Assistant Professor at Addis Ababa Science and Technology University, Ethiopia📖
Tesfay Gidey Hailu is a highly skilled Data Scientist and Information and Communication Engineer with a strong background in computer science, machine learning, signal processing, and public health data analysis. With a Ph.D. in Information and Communication Engineering from the University of Electronic Science and Technology of China, Tesfay is proficient in programming languages like Python, Java, C++, and SQL, and has extensive experience in applying machine learning, data mining, and optimization techniques to solve real-world problems. His expertise spans indoor localization, transfer learning, and epidemiological data modeling, positioning him as a leader in technology-driven research and project management.
Profile
Scopus Profile
Orcid Profile
Google Scholar Profile
Education Background🎓
- Ph.D. in Information and Communication Engineering, University of Electronic Science and Technology of China, 2023
- MSc in Software Engineering, HILCOE School of Computer Science and IT, 2018
- MSc in Health Informatics and Biostatistics, College of Health Sciences, Mekelle University, 2013
- BSc in Statistics with a Minor in Computer Science, Addis Ababa University, 2006
Professional Experience🌱
Tesfay has held several academic leadership roles, including Associate Dean at Addis Ababa Science and Technology University (AASTU), where he oversaw research initiatives and technology transfer. He also served as the Head of Department at Jimma University, where he led curriculum development, research, and faculty management. Throughout his career, Tesfay has contributed to driving quality improvements in manufacturing industries and has successfully managed cross-functional teams and student programs, fostering academic excellence and industry collaboration.
Tesfay’s research primarily focuses on signal processing, indoor localization, machine learning, data fusion, and transfer learning. He also specializes in epidemiological data modeling, quality control in manufacturing industries, and predictive modeling. His work aims to leverage advanced algorithms to drive actionable insights in fields like healthcare and industrial applications.
Author Metrics
Publications Top Notes 📄
1. Comparing Data Mining Techniques in HIV Testing Prediction
- Authors: TG Hailu
- Journal: Intelligent Information Management
- Volume & Issue: 7 (3), 153-180
- Year: 2015
- Citations: 24
- Summary: This paper compares various data mining techniques used for predicting HIV testing outcomes, focusing on the effectiveness and accuracy of the models. It explores different algorithms and methodologies used in health data analytics to predict HIV testing and suggests the most appropriate techniques based on the dataset used.
2. Assessing the Awareness and Usage of Quality Control Tools with Emphasis to Statistical Process Control (SPC) in Ethiopian Manufacturing Industries
- Authors: L Berhe, T Gidey
- Journal: Intelligent Information Management
- Volume & Issue: 8 (06), 143
- Year: 2016
- Citations: 17
- Summary: This paper examines the level of awareness and usage of quality control tools, particularly Statistical Process Control (SPC), within Ethiopian manufacturing industries. It provides an in-depth analysis of the impact of SPC on improving product quality and manufacturing efficiency, with an emphasis on the challenges faced in the local context.
3. Determinants and Cross-Regional Variations of Contraceptive Prevalence Rate in Ethiopia: A Multilevel Modeling Approach
- Authors: TG Hailu
- Journal: American Journal of Mathematical and Statistical Sciences (Am J Math Stat)
- Volume & Issue: 5 (3), 95-110
- Year: 2015
- Citations: 16
- Summary: This paper employs multilevel modeling to analyze the determinants of contraceptive prevalence rates in Ethiopia. It explores variations in contraceptive use across different regions and socio-economic factors, providing insights for policymakers in improving family planning initiatives.
4. Data Fusion Methods for Indoor Positioning Systems Based on Channel State Information Fingerprinting
- Authors: HT Gidey, X Guo, K Zhong, L Li, Y Zhang
- Journal: Sensors
- Volume & Issue: 22 (22), 8720
- Year: 2022
- Citations: 5
- Summary: This research investigates the application of data fusion methods for improving the accuracy of indoor positioning systems. The authors focus on utilizing channel state information fingerprinting to enhance the reliability and performance of these systems in real-world scenarios.
5. Heterogeneous Transfer Learning for Wi-Fi Indoor Positioning Based Hybrid Feature Selection
- Authors: HT Gidey, X Guo, L Li, Y Zhang
- Journal: Sensors
- Volume & Issue: 22 (15), 5840
- Year: 2022
- Citations: 5
- Summary: This paper proposes a novel approach to indoor positioning systems by integrating heterogeneous transfer learning with hybrid feature selection techniques. The study explores the potential of combining Wi-Fi signal data with machine learning methods to improve the accuracy and adaptability of indoor positioning systems.
Conclusion
Dr. Tesfay Gidey Hailu is a highly deserving candidate for the Best Researcher Award based on his exceptional research contributions, leadership in academia, and innovative work in machine learning, data science, and public health. His interdisciplinary research in areas like indoor localization, Wi-Fi positioning, and predictive modeling demonstrates a solid track record of impactful work that benefits both academia and industry. With his expertise and leadership, Dr. Tesfay is poised to make further significant strides in advancing the field of network science and beyond. His work continues to have a profound influence on technology-driven research, particularly in healthcare and industrial applications.
By addressing the areas for improvement, Dr. Tesfay can expand his influence and continue shaping the future of technology and public health research. His potential for further academic and research accomplishments is immense, making him an ideal candidate for the Best Researcher Award.