Awele Okolie | Computer Science | Excellence in Research Award

Ms. Awele Okolie | Computer Science | Excellence in Research Award

Wentworth Institute of Technology | United States

Ms. Awele Catherine Okolie is a data analyst and MSc Data Science candidate at Wentworth Institute of Technology with a strong foundation in Python, SQL, and data visualization. She has hands-on industry experience as a Data Analyst Intern at New Horizon, where she improved data accuracy, automated processes, and built real-time Power BI dashboards for business decision-making. Her work includes cleaning and analyzing large datasets, validating data during system migrations, and enhancing reporting reliability. Awele has led an end-to-end customer churn analysis project, analyzing over 7,000 telecom records and building an interactive dashboard to identify churn drivers. She also developed a Random Forest churn prediction model achieving 84% accuracy to support proactive customer retention. In addition, she has conducted customer segmentation and clustering analyses using EDA and K-Means to deliver actionable marketing insights. Her technical skill set spans Python, SQL, Excel, AWS, Snowflake, PostgreSQL, data modeling, and statistical analysis, supported by industry-recognized certifications.

Citation Metrics (Google Scholar)

26
20
15
5
0

Citations

26

h-index

4

i10-index

0

Citations

h-index

i10-index

View ResearchGate View Google Scholar Profile

Featured Publications


Heart disease prediction: A logistic regression approach

– Open Journal of Applied Sciences, 2025 (4 cites)

Dhulfiqar Zoltán Alwahab | Computer Science | Best Researcher Award

Dr. Dhulfiqar Zoltán Alwahab | Computer Science

Best Researcher Award | Obuda University | Hungary

Dr. Dhulfiqar Zoltán Alwahab is an accomplished researcher and academic professional with extensive expertise in cloud computing, Python programming, data science, DevOps, edge systems, and AI-assisted education. Currently serving as an Associate Professor at the John von Neumann Faculty of Informatics, Óbuda University, Budapest, he plays a significant role in curriculum development, supervision of MSc and PhD students, and contribution to international research projects and publications. His academic journey reflects a solid foundation in computer networks and engineering, holding a PhD in Informatics from Eötvös Loránd University, a Master’s degree in Computer Networks and Information from Al-Nahrain University, and a Bachelor’s degree in Computer Engineering from Mustansiriyah University. With progressive teaching experience from Assistant Lecturer to Associate Professor, he has consistently demonstrated academic leadership and research excellence. He is also a certified Cisco instructor with multiple credentials including CCNA, CCNP, DevNet Associate, CyberOps Associate, and Model Driven Programmability, which highlight his commitment to technological advancement and applied research. His professional focus extends to Linux systems, IoT, and modern operating systems, combining academic rigor with practical skill development. Over the years, Dr. Alwahab has made impactful contributions to higher education, international collaborations, and knowledge dissemination through conferences, workshops, and public platforms such as YouTube. His blend of advanced research expertise, international teaching experience, industry certifications, and leadership in innovative educational practices strongly position him as a suitable candidate for the Best Researcher Award. His work not only demonstrates technical depth but also reflects a clear commitment to fostering academic excellence, technological innovation, and future-oriented research in computing and informatics.


Featured Publications

Ali, T. E., Ali, F. I., Dakić, P., & Zoltan, A. D. (2025). Trends, prospects, challenges, and security in the healthcare Internet of Things. Computing, 107(1), 28.

Alwahab, D. A., & Laki, S. (2018). A simulation-based survey of active queue management algorithms. Proceedings of the 6th International Conference on Communications and Signal Processing.

Zaghar, D. (2013). Simplified the QoS factor for the ad-hoc network using fuzzy technique. International Journal of Communications, Network and System Sciences.

AlWahab, D. A., Gombos, G., & Laki, S. (2021). On a deep Q-network-based approach for active queue management. Joint European Conference on Networks and Communications & 6G Summit.

Eyvazov, F., Ali, T. E., Ali, F. I., & Zoltan, A. D. (2024). Beyond containers: orchestrating microservices with Minikube, Kubernetes, Docker, and Compose for seamless deployment and scalability. 11th International Conference on Reliability, Infocom Technologies and Optimization.

 

Computer Science

Introduction of Computer Science:

Computer Science research is the driving force behind the rapid evolution of technology and its profound impact on society. This field encompasses the study of algorithms, data structures, software development, and computational theory.

Artificial Intelligence (AI):

The study of creating intelligent agents and systems capable of tasks like natural language processing, image recognition, and decision-making, with applications in robotics, healthcare, and more.

Machine Learning:

Developing algorithms and models that enable computers to learn and make predictions from data, revolutionizing fields like data analysis, recommendation systems, and autonomous vehicles.

Cybersecurity:

Investigating methods to protect computer systems, networks, and data from cyber threats, including encryption, intrusion detection, and ethical hacking.

Human-Computer Interaction (HCI):

Exploring how humans interact with computers and designing user-friendly interfaces, including virtual reality, augmented reality, and usability studies.

Quantum Computing:

Pioneering the development of quantum algorithms and quantum computers that have the potential to solve problems beyond the reach of classical computers, from cryptography to materials science.