slimane arbaoui | Artificial Intelligence | Young Scientist Award

Mr. slimane arbaoui | Artificial intellegence | Young Scientist Award

Cube-SDC team, INSA Strasbourg, University of Strasbourg , 24 Bd de la Victoire, Strasbourg, 67000, France, insa strasbourg, France

Slimane Arbaoui is a dedicated final-year Computer Science student at École Supérieure en Informatique (ESI) in Sidi Bel Abbess, Algeria, specializing in Android application development and machine learning. 🎓 His skills span Java-based Android development, data integration, and advanced problem-solving in software, alongside a versatile understanding of multiple programming languages, including Python and Kotlin. Slimane has applied his AI knowledge to impactful projects, even authoring a research paper. 📚 Known for his innovation and strong analytical skills, Slimane is passionate about tackling real-world challenges with technology.

Publication Profile

Scopus

Education

Slimane completed his State Engineering and Master’s degrees in Computer Science at ESI SBA in 2023. 🎓 His academic journey has strengthened his technical expertise and provided a foundation in both theoretical and applied computing, with a focus on machine learning, mobile app development, and web technologies.

Experience

During his internship at INSA-Strasbourg, France 🇫🇷, Slimane applied machine learning to improve battery health prediction, developing models that track and identify factors contributing to battery degradation. At CNAS in Algeria, he gained practical insights into network database applications and web app development. 💻 As a freelancer on Upwork, Slimane developed Android applications and managed web back-end services, demonstrating his versatility in real-world projects.

Research Focus

Slimane’s research interests center on artificial intelligence and machine learning, with a special focus on NLP applications, sentiment analysis, and health data prediction. 🧠 His projects include sentiment analysis and fake news detection in Arabic language datasets, alongside health management applications that leverage data-driven insights to enhance service quality. His work in battery health prediction highlights his proficiency in machine learning model development and evaluation.

Awards and Honours

Slimane holds several certifications, including Microsoft Certified: Azure Fundamentals and the Android Basics Nanodegree. 🏅 His achievements in AI include completing courses on deep learning and machine learning through Kaggle and Coursera, which demonstrate his commitment to continuous learning and professional development.

Publication Top Notes

Dual-model approach for one-shot lithium-ion battery state of health sequence prediction

SOCXAI: Leveraging CNN and SHAP Analysis for Battery SOC Estimation and Anomaly Detection

Data-driven strategy for state of health prediction and anomaly detection in lithium-ion batteries

 

 

Tesfay Gidey | Artificial Intelligence | Best Researcher Award

Dr. Tesfay Gidey | Artificial Intelligence | Best Researcher Award

Lecturer, Addis Ababa Science and Technology University, Ethiopia

Tesfay Gidey Hailu is a highly skilled Information and Communication Engineer and data scientist with a passion for leveraging data to drive innovation and business insights. With expertise in computer science, software engineering, machine learning, and data analytics, he excels in problem-solving, leadership, and technology project management. Tesfay’s work focuses on indoor localization, signal processing, and health data applications, making him a forward-thinking leader in his field. His dedication to continuous learning and delivering actionable results underscores his impressive career in academia and industry. 💼🔧📊

Publication Profile

ORCID

Strengths for the Award:

  1. Diverse Expertise: Tesfay’s expertise spans across critical areas such as signal processing, indoor localization, machine learning, data fusion, and health informatics, aligning well with cutting-edge research areas.
  2. Impressive Academic Qualifications: Holding a Ph.D. in Information and Communication Engineering, along with two MSc degrees, he possesses deep knowledge in interdisciplinary fields.
  3. Research Contributions: He has authored numerous peer-reviewed publications in high-impact journals such as Sensors, Intelligent Information Management, and Journal of Biostatistics. His work in Wi-Fi indoor positioning, predictive modeling, and health informatics shows a broad application of research across industries.
  4. Leadership in Academia: His roles as Associate Dean and Head of Department demonstrate his leadership in driving research, improving curriculum quality, and promoting technology transfer.
  5. Innovative Research Focus: His Ph.D. dissertation on transfer learning for fingerprint-based indoor positioning and various data fusion methods reflect his innovative contributions to solving real-world problems with advanced technologies.

Areas for Improvement:

  1. Broader Industry Impact: While his research is highly academic, incorporating more industry-driven collaborations or commercial applications could strengthen the practical impact of his work.
  2. Public Engagement: Increasing public outreach and collaboration with non-academic sectors or public talks could elevate his visibility and expand the impact of his research findings.
  3. Global Collaboration: Expanding his research collaborations beyond local and regional levels, particularly with international industries, could further showcase the global relevance of his work.

Education 🎓

Tesfay holds a Ph.D. in Information and Communication Engineering from the University of Electronic Science and Technology of China (2023), where his research centered on signal and information processing applied to indoor positioning using machine learning algorithms. He also earned an MSc in Software Engineering from HILCOE School of Computer Science and Information Technology (2018) and an MSc in Health Informatics and Biostatistics from Mekelle University (2013). Additionally, he completed his BSc in Statistics with a minor in Computer Science at Addis Ababa University (2006). 📚💻📈

Experience 💼

Tesfay has held several leadership positions, including Associate Dean at Addis Ababa Science and Technology University (AASTU), where he led research, technology transfer, student recruitment, and faculty training initiatives. He was also the Head of Department and Coordinator at Jimma University, contributing to curriculum enhancement and student retention programs. His experience spans research in manufacturing industries, project management, and academic administration. 🏫📊👨‍🏫

Research Focus 🔬

Tesfay’s research focuses on signal processing, indoor localization, machine learning, data mining, and information fusion. He specializes in developing advanced models for indoor positioning systems, predictive modeling, and statistical quality control, aiming to solve complex problems in health informatics, manufacturing industries, and public health. His work integrates cutting-edge technologies to advance both theoretical and applied fields. 📡📉🤖

Awards and Honors 🏆

Tesfay has been recognized for his contributions to the fields of information and communication engineering and data science. He has received multiple awards and honors for his research and leadership roles in academia, particularly in driving innovative projects that bridge the gap between technology and industry. 🌍🎖️

Publications Highlights 📚

Tesfay has published extensively in top-tier journals, with a focus on indoor positioning systems, data fusion, and health informatics. His research includes the development of novel machine learning models and statistical analysis tools. His works have been widely cited, showcasing his impact in the academic community. 📊✍️

MultiDMet: Designing a Hybrid Multidimensional Metrics Framework to Predictive Modeling for Performance Evaluation and Feature Selection (2023). Intelligent Information Management, 15, 391-425. Cited by 2 articles. Link

Data Fusion Methods for Indoor Positioning Systems Based on Channel State Information Fingerprinting (2022). Sensors, 22, 8720. Cited by 15 articles. Link

Heterogeneous Transfer Learning for Wi-Fi Indoor Positioning Based Hybrid Feature Selection (2022). Sensors, 22, 5840. Cited by 10 articles. Link

OHetTLAL: An Online Transfer Learning Method for Fingerprint-Based Indoor Positioning (2022). Sensors, 22, 9044. Cited by 5 articles. Link

A Multilevel Modeling Analysis of the Determinants and Cross-Regional Variations of HIV Testing in Ethiopia (2016). J Biom Biostat, 7, 277. Cited by 8 articles. Link

Conclusion:

Tesfay Gidey Hailu’s robust academic background, extensive research portfolio, and leadership roles make him a strong candidate for the Best Research Award. His work in signal processing, machine learning, and data-driven innovation in health informatics and communication systems demonstrates a clear commitment to advancing technology and solving societal problems. While his impact could be enhanced by deeper industry collaborations and global outreach, his current achievements already reflect substantial contributions to the field, making him deserving of recognition.