Csaba Makó | Artificial Intelligence | Innovative Research Award

Published on by Superior Engineering

Innovative Research Award

Csaba Makó
Ludovika University of Public Service, Hungary

Csaba Makó
Affiliation Ludovika University of Public Service
Country Hungary
Scopus ID 6508289335
Documents 49
Citations 585
h-index 10
Subject Area Artificial Intelligence
Event Superior Engineering Research Awards
ORCID 0000-0002-2597-3103

Csaba Makó is a researcher affiliated with the Ludovika University of Public Service in Hungary. The researcher record supplied for this recognition profile identifies 49 documents, 585 citations, and an h-index of 10 in the Scopus-indexed record. The stated subject area is Artificial Intelligence, providing the disciplinary context for consideration under the Innovative Research Award category. [1]

Abstract

This academic recognition profile presents the documented research information of Csaba Makó in relation to the Innovative Research Award. His supplied bibliometric record contains 49 documents, 585 citations, and an h-index of 10. The profile identifies Artificial Intelligence as the relevant subject area and places the researcher within the academic environment of the Ludovika University of Public Service. Bibliographic identifiers provide a basis for distinguishing the researcher and locating associated scholarly records. [2]

Keywords

  • Artificial Intelligence
  • Innovation
  • Research
  • Bibliometrics
  • Academic Publications
  • Research Impact

Introduction

Research recognition commonly considers scholarly output, documented influence, disciplinary relevance, and identifiable research records. In this context, the Innovative Research Award profile records the available bibliometric indicators associated with Csaba Makó and relates them to the stated field of Artificial Intelligence. Scopus author identifiers and ORCID provide complementary mechanisms for researcher identification and scholarly record management. [1] [3]

Research Profile

The supplied profile associates Csaba Makó with the Ludovika University of Public Service in Hungary and identifies Artificial Intelligence as the principal subject area. The reported publication record consists of 49 documents. Its citation count is 585, while the h-index is reported as 10. These indicators describe bibliometric activity but do not, by themselves, characterize the methodological quality or substantive significance of individual publications. [1]

Research Contributions

Within the information supplied for this profile, the research contribution is framed around scholarly activity in Artificial Intelligence. Relevant contributions may be examined through individual publications, research topics, collaborations, methodologies, and documented applications. A complete assessment requires examination of the underlying publications and their research contexts rather than relying solely on aggregate bibliometric indicators. [4]

Publications

The supplied Scopus record reports 49 documents associated with the researcher identifier 6508289335. Individual publication titles, journals, publication dates, citation distributions, and DOI records should be verified against the corresponding bibliographic databases before being used for detailed publication-level analysis. [1]

Research Impact

The reported total of 585 citations and h-index of 10 provides a quantitative description of the researcher’s citation record at the time represented by the supplied data. Citation indicators can vary between databases and over time, and they may also differ according to indexing coverage. Consequently, the figures should be interpreted together with publication-level and disciplinary context. [1] [5]

Award Suitability

The Innovative Research Award profile connects the supplied research record with the Superior Engineering Research Awards event. The documented affiliation, subject area, publication count, citation count, h-index, and persistent researcher identifier provide factual information for an award-review process. Final recognition should be determined according to the applicable award criteria and verification procedures. [6]

Conclusion

Csaba Makó’s supplied academic profile documents a research record associated with the Ludovika University of Public Service, Hungary, and Artificial Intelligence. The reported 49 documents, 585 citations, and h-index of 10 form the principal bibliometric indicators presented in this recognition profile. Persistent identifiers such as Scopus Author ID and ORCID support researcher identification and facilitate further verification of scholarly records.

References

  1. ORCID. (n.d.). Csaba Makó — ORCID record.
    https://orcid.org/0000-0002-2597-3103
  2. Elsevier. (n.d.). Scopus Author Details: Csaba Makó, Author ID 6508289335.
    https://www.scopus.com/authid/detail.uri?authorId=6508289335
  3. Makó, C., Illéssy, M., Pap, J., Farkas, É., & Komlósi, L. (2025). Algorithmic Management in Traditional Workplaces: The Case of High vs. Low Involvement Working Practices. Journal of Labor and Society. https://doi.org/10.1163/24714607-bja10182
  4. Molina, O., Butollo, F., Makó, C., et al. (2023). It takes two to code: A comparative analysis of collective bargaining and artificial intelligence. Transfer: European Review of Labour and Research. https://doi.org/10.1177/10242589231156515
  5. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572.

Mr. Mohammed Abdullah Abbas | Machine Learning | Best Researcher Award

Published on by Superior Engineering

Mr. Mohammed Abdullah Abbas | Machine Learning | Best Researcher Award

Mr. Mohammed Abdullah Abbas , University of Technology Department of Computer Science , Iraq.

Mr. Mohammed Abdullah Abbas is a dedicated researcher in the field of Artificial Intelligence 🤖 and Machine Learning 📊. Based in Baghdad, Iraq 🇮🇶, he is affiliated with the University of Technology’s Computer Science Department 🏛️. He earned his B.Sc. in Computer Engineering in 2015 🎓 and his M.Sc. in Computer and Communication Engineering from IUL, Lebanon in 2020 🌍. Mohammed’s scholarly work explores innovations in credit card fraud detection 💳, ECG signal analysis 🫀, and battery life prediction 🔋. He is proficient in Arabic and English 🌐 and actively contributes to academic platforms like Google Scholar, Scopus, and ResearchGate 📚.

Professional Profile

Orcid

Education & Experience

🎓 B.Sc. in Computer Engineering – Al Salam University, 2015
🎓 M.Sc. in Computer and Communication Engineering – IUL, Lebanon, 2020
🏫 Current Position: Researcher, Computer Science Department, University of Technology, Baghdad
💡 Research Specialization: Artificial Intelligence & Machine Learning
📍 Location: Baghdad, Iraq

Summary Suitability

Mr. Mohammad A. Abbas is a compelling nominee for the Best Researcher Award, recognized for his significant contributions to the fields of Artificial Intelligence (AI) and Machine Learning (ML). As a rising researcher affiliated with the University of Technology – Baghdad, his work has demonstrated remarkable impact, innovation, and interdisciplinary application, particularly in areas like financial fraud detection, biomedical signal analysis, and battery health prediction.

Professional Development

Mr. Mohammed A. Abbas is committed to lifelong learning and innovation in technology. He has developed and published advanced research in machine learning and signal processing 🧠, with applications in financial security 💳, health monitoring 🫁, and energy storage systems 🔋. He continually enhances his expertise through academic publishing, peer collaboration 🤝, and participation in scholarly platforms such as Scopus, ORCID, and ResearchGate 🌐. His professional growth is anchored in practical problem-solving and theoretical advancements, bridging gaps between research and real-world applications ⚙️. Mohammed embraces every opportunity to contribute to the AI and data science communities globally 🌍.

Research Focus

Mohammed’s research centers on Artificial Intelligence 🤖 and Machine Learning 📈, targeting impactful real-world applications. His projects range from fraud detection in financial systems 💰 to improving ECG signal analysis for healthcare innovation ❤️, and predicting battery performance for sustainable energy solutions 🔋. By leveraging deep learning, signal processing, and support vector machines, he aims to solve pressing problems in data-intensive environments 🧠. His interdisciplinary focus contributes to smarter, data-driven systems across sectors like finance, healthcare, and renewable energy 🌱. With a forward-looking mindset, Mohammed is advancing the future of AI through meaningful and ethical research 🔍.

Awards and Honors 

🏅 Long-term Service – Serving at the University of Technology – Iraq, Baghdad since June 1987 in the field of Computer Science 🖥️

🎖️ Academic Position of Distinction – Recognized with an invited position in Computer Engineering at the University of Technology, Department of Computer Science 🧠

📚 Scholarly Contributions – Published multiple peer-reviewed articles in reputable journals including Springer, Elsevier, and IEEE-indexed platforms 📖

🌐 Active Contributor to Research Networks – Verified academic profiles on Google Scholar, Scopus, ORCID, and ResearchGate 🔍

🏆 Recognition by Academic Community – Trusted and cited by international researchers for contributions in Artificial Intelligence, Machine Learning, and Signal Processing 🌍

Publication Top Notes

📘 1. Identifying Oil Spill Areas and Causes Using a Deep Learning Model

  • Type: Conference Paper

  • Conference Series: Communications in Computer and Information Science (CCIS)

  • Year: 2024

  • DOI: 10.1007/978-3-031-87076-7_2

  • ISBNs: 978-3-031-87075-0 (Print), 978-3-031-87076-7 (Online)

  • ISSNs: 1865-0929 (Print), 1865-0937 (Electronic)

  • Contributors: Mohammad A. Abbas, Bilal A. Ghazal, Kadhim H. Gitr

🫀 2. Improving Automated Labeling with Deep Learning and Signal Segmentation for Accurate ECG Signal Analysis

  • Type: Journal Article

  • Journal: Service Oriented Computing and Applications (Springer)

  • Year: 2024

  • DOI: 10.1007/s11761-024-00436-5

  • EID: 2-s2.0-85208991354

  • ISSNs: 1863-2394 (Print), 1863-2386 (Online)

  • Contributors: Hussein, O.; Jameel, S.M.; Altmemi, J.M.; Abbas, M.A.; Uğurenver, A.; Alkubaisi, Y.M.; Sabry, A.H.

🔋 3. Predicting Batteries’ Second-Life State-of-Health with First-Life Data and On-Board Voltage Measurements Using Support Vector Regression

  • Type: Journal Article

  • Journal: Journal of Energy Storage (Elsevier)

  • Year: 2024

  • DOI: 10.1016/j.est.2024.114554

  • EID: 2-s2.0-85209142364

  • ISSN: 2352-152X

  • Contributors: Jameel, S.M.; Altmemi, J.M.; Oglah, A.A.; Abbas, M.A.; Sabry, A.H.

Conclusion

Mr. Mohammad Abdullah Abbas exemplifies the qualities of an outstanding researcher with his commitment to advancing AI applications across multiple domains. His innovative approach, consistent research output, and focus on impactful, real-world problems make him a highly suitable candidate for the Best Researcher Award. His ongoing dedication to research excellence promises continued contributions to both academia and industry.