabor University with high academic distinction, completing his studies with a focus on programming, systems, and applied computing. He later pursued a Master of Science degree in Computer Science at the University of Gondar, where he further deepened his knowledge of computational theory, advanced software systems, and the practical applications of computer science in solving real-world challenges. His academic excellence is demonstrated by his strong cumulative performance in both degrees, which reflect a commitment to rigor and perseverance. Professionally, he began his teaching journey as an Assistant Lecturer at Debark University, where he taught undergraduate computer science courses and contributed to shaping the foundational knowledge of young scholars. Later, he advanced to the position of Lecturer at Debark University, where he continues to teach computer science students across a variety of specializations, delivering core programming, system analysis, and applied computing courses while contributing to other departments with harmonized curriculum approaches. His students have consistently benefited from his structured teaching style, with many advancing to careers in high-level companies and industries, demonstrating the practical effectiveness of his teaching methodologies. He is capable of teaching a wide range of programming languages and has also been recognized for his leadership within his department, guiding academic processes, curriculum harmonization, and student development initiatives. His research works and community service contributions are documented and accessible through his ORCID profile, reflecting his engagement with both scholarly and societal responsibilities. Beyond academics, he is a person of discipline, patience, and strong work habits, qualities that enhance his ability to serve effectively in challenging environments and to maintain positive relationships with colleagues and students. He is fluent in Amharic and English, which allows him to engage in both local and international academic contexts, and his hobbies such as reading, traveling, counseling, and cultural exploration reflect a personality committed to lifelong learning, empathy, and service to others. Overall, his biography presents the portrait of a self-respecting, fair, and hardworking educator who combines academic achievement, teaching excellence, research contributions, and community service, making him a valuable asset in the advancement of computer science education in Ethiopia and beyond.

Profile: Orcid

Featured Publications:

Asnake, N. W., Ayalew, A. M., & Engda, A. A. (2025). Detection of oral squamous cell carcinoma cancer using AlexNet on histopathological images. Discover Applied Sciences.

Ayele, M. K., Baye, G. A., Yesuf, S. H., Engda, A. A., & Mitiku, E. T. (2025). Predicting stunting status among under five children in Ethiopia using ensemble machine learning algorithms. Scientific Reports.

Engda, A. A., Salau, A. O., & Ajala, O. (2025). Classical machine learning approaches for early hypertension risk prediction: A systematic review. Applied AI Letters.

Engda, A. A., Zewale, G. E., Mihret, B. G., & Adane, A. T. (2025). Developing pneumonia detection model using chest X-ray images: Deep learning approach. Preprint.

Engda, A. A. (2025). Detection of oral squamous cell carcinoma cancer using AlexNet on histopathological images. Conference paper.

Engda, A. A. (2025). Development of a case-based reasoning system for onion disease diagnosis and treatment. Proceedings of the IEEE International Conference on Emerging and Sustainable Technologies for Power and ICT in a Developing Society.

Mr. Oussama El Othmani | Data Science and Deep Learning | Excellence in Research

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Mr. Oussama El Othmani | Data Science and Deep Learning | Excellence in Research

Computer Engineering, Tunisia Polytechnic School, Tunisia

This individual is a promising researcher and software engineer with a strong background in computer science. Currently pursuing a PhD in ETIC at Tunisia Polytechnic School, University of Carthage La Marsa, they have a solid foundation in computer engineering from the Tunisian Military Academy. With experience as a software engineer at the Tunisian Ministry of National Defense, they have developed expertise in software development, collaboration, and problem-solving. Their research interests lie at the intersection of technology and innovation, with potential applications in various fields.

Profile

orcid

🎓 Education

– *PhD in ETIC*: Tunisia Polytechnic School, University of Carthage La Marsa, Tunis (2024 – Present)- *Computer Engineering*: Tunisian Military Academy, Fondik Jdid (2020-2023)- *Preparatory Mathematics-Physics*: Tunisian Military Academy, Fondik Jdid (2018-2020)- *Relevant Coursework*: Advanced Learning Algorithms, Artificial Intelligence, Computer Architecture, Database Management, Software Methodology, Project Management Fundamentals

👨‍🔬 Experience

– *Software Engineer*: Tunisian Ministry of National Defense (August 2023 – Present) – Participated in the full software development lifecycle – Collaborated with system engineers, hardware designers, and integration/test engineers – Developed optimized code for specific hardware platforms – Applied Agile development methodologies and object-oriented architectures

🔍 Research Interest

The individual’s research focus is not explicitly stated, but based on their education and experience, they may be interested in exploring topics related to artificial intelligence, computer architecture, and software methodology. Potential research areas could include machine learning, data science, and software engineering.

Awards and Honors🏆

No information is available on awards and honors received by the individual.

📚 Publications 

Rough Set Theory and Soft Computing Methods for Building Explainable and Interpretable AI/ML Models

Développement d’un système de détection des anomalies des cellules sanguines et son utilisation en télémédecine

BloodScan

Conclusion

The candidate shows promise for the Best Researcher Award with their relevant education, professional experience, and technical skills. However, additional research experience, interdisciplinary knowledge, and a stronger publication record would significantly enhance their application. With focused effort in these areas, the candidate could become a strong contender for the award.

Hambisa Bedassa | Artificial Insemination | Best Researcher Award

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Mr. Hambisa Bedassa | Artificial Insemination | Best Researcher Award

Researcher at Ethiopian Institute of Agricultural Research, Ethiopia

Abdi Bedassa is a dedicated professional in the fields of veterinary science, animal health, and food safety, with a strong focus on enhancing the quality and safety of dairy products in Ethiopia. Fluent in Afan Oromo, he combines technical expertise with leadership, adaptability, and strategic planning to address critical challenges in agriculture and public health. With extensive experience in project management and a passion for collaborative problem-solving, Abdi is committed to driving impactful changes in Ethiopia’s agricultural sector.

Publication Profile

orcid

Education 🎓

BSc in Veterinary Science from Addis Ababa University (2012).MSc in Animal Health and Food Safety from Haramaya University (2015).PhD in Veterinary Public Health from Hawassa University (2022).

Experience  💼

Researcher in food safety and dairy value chain improvements (2018–2022).Project leader addressing milk contamination and quality control in Ethiopia.Extensive collaboration with farmers, processors, and stakeholders.

Awards and Honors 🏅

“Excellence in Dairy Safety Research” award (2021).Recognized for exceptional contributions to Ethiopian agricultural development.

Research Focus 🔬

Dairy safety and quality assurance.Comparative ovarian follicular dynamics in cattle breeds.Prevalence of Salmonella enterica in milk and cottage cheese.

Publications 📖

Enhancing Bovine Reproduction (2025): DOI: 10.1111/rda.70003.

Seasonal Variation of Salmonella in Dairy Products (2024): DOI: 10.1186/s40550-024-00108-4.

Risk Factors for Salmonella in Dairy Products (2023): DOI: 10.1186/s40550-023-00101-3.

Conclusion

Abdi Bedassa is a highly capable and dedicated researcher with a proven track record in addressing critical challenges in dairy safety, livestock reproduction, and biotechnology. His commitment to excellence, combined with practical experience and leadership skills, positions him as a strong candidate for the Best Researcher Award. By building international collaborations, enhancing methodological expertise, and broadening research scope, Abdi can further strengthen his candidacy and make an even greater impact on the scientific community.

 

Dr. Talent Diotrefe Banda | Artificial Neural Networks | Best Researcher Award

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Dr. Talent Diotrefe Banda | Artificial Neural Networks | Best Researcher Award

Dr. Talent Diotrefe Banda, ZAKUMI Consulting Engineers, South Africa

Talent Diotrefe Banda is a highly accomplished civil engineer with over 20 years of experience, specializing in water science, AI, ANNs, and WQIs. He holds numerous qualifications, including a PhD in Engineering from the University of KwaZulu-Natal, an MBA from the University of Cape Town, and multiple degrees from the Tshwane University of Technology and Bulawayo Polytechnic. As the CEO of ZAKUMI Consulting Engineers, Talent has a robust professional background with memberships in ECSA, SAICE, SABTACO, WISA, and ZIE. He has received multiple academic and business excellence awards and has published extensively in peer-reviewed journals.

Professional Profiles:

Google Scholar

QUALIFICATIONS 🎓

Master of Business Administration (MBA) – University of Cape Town, South Africa (2022)Doctor of Philosophy in Engineering (Civil) – University of KwaZulu Natal, South Africa (2020)Master of Technology Degree in Engineering: Civil – Tshwane University of Technology, South Africa (2015)Bachelor of Technology Degree in Engineering: Civil – Tshwane University of Technology, South Africa (2011)National Diploma in Civil Engineering – Bulawayo Polytechnic, Zimbabwe (2003)National Certificate in Civil Engineering – Bulawayo Polytechnic, Zimbabwe (2001)

Talent Diotrefe Banda: Chief Executive Officer (Civil Engineer) 🌟

Employer: ZAKUMI Consulting Engineers (Pty) LtdName of Staff: Talent Diotrefe BANDADate of Birth: 19th of October 1982National Identity Number: 821019 5989 188Nationality: Zimbabwean with South African Permanent Residence PermitExperience: Twenty (20) yearsArea of Specialisation: Civil Engineering, Water Scientist, Artificial Intelligence (AI), Artificial Neural Networks (ANNs), Water Quality Indices (WQIs), Research Scientist

PROFESSIONAL MEMBERSHIP 🏆

Professional Engineering Technician (Pr. Techni Eng) – Engineering Council of South Africa (ECSA)Registration Number: 201030123 from 06th of July 2010Member (MSAICE) – South Africa Institution of Civil Engineering (SAICE)Registration Number: 207890 from 06th of December 2007 (Changed from Associate Member on the 14th of December 2015)Member (MSABTACO) – South African Black Technical & Allied Careers Organization (SABTACO)Registration Number: LIMP/0095I from 22nd of October 2007Member (MWISA) – Water Institute of Southern Africa (WISA)Registration Number: 25927 from 23rd of June 2014Graduate Technician (GradTZweIE) – Zimbabwe Institution of Engineers (ZIE)Registration Number: ZIE073967 from 30th of April 2007Competent Person (Competent Engineer) – National Home Builders Registration Council (NHBRC)Registration Number: 3000166150 from 01st of June 2016

PROFILE & KEY EXPERIENCE 📈

A multi-award-winning Civil Engineer with several university qualifications, including a Doctor of Philosophy in Engineering (Civil) from the University of KwaZulu-Natal, a Master of Technology in Engineering (Civil), and a Bachelor of Technology in Engineering (Civil) from the Tshwane University of Technology where he obtained an award for the Outstanding Research: Young Water Scientist of 2012 with WaterNet/WARFSA/GWP – SA for his paper entitled “Analysis of the gazetted pricing strategy for raw water use charges in South Africa”. Furthermore, Talent holds a National Diploma in Engineering (Civil) and a National Certificate in Engineering (Civil) from Bulawayo Polytechnic, where he received three academic awards. Dr. Banda is registered as a Professional Engineering Technician (Pr. Techni. Eng) with the Engineering Council of South Africa, where he is a serving member of the Registration Committee of Professional Engineering Technicians. He gained more than twenty (20) years of experience working on Civil Engineering Projects responsible for water and wastewater designs, roads and stormwater drainage, contract and tender documentation, project implementation, and management.Additionally, Talent has a Master of Business Administration (MBA) from the University of Cape Town, Graduate School of Business (GSB) in South Africa, where he obtained an academic award as the Best Student for the Economics for Business Module. Dr. Talent Banda has ten academic and business excellence awards from institutions of higher learning and corporate organizations in Zimbabwe and South Africa. Additionally, Talent has ten publications, including peer-reviewed journal articles, conference papers, master’s dissertations, and doctoral thesis. Dr. Banda serves as Peer Reviewer and Editor in three Academic Journals. Lastly, Talent holds key positions in various working groups, committees, and management boards. 

✍️Publications Top Note :

Development of Water Quality Indices (WQIs): A Review 🌊📊

Authors: TD Banda, MV Kumarasamy Journal: Polish Journal of Environmental Studies Volume: 29 (3) Citations: 74 Year: 2020

Application of Multivariate Statistical Analysis in the Development of a Surrogate Water Quality Index (WQI) for South African Watersheds 🏞️🔬

Authors: TD Banda, M Kumarasamy Journal: Water Volume: 12 (6), 1584 Citations: 62 Year: 2020

Development of a Universal Water Quality Index (UWQI) for South African River Catchments 🌍💧

Authors: TD Banda, M Kumarasamy Journal: Water Volume: 12 (6), 1534 Citations: 34 Year: 2020

A Review of the Existing Water Quality Indices (WQIs) 📚📈

Authors: TD Banda, M Kumarasamy Journal: Pollution Research Volume: 39 (2), 489-514 Citations: 23 Year: 2020

Developing an Equitable Raw Water Pricing Model: The Vaal Case Study 💰💦

Author: TD Banda Institution: Tshwane University of Technology Citations: 11 Year: 2015

Aggregation Techniques Applied in Water Quality Indices (WQIs) 🔄🌐

Authors: TD Banda, M Kumarasamy Journal: Pollution Research Volume: 39 (2), 400-412 Citations: 8 Year: 2020

Development of a Universal Water Quality Index and Water Quality Variability Model for South African River Catchments 🌊🧪

Author: TD Banda Year: 2020

Artificial Neural Network (ANN)-Based Water Quality Index (WQI) for Assessing Spatiotemporal Trends in Surface Water Quality—A Case Study of South African River Basins 🤖🌍

Authors: TD Banda, M Kumarasamy Journal: Water Volume: 16 (11), 1485 Year: 2024

Dr. Katarina Djordjevic | Artificial Intelligence | Best Researcher Award

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Dr. Katarina Djordjevic | Artificial Intelligence | Best Researcher Award

Dr. Katarina Djordjevic, University of Belgrade, Serbia

Dr. Katarina Đorđević holds a PhD in Physics and is an expert in the physics of condensed matter and photoacoustics. She has significant experience in applying neural networks for material characterization, supervised machine learning, and solving inverse problems. Dr. Đorđević is skilled in numerical testing and developing measurement procedures, as well as utilizing computational intelligence algorithms in various applications. Her work involves a blend of theoretical and practical approaches, leveraging advanced computational techniques to enhance understanding and innovation in material sciences.

 

Professional Profiles:

Google Scholar

Intelligence 🚀

Dr. Katarina Đorđević, PhD in Physics, is a renowned expert with extensive experience in the physics of condensed matter, photoacoustics, and the application of neural networks in material characterization. Her diverse expertise spans multiple cutting-edge fields, making her a leading figure in both theoretical and applied physics.

🌟 Physics of Condensed Matter:

Dr. Đorđević’s work in condensed matter physics delves into the intricate properties of matter in various states, contributing to a deeper understanding of material behavior under different conditions.

🔊 Photoacoustics:

She is well-versed in photoacoustics, a technique that combines light and sound to probe the properties of materials. This innovative approach allows for non-invasive, highly precise material characterization.

🤖 Neural Networks & Material Characterization:

Leveraging neural networks, Dr. Đorđević has advanced the field of material characterization. Her research utilizes these artificial intelligence systems to analyze and predict material properties with unprecedented accuracy.

💻 Supervised Machine Learning:

A significant portion of her work involves supervised machine learning, where she trains models to recognize patterns and make predictions based on extensive datasets. This has vast applications in materials science and beyond.

🔄 Inverse Problem Solving:

Dr. Đorđević excels in solving inverse problems, which involve determining unknown causes from known consequences. This is crucial in many scientific and engineering disciplines, where direct measurement is challenging or impossible.

🔢 Numerical Testing & Measurement Procedures:

Her expertise extends to numerical testing and developing precise measurement procedures, ensuring accuracy and reliability in experimental physics.

🧠 Computational Intelligence Algorithms:

She applies advanced computational intelligence algorithms to tackle complex problems in physics and material science, driving innovation and efficiency in her research.Dr. Katarina Đorđević’s multidisciplinary approach and profound knowledge make her a standout scientist, continually pushing the boundaries of what is possible in physics and computational intelligence. 🌍🔬✨

📖 Publications Top Note :

1. Photoacoustic Measurements of the Thermal and Elastic Properties of n-type Silicon Using Neural Networks

Authors: КL Djordjević, DD Markushev, ŽМ Ćojbašić, KL Djordjević
Journal: Silicon 12 (6), 1289-1300, 2020
Citations: 21

2. Computationally Intelligent Description of a Photoacoustic Detector

Authors: MI Jordovic-Pavlovic, AD Kupusinac, KL Djordjevic, SP Galovic, …
Journal: Optical and Quantum Electronics 52, 1-14, 2020
Citations: 19

3. Development and Comparison of Techniques for Solving the Inverse Problem in Photoacoustic Characterization of Semiconductors

Authors: M Nesic, M Popovic, K Djordjevic, V Miletic, M Jordovic-Pavlovic, …
Journal: Optical and Quantum Electronics 53, 1-16, 2021
Citations: 17

4. Photoacoustic Optical Semiconductor Characterization Based on Machine Learning and Reverse-Back Procedure

Authors: КL Djordjevic, SP Galovic, MI Jordovic-Pavlovic, MV Nesic, MN Popovic, …
Journal: Optical and Quantum Electronics 52, 1-9, 2020
Citations: 16

5. Influence of Data Scaling and Normalization on Overall Neural Network Performances in Photoacoustics

Authors: КLj Djordjević, MI Jordović-Pavlović, ŽM Ćojbašić, SP Galović, MN Popović …
Journal: Optical and Quantum Electronics 54 (501), 31-35, 2022
Citations: 14*

6. Photothermal Response of Polymeric Materials Including Complex Heat Capacity

Authors: KL Djordjevic, D Milicevic, SP Galovic, E Suljovrujic, SK Jacimovski, …
Journal: International Journal of Thermophysics 43 (5), 68, 2022
Citations: 14

7. Estimation of Linear Expansion Coefficient and Thermal Diffusivity by Photoacoustic Numerical Self-Consistent Procedure

Authors: MV Nesic, MN Popovic, SP Galovic, KL Djordjevic, MI Jordovic-Pavlovic, …
Journal: Journal of Applied Physics 131 (10), 2022
Citations: 13

8. Sintering of Fly Ash Based Composites with Zeolite and Bentonite Addition for Application in Construction Materials

Authors: A Terzić, N Đorđević, M Mitrić, S Marković, K Đorđević, VB Pavlović
Journal: Science of Sintering 49 (1), 23-37, 2017
Citations: 13

9. Inverse Problem Solving in Semiconductor Photoacoustics by Neural Networks

Authors: KL Djordjevic, DD Markushev, ŽM Ćojbašić, SP Galović
Journal: Inverse Problems in Science and Engineering 29 (2), 248-262, 2021
Citations: 11

10. Use Neural Network in Photoacoustic Measurement of Thermoelastic Properties of Aluminum Foil

Authors: К Lj Djordjević, SP Galović, MN Popović, MV Nešić, IP Stanimirović, ZI …
Journal: Measurement, 111537, 2022
Citations: 10