Prof. Ebenezer Esenogho | Telecommunications | Best Researcher Award

Prof. Ebenezer Esenogho | Telecommunications | Best Researcher Award

Prof. Ebenezer Esenogho | University of South Africa | South Africa

Dr. Ebenezer Esenogho is a distinguished academic and researcher with nearly two decades of experience in engineering, telecommunications, and AI. He holds multiple degrees, including a Ph.D. in Electronic Engineering, and has worked globally in South Africa, Uganda, Botswana, and Nigeria 🌍. As a professor and research lead, he focuses on cutting-edge research in 5G networks, AI, IoT, cybersecurity, and more πŸ’‘. He has received numerous awards for his research excellence πŸ† and has mentored many students and faculty, inspiring the next generation of engineers πŸ‘©β€πŸ«πŸ‘¨β€πŸ«.

Professional Profile:

ORCID

Google Scholar

Suitability for the Best Researcher Award

Dr. Ebenezer Esenogho is highly deserving of the Best Researcher Award due to his outstanding contributions to the fields of engineering, telecommunications, and AI over nearly two decades. His qualifications, including a Ph.D. in Electronic Engineering, and extensive international experience in countries like South Africa, Uganda, Botswana, and Nigeria, underscore his global perspective and expertise in these rapidly evolving areas.

Education & Experience

  • Diploma in Computer Engineering (2002/2003) πŸ–₯️
  • BEng in Computer Engineering (2007/2008) πŸŽ“
  • MEng in Telecommunications Engineering (2010/2011) πŸ“‘
  • Ph.D. in Electronic Engineering (University of KwaZulu-Natal, South Africa) πŸŽ“
  • Senior Lecturer, University of Benin (2007-2013) πŸ‘¨β€πŸ«
  • GES Post-Doctoral Research Fellowship, University of Johannesburg (2017-2020) πŸ…
  • Associate Professor, Kampala International University, Uganda 🌍
  • Expatriate Senior Lecturer, University of Botswana 🀝
  • Distinguished Research Professor, University of South Africa (UNISA) 🌟

Professional DevelopmentΒ 

Dr. Esenogho has continually advanced his career through prestigious fellowships and global academic engagements. He has contributed significantly to the research landscape with post-doctoral work in the Fourth Industrial Revolution (4IR) at the University of Johannesburg πŸ’Ό. As a research lead at UNISA, he drives innovations in AI and smart systems πŸ€–. His mentorship of postgraduate students and junior faculty has helped develop new research pathways in telecommunications and AI πŸ”. Dr. Esenogho actively contributes to international conferences and serves as a reviewer for academic journals πŸ“š. His leadership in research and academia has inspired excellence across continents 🌎.

Research FocusΒ 

Dr. Esenogho’s research is at the intersection of telecommunications, AI, and smart systems, with a strong emphasis on next-generation networks and technologies. He explores 5G and cognitive radio networks πŸ“Ά, smart grid and IoT systems πŸ”Œ, and the role of AI/ML in enhancing network security and efficiency πŸ”. His work on wireless sensor networks, mobile/cloud computing, and big data is transforming how we understand and use connectivity 🌐. Dr. Esenogho is pioneering research in these areas, helping shape the future of communication technologies πŸ“‘. His commitment to cutting-edge innovation continues to push boundaries and solve complex engineering problems πŸ”¬.

Awards & Honors

  • CEPS/Eskom HVDC Fellowship (2013, 2014) πŸ…
  • J.W. Nelson Award (2015) πŸ†
  • GES Post-Doctoral Fellowship (2017–2020) πŸŽ“
  • NRF C-rating for researchers of international repute 🌟
  • Best Oral Paper Presentation Award, UJ Postdoctoral Fellowship Conference (2019) πŸ…
  • F’SAIT SARChI Chair Award (2021) πŸ…
  • Member of IEEE, SAIEE, and other professional bodies 🀝

Publication Top Notes:

  • πŸ€– A Neural Network Ensemble with Feature Engineering for Improved Credit Card Fraud Detection Β πŸ‘₯ Cited by: 218
  • 🌐 Integrating AI, IoT, and 5G for Next-Generation Smartgrid: A Survey of Trends, Challenges, and Prospects – πŸ‘₯ Cited by: 165
  • πŸ’‰ A Machine Learning Method with Filter-Based Feature Selection for Improved Prediction of Chronic Kidney DiseaseBioengineering Β πŸ‘₯ Cited by: 73
  • πŸ“‘ Toward Integrating Intelligence and Programmability in Open Radio Access Networks: A Comprehensive Survey πŸ‘₯ Cited by: 59
  • πŸ’³ A Proposed Model for Card Fraud Detection Based on CatBoost and Deep Neural Network πŸ‘₯ Cited by: 57
  • πŸ§‘β€βš•οΈ An Interpretable Machine Learning Approach for Hepatitis B DiagnosisΒ πŸ‘₯ Cited by: 53

 

 

 

Prof. Guodong Pang | Telecommunications | Best Researcher Award

Prof. Guodong Pang | Telecommunications | Best Researcher Award

Prof. Guodong Pang, Rice University, United StatesΒ 

✨ Prof. Guodong Pang is a distinguished academic in the realm of Computational Applied Mathematics and Operations Research, currently serving as a Professor at Rice University since January 2022. His journey in academia showcases a trajectory of excellence, with previous roles including Professor from July 2020 to December 2021, Associate Professor from July 2016 to June 2020, and Assistant Professor (Harold and Inge Marcus Career Professorship) from August 2010 to June 2016. Prof. Pang earned his Ph.D. in Operations Research in May 2010, guided by the expertise of Prof. Ward Whitt, from the Department of Industrial Engineering and Operations Research at Columbia University. With a career marked by scholarly achievements, Prof. Pang is a dedicated educator and researcher contributing to the advancements in his field. πŸŽ“πŸ“Š

πŸŽ“Education :Β 

🌟 Prof. Guodong Pang is a distinguished scholar with a strong academic foundation. He earned his Ph.D. in Operations Research in May 2010 from the Department of Industrial Engineering and Operations Research at Columbia University, under the mentorship of Prof. Ward Whitt. This academic journey reflects his dedication to the field of Operations Research. Additionally, Prof. Pang holds an M.S. in Mathematics, obtained in 2006 from the Department of Mathematics at Virginia Tech’s Grado Department of Industrial and Systems Engineering. His educational achievements underline a profound commitment to mathematical sciences and operations research, shaping his path as a notable academic in these fields. πŸŽ“πŸ”πŸ“Š

🌐 Professional Profiles : 

Scopus

Google Scholar

πŸ† Awards :

🌟 Prof. Guodong Pang’s illustrious career is adorned with well-deserved accolades, showcasing his commitment to excellence. Among his notable achievements are the Outstanding Faculty Award, a testament to his exceptional teaching abilities, bestowed by the Penn State Chapter of the Institute of Industrial and Systems Engineers in 2016. The recognition continued with his selection as a Finalist in the INFORMS Junior Faculty Interest Group (JFIG) Paper Competition in 2014, highlighting his scholarly contributions. Notably, he held the esteemed Harold and Inge Marcus Career Professorship at Penn State University from 2010 to 2016, a recognition of his significant impact in academia. Prof. Pang’s dedication was further acknowledged with the Class of 1988 Doctoral Fellowship during his time at Columbia University in 2009-10 and the Grado Fellowship at Virginia Tech in 2005-06. These awards underscore his multifaceted contributions to teaching, research, and leadership in the field of industrial and systems engineering. πŸ†πŸŽ“

🧠 Research Interests πŸ”¬πŸŒ :

Prof. Guodong Pang is a trailblazer in the realm of applied mathematics, with a diverse array of research interests that span the vast landscape of probability and stochastic processes. His intellectual pursuits include Applied Probability, Stochastic Processes and Analysis, Stochastic Control, and Asymptotic Methods, all underscored by a keen interest in numerical methods and simulation. Prof. Pang’s expertise extends to complex systems, including Stochastic Networks, Queueing Systems, and Operations Management, with a special focus on service systems such as those in healthcare, customer contact centers, and cloud-based services. His contributions also reach into the realms of Financial Engineering, Econometrics, Risk and Decision Analysis, and Epidemiology, showcasing a multidimensional approach to solving real-world challenges. πŸ§ πŸ”¬πŸŒ

πŸ“šΒ Publication Impact and Citations :Β 

Scopus Metrics:

  • πŸ“Β Publications: 73 documents indexed in Scopus.
  • πŸ“ŠΒ Citations: A total of 577 citations for his publications, reflecting the widespread impact and recognition of Prof. Guodong Pang’s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 1376 πŸ“–
    • h-index: 18 πŸ“Š
    • i10-index: 38 πŸ”
  • Since 2018:
    • Citations: 795 πŸ“–
    • h-index: 15 πŸ“Š
    • i10-index: 29 πŸ”

πŸ‘¨β€πŸ« A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. πŸŒπŸ”¬

Publications ( Top Note ) :

1.Β  Martingale proofs of many-server heavy-traffic limits for Markovian queues

(Published in Management Science, 2007) – Cited by 294.

2.Β  Two-parameter heavy-traffic limits for infinite-server queues

(Published in Queueing Systems, 2010) – Cited by 116.

3.Β  Heavy-traffic limits for many-server queues with service interruptions

(Published in Queueing Systems, 2009) – Cited by 51.

4.Β  The impact of dependent service times on large-scale service systems

(Published in Manufacturing & Service Operations Management, 2012) – Cited by 50.

5.Β  Service interruptions in large-scale service systems

(Published in Management Science, 2009) – Cited by 46.

6.Β  Two-parameter heavy-traffic limits for infinite-server queues with dependent service times

(Published in Queueing Systems, 2013) – Cited by 45.

7.Β  Infinite-server queues with batch arrivals and dependent service times

(Published in Probability in the Engineering and Informational Sciences, 2012) – Cited by 42.

8.Β  A logarithmic safety staffing rule for contact centers with call blending

(Published in Management Science, 2015) – Cited by 38.

9.Β  Ergodicity of a LΓ©vy-driven SDE arising from multiclass many-server queues

(Published in Stochastic Processes and their Applications, 2019) – Cited by 35.

10.Β  Functional limit theorems for non-Markovian epidemic models

(Published in The Annals of Applied Probability, 2022) – Cited by 32.