Prince Yaw Owusu Amoako | Artificial Intelligence | Best Researcher Award

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Dr. Prince Yaw Owusu Amoako | Artificial Intelligence | Best Researcher Award

PhD Student at Nanjing University of Science and Technology, China.

Dr. Prince Yaw Owusu Amoako is a distinguished researcher and academician known for his contributions to [specific field]. With a strong passion for innovation and knowledge dissemination, he has made significant strides in advancing research and education. His work has influenced both theoretical and practical applications, shaping new paradigms in his field. As an accomplished scholar, he has authored numerous publications in high-impact journals and has presented at international conferences. His dedication to research excellence and mentorship has earned him a reputable standing among peers and students alike.

Professional Profile

Education

Dr. Amoako holds a [Doctorate/Master’s/Bachelor’s degree] in [Field] from [University Name], where he specialized in [specific research area]. His academic journey has been marked by a commitment to excellence, having received various scholarships and academic accolades. During his postgraduate studies, he conducted groundbreaking research on [topic], which laid the foundation for his future contributions. His multidisciplinary education has equipped him with a holistic understanding of [field], fostering a comprehensive approach to solving complex challenges.

Professional Experience

With extensive experience in academia and industry, Dr. Amoako has held pivotal roles in research, teaching, and professional practice. He has served as a [Position] at [Institution/Organization], where he played a crucial role in curriculum development, research supervision, and academic leadership. Beyond academia, he has collaborated with industry leaders on innovative projects, bridging the gap between theoretical research and real-world applications. His professional journey reflects a deep commitment to fostering knowledge and technological advancements.

Research Interest

Dr. Amoako’s research interests encompass a wide range of topics, including [specific areas such as Artificial Intelligence, Biomedical Research, Structural Engineering, etc.]. He is particularly focused on addressing contemporary challenges through innovative methodologies and interdisciplinary collaboration. His research aims to push the boundaries of knowledge, providing impactful solutions to industry and society. His passion for inquiry-driven discovery continues to inspire new research directions.

Research Skills

Equipped with a robust skill set, Dr. Amoako is proficient in various research methodologies, statistical analyses, and advanced technological tools. His expertise includes data analytics, machine learning, experimental design, and scientific writing. He is adept at utilizing cutting-edge software and laboratory techniques, ensuring precision and reliability in his research findings. His methodological rigor and analytical acumen have contributed to numerous successful projects.

Awards and Honors

Dr. Amoako has been recognized with multiple prestigious awards for his contributions to research and academia. These accolades include [list specific awards, fellowships, grants, or honorary recognitions]. His outstanding achievements have been celebrated by renowned institutions and professional organizations, reflecting his excellence and leadership in the field. His recognitions serve as a testament to his relentless pursuit of academic and research excellence.

Conclusion

In conclusion, Dr. Prince Yaw Owusu Amoako stands as a beacon of academic and research excellence. His dedication to advancing knowledge, mentoring young researchers, and contributing to real-world solutions highlights his impact on both academia and industry. His journey is a testament to perseverance, innovation, and scholarly commitment. Moving forward, he continues to strive for excellence, leaving a lasting legacy in his field. His work not only enriches the academic community but also contributes to global advancements, making him a distinguished figure in research and education.

Publication Top Notes

  • Causes of Failure of Students in Computer Programming Courses: The Teacher–Learner Perspective
    Authors: KAM Sarpong, JK Arthur, PYO Amoako
    Journal: International Journal of Computer Applications 77
    Year: 2013
    Citations: 113
  • Performance of students in computer programming: Background, field of study and learning approach paradigm
    Authors: PYO Amoako, KA Sarpong, JK Arthur, C Adjetey
    Journal: International Journal of Computer Applications 77 (12)
    Year: 2013
    Citations: 19
  • Dual sparse representation graph-based copropagation for semisupervised hyperspectral image classification
    Authors: Y Zhang, G Cao, B Wang, X Li, PYO Amoako, A Shafique
    Journal: IEEE Transactions on Geoscience and Remote Sensing 60
    Year: 2021
    Citations: 12
  • Emerging bimodal biometrics authentication for non-venue-based assessments in open distance e-learning (OdeL) environments
    Authors: PYO Amoako, IO Osunmakinde
    Journal: International Journal of Technology Enhanced Learning 12 (2)
    Year: 2020
    Citations: 9
  • Adoption of mobile payment systems in Ghana
    Authors: WO Larkotey, PY Amoako, EA Laryea, E Dey
    Journal: International Journal of Societal Applications of Computer Science 2 (4)
    Year: 2013
    Citations: 5
  • ChatGPT Implementation in the Metaverse: Towards Another Level of Immersiveness in Education
    Authors: M Adarkwah, A Tlili, B Shehata, R Huang, PYO Amoako, H Wang
    Journal: Applications of Generative AI
    Year: 2024
    Citations: 4
  • Smart teaching versus hard teaching: Insights from instructors from old and new classrooms in Ghana
    Authors: MA Adarkwah, J Odame, R Huang, H Wang, PYO Amoako
    Journal: E-Learning and Digital Media
    Year: 2024
    Citations: 3
  • An Image-Based Cocoa Diseases Classification Based on an Improved Vgg19 Model
    Authors: PYO Amoako, G Cao, JK Arthur
    Journal: Applied Research Conference in Africa
    Year: 2022
    Citations: 3
  • A Meta-reinforcement Learning based Hyperspectral Image Classification with Small Sample Set
    Authors: PYO Amoako, G Cao, D Yang, L Amoah, Y Wang, Q Yu
    Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
    Year: 2023
    Citations: 2
  • The Topology of Virtual Learning Environment Technologies in Institutions of Higher Learning in Ghana
    Authors: S Hatsu, PYO Amoako, MU Mabeifam
    Journal: International Journal of Computer Applications 93 (19)
    Year: 2014
    Citations: 1

 

 

Masoumeh Alinia | Artificial Intelligence | Best Researcher Award

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Ms Masoumeh Alinia |Artificial Intelligence | Best Researcher Award 🏆

student at Alzahra university,  Iran🎓

Masoumeh Alinia is a talented and driven professional with a dual background in Software and Electronic Engineering. With a focus on data science and deep learning, she has contributed to innovative projects across various sectors. Her expertise lies in recommender systems, machine learning models, and big data analysis. Passionate about technology and education, Masoumeh has experience teaching and mentoring students, while also pursuing impactful research in advanced machine learning techniques and IoT systems. Fluent in both Persian and English, she thrives on solving complex problems and continuously improving her technical and soft skills. 

Professional Profile 

Education

Masoumeh earned her Master of Science in Software Engineering from Alzahra University, Tehran, in 2024 with an impressive GPA of 18.57/20. Her thesis focused on collaborative filtering recommender systems using deep learning, supervised by Dr. Hasheminejad. She also holds an M.Sc. in Electronic Engineering from Shahid Beheshti University, where her thesis explored nanoscale spintronic technology for three-valued memory. She completed her Bachelor’s in Electronic Engineering from Technical and Vocational University with a GPA of 18.87/20. Throughout her academic journey, she excelled in both practical and theoretical fields.

Work Experience

Masoumeh worked as a Data Scientist at Afarinesh, a knowledge-based IT firm, from February to July 2023. There, she developed deep learning-based recommender systems using TensorFlow and designed various models like Neural Collaborative Filtering (CF), SVD, and NMF. She also managed relational databases, processed large datasets, and conducted A/B tests for performance evaluation. Masoumeh played a key role in enhancing data-driven decision-making processes within the company’s ecosystem of startups, contributing to projects like Sayeh platform and Boxel. Her experience spans technical model development and business-focused data analysis.

Skills & Competencies

Masoumeh is proficient in Machine Learning, Data Visualization, Database Management, and Model Deployment. She is skilled in programming languages such as Python, C#, C, VHDL, and Verilog, and works comfortably with frameworks like TensorFlow, PyTorch, Scikit-learn, and Keras. Her key soft skills include Critical Thinking, Adaptability, and a strong Openness to Feedback. She has consistently demonstrated her ability to learn new technologies quickly, solve complex problems, and contribute to collaborative environments.

Awards & Honors

Masoumeh has contributed to major international conferences, presenting papers on advanced topics in deep learning and recommender systems. Her research, co-authored with Dr. Hasheminejad, was presented at the 13th International Conference on Computer and Knowledge Engineering, focusing on link prediction for recommendation systems. She also co-authored another paper on location-based deep collaborative filtering for IoT service quality prediction, which was presented at the 7th International IoT Conference. These recognitions highlight her innovative contributions to both academia and industry.

Membership & Affiliations

Throughout her academic and professional journey, Masoumeh has actively participated in research and technical communities. Her involvement in collaborative research groups led to valuable insights in areas such as deep learning, IoT, and complex dynamical networks. While no specific memberships are listed, her participation in international conferences and collaborations with academic advisors and peers indicates strong engagement with the scientific and technical community. Her work is grounded in research excellence and practical application.

Teaching Experience

Masoumeh has shared her knowledge by teaching various technical courses. She served as an instructor at Atrak Institute of Higher Education, where she taught electronics courses and microcontroller/microprocessor labs using tools like Proteus and Atmel Studio. She also worked as a teaching assistant for Electric Circuits and Logic Circuit courses under Dr. Ramin Rajaee at Shahid Beheshti University. Her passion for teaching has allowed her to guide and mentor students in understanding complex concepts, fostering a collaborative learning environment.

Research Focus

Masoumeh’s research centers on recommender systems, deep learning, and IoT technologies. Her thesis explored collaborative filtering using deep learning techniques, aiming to enhance recommendation accuracy. She has also worked on link prediction for recommender systems, leveraging machine learning algorithms such as GCN-GNNs for better user experience. Additionally, her research extends to Quality-of-Service predictions in IoT through location-based collaborative filtering, pushing the boundaries of how personalized recommendations and service quality can be optimized in data-driven environments.

📖Publications : 

  • Link Prediction for Recommendation based on Complex Representation of Items Similarities
    📅 2023 | 📰 13th International Conference on Computer and Knowledge Engineering (ICCKE)
    👩‍💻 Masoumeh Alinia
    🔗 DOI: 10.1109/ICCKE60553.2023.10326315
  • Location-Based Deep Collaborative Filtering for Quality of Service Prediction in IoT
    📅 2023 | 📰 7th International Conference on Internet of Things and Applications (IoT)
    👨‍💻 Author unspecified
    🔗 DOI: 10.1109/IoT60973.2023.10365357

Cicil Denny | AI and Machine Learning | Best Researcher Award |

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Mr Cicil Denny | AI and Machine Learning |  Best Researcher Award

Student/Member at Vellore Institute of Technology, Chennai ,India

🌟 Cicil Melbin Denny J is a versatile Data Analyst with a strong background in Artificial Intelligence, Machine Learning, and Software Engineering. With hands-on experience in programming languages like Python, Java, C++, and JavaScript, and advanced skills in AI, ML, and Deep Learning frameworks such as PyTorch and TensorFlow, Cicil excels in tackling complex data problems. Notably, he led a research project on Semantic Segmentation for Underwater Imagery (SUIM), achieving an impressive mIoU of 84.83%, which was published in the prestigious “Results in Engineering” journal. Cicil’s technical prowess extends to data analytics tools like MySQL and NoSQL, and he is adept at using PowerBI and Tableau for business insights. His proficiency in network administration, cloud services (AWS, Azure, Google Cloud), and cybersecurity underlines his comprehensive skill set. Recognized for his problem-solving attitude and effective communication skills, Cicil is well-equipped to contribute to product analysis and support, making him a valuable asset in any tech-driven environment. 📊💡🤖

professional profile:

📚 Education:

  • B.Tech in CSE with specialization in Artificial Intelligence and Machine Learning, CGPA: 8.25 (Completed 6 Semesters)
  • Higher Education (2019-20): Mathematics, Biology, CGPA: 8.38

💼 Work Experience:

  • Research Internship at Vellore Institute of Technology, Chennai (May 2023 – July 2023)
  • Worked on Semantic Segmentation for Underwater Imagery (SUIM) using Swin Transformer, ConvMixer, and UNet architectures. Achieved mIoU metrics of 84.83% and published in “Results in Engineering” Journal – 2024 by Elsevier.

🔍 Skills:

  • Programming Languages: Python, Java, C++, C, JavaScript, PHP
  • Data Analytics: MySQL, NoSQL, PowerBI, Tableau
  • AI & ML: PyTorch, TensorFlow, Machine Learning, Deep Learning, Computer Vision
  • Software Engineering: DevOps, Software Design and Debugging, Test Development
  • Networking: TCP/IP, DNS, DHCP, VLANs, VPNs, Firewalls
  • Virtualization & Cloud: VMware, VirtualBox, AWS, Azure, Google Cloud
  • Other Tools: Jupyter Notebook, MATLAB, LTspice, CISCO, Unity Engine, MS Excel

🏆 Certifications:

  • TensorFlow Developer Certificate (2023: Zero to Mastery)
  • Deep Learning A-Z™ 2023: Neural Networks, AI & ChatGPT Bonus
  • Artificial Intelligence Analyst – IBM
  • Introduction to Artificial Intelligence – LinkedIn Learning
  • Artificial Intelligence – Verzeo
  • Introduction to Financial Modeling
  • Digital Marketing Fundamentals with Live Projects
  • The A-Z Digital Marketing Course

🔬 Research Focus:

  • 🔬 Cicil Melbin Denny J’s research focuses on cutting-edge technologies in AI and Machine Learning. He has extensively worked on Semantic Segmentation for Underwater Imagery using advanced architectures like Swin Transformer, ConvMixer, and UNet, achieving high accuracy. His work on IoT botnet detection leverages autoencoders, LSTM-CNN, and DNN to enhance cybersecurity. Additionally, he explores route mapping algorithms, blockchain technology, and cryptocurrency trends. Cicil’s dedication to innovation is evident through his projects on malware detection using ML algorithms and IoT-based accident intimation systems, aiming to improve safety and security in various domains. 🌊🤖🔒🌐

👩‍🏫 Teaching & Knowledge Sharing:

  • Advanced skills in AI, ML, Deep Learning, and Computer Vision with hands-on experience.
  • Prepared detailed reports and suggested improvements on QA patterns for Amazon Warehouses.

 

publications🌟