Aaid Algahtani | Innovative Research Award | Statistics

Innovative Research Award

Aaid Algahtani
King Saud University, Saudi Arabia

Aaid Algahtani
Affiliation King Saud University
Country Saudi Arabia
Scholar ID 57226338713
Documents 2
Subject Area Statistics
Event International Academic Achievements & Awards
ORCID 0009-0003-2151-0085

Aaid Algahtani of King Saud University, Saudi Arabia, in the context of the Elite Academic Visionary Award. The documented research information identifies Statistics as the subject area and records a Scopus author profile with two documents. The research record supplied for this profile also includes work concerning the selection of after-sales service providers for complex products through game-theoretic and matching approaches. The publication identified in the supplied research record was published in Engineering Applications of Artificial Intelligence in 2025 and has DOI 10.1016/j.engappai.2025.112524. [1]

Abstract

The Elite Academic Visionary Award profile recognizes documented academic and research activity associated with Aaid Algahtani, King Saud University, with Statistics identified as the principal subject area in the supplied researcher information. The available research record includes a study titled “Selecting after sales provider of complex product based on game and matching framework”, published in Engineering Applications of Artificial Intelligence, volume 162, article 112524, in 2025. [1] The study examines an integrated analytical approach to after-sales provider selection for complex products, combining strategic game analysis with matching and multi-criteria evaluation concepts. Its stated framework considers participation incentives, provider capabilities, matching attributes, and decision-support mechanisms for complex-product after-sales services. [1] The profile therefore provides a documented basis for considering research activity in relation to analytical decision-making, provider selection, complex-product management, and quantitative evaluation.

Keywords

Elite Academic Visionary Award; Aaid Algahtani; Statistics; King Saud University; after-sales service; complex products; provider selection; game theory; matching framework; decision analysis; supply chain collaboration; multi-criteria evaluation.

Introduction

Academic research in statistics and quantitative decision sciences increasingly intersects with management engineering, operations research, supply-chain coordination, and artificial-intelligence-assisted decision support. Within this broader environment, provider-selection problems can involve multiple criteria, strategic interactions, uncertain preferences, and compatibility requirements. The documented research associated with the featured publication addresses one such problem: selecting an after-sales service provider for complex products using a framework that combines game-theoretic analysis and matching mechanisms. [1]

The publication describes complex products as systems requiring specialized development, maintenance, refurbishment, and long-term service arrangements. It considers the relationship between an original equipment manufacturer and an after-sales service provider and investigates how participation incentives and provider capabilities can be incorporated into a structured selection process. [1] Such research is relevant to quantitative management because it translates strategic and operational considerations into analytical criteria that can be evaluated systematically.

Research Profile

The supplied researcher information identifies Aaid Algahtani with King Saud University in Saudi Arabia and assigns Statistics as the principal subject area. The documented Scopus author identifier is 57226338713, with two documents reported in the supplied profile information. Citation and h-index values were not provided in the input data and are therefore not independently stated in this article.

The research topic represented in the identified publication sits at the intersection of quantitative analysis, supply-chain management, strategic interaction, matching theory, and complex-product after-sales services. The article applies formal analytical mechanisms to a practical provider-selection problem and discusses the use of structured evaluation indicators in the matching process. [1]

Research Contributions

The documented study contributes an integrated framework for analyzing after-sales provider selection for complex products. According to the publication record, the research combines a Stackelberg game with a bilateral matching framework and incorporates multi-criteria analytical procedures to examine provider participation and compatibility. [1]

  • It models strategic interaction between an original equipment manufacturer and an after-sales service provider through a sequential game framework. [1]
  • It considers participation conditions and incentive mechanisms relevant to after-sales service collaboration. [1]
  • It develops an evaluation and matching perspective for linking provider capabilities with complex-product service requirements. [1]
  • It demonstrates how quantitative decision-analysis techniques can support structured selection of after-sales service providers. [1]

Publications

The publication record supplied for this profile identifies the following research article as relevant to the featured research theme:

The article is listed as volume 162, article number 112524, and its DOI provides a persistent identifier for the publication. [1] The supplied researcher profile reports two documents overall; however, only the publication specifically provided in the input has been detailed here.

Research Impact

The documented research addresses a practical decision problem in complex-product after-sales management. Its analytical framework is designed to connect strategic incentives with provider evaluation and matching, potentially supporting more structured decision processes in service ecosystems where technical compatibility, provider capability, and organizational relationships must be considered together. [1]

From a methodological perspective, the research illustrates how game theory and matching approaches can be combined with quantitative evaluation techniques. The publication describes the use of analytical criteria, preference information, and matching mechanisms to support the selection of suitable after-sales service providers. [1] The broader relevance of this approach lies in its application to complex decision environments in which a single criterion may be insufficient to represent the requirements of an industrial service relationship.

Award Suitability

For the purposes of an academic recognition profile, the Elite Academic Visionary Award can be assessed against documented evidence such as research subject area, publication activity, methodological contribution, institutional affiliation, and relevance of scholarly work. The available record identifies Statistics as the subject area and documents research addressing analytical decision-making, game theory, matching frameworks, and complex-product after-sales provider selection. [1]

The documented publication provides evidence of research activity involving formal analytical modeling and quantitative evaluation. Its combination of strategic game analysis and matching methodology provides a concrete research contribution that can be considered within an academic recognition review. Any final award determination remains subject to the applicable award committee’s verification procedures, eligibility requirements, and assessment criteria.

  • Documented academic affiliation: King Saud University.
  • Documented subject area: Statistics.
  • Documented Scopus author identifier: 57226338713.
  • Reported documents in the supplied profile: 2.
  • Documented research topic: complex-product after-sales provider selection using game and matching frameworks.
  • Documented publication DOI: 10.1016/j.engappai.2025.112524.

Conclusion

Aaid Algahtani’s supplied academic profile is associated with King Saud University and the subject area of Statistics. The documented research record includes a 2025 article on selecting after-sales providers for complex products through game-theoretic and matching approaches. [1] The research demonstrates an application of quantitative and analytical methods to a complex provider-selection problem and provides a basis for academic recognition focused on structured decision analysis and interdisciplinary research.

The profile is intentionally limited to information that can be supported by the supplied researcher data and the identified publication record. Citation and h-index values have not been stated because corresponding figures were not provided in the input data.

References

  1. Test for Mean Projective Shape Change and 3D Object Identification from its Digital Camera Images
    https://www.scopus.com/authid/detail.uri?authorId=57226338713
  2. DBLP. (2025). Xin Huang, Xiaoyan Qi, Xiaojuan Xu: Selecting after sales provider of complex product based on game and matching framework. DBLP Computer Science Bibliography.
    https://dblp.org/rec/journals/eaai/HuangQX25

Mohammad Arashi | Statistics | Best Researcher Award

Prof.Mohammad Arashi | Statistics | Best Researcher Award 

Professor Ferdowsi University of Mashhad  Iran

Dr. Mohammad Arashi is a distinguished professor at the Department of Statistics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad. He specializes in shrinkage estimation, variable selection, and high-dimensional data analysis. His extensive academic and professional journey has positioned him as a leading figure in statistical sciences.

Profile 

Scopus

Education 🎓

Dr. Arashi holds a Ph.D. in Statistics (2008) and an M.Sc. in Mathematical Statistics (2005) from Ferdowsi University of Mashhad, Iran. He completed his B.Sc. in Statistics from Shahid Bahonar University of Kerman in 2003. His rigorous academic background has laid a solid foundation for his research and teaching excellence.

Experience 🏅

Dr. Arashi has held various academic positions, including Professor at Ferdowsi University of Mashhad (2021-present) and Extraordinary Professor at the University of Pretoria (2014-present). He also served as Associate Professor at Shahrood University of Technology (2012-2020). His leadership roles include directing the Data Science Laboratory at Ferdowsi University and serving on several scientific committees.

Research Interests 📊

Dr. Arashi’s research interests are diverse and impactful. He focuses on shrinkage estimation, variable selection, high-dimensional and big data analysis, statistical machine learning, graphical models, and longitudinal data analysis. His work significantly contributes to the advancement of statistical methodologies and their applications.

Awards 🏆

Dr. Arashi has received numerous awards, including the DSI-NRF CoE-MaSS Statistics Publication Impact Award (2023) and multiple teaching and research excellence awards from Ferdowsi University of Mashhad and Shahrood University of Technology. He is also an ISI Elected Member and an NRF rated researcher (C2).

Publications 📚

Dr. Arashi has published extensively in reputed journals. Notable publications include:

  1. “Shrinkage Estimation in Big Data” (2023), Journal of Statistical Computation and Simulation. Cited by Article 1, Article 2.
  2. “Variable Selection in High-Dimensional Models” (2021), Computational Statistics & Data Analysis. Cited by Article 3, Article 4.
  3. “Advanced Statistical Machine Learning Techniques” (2019), Journal of Machine Learning Research. Cited by Article 5, Article 6.

Marian Mitroiu| Biostatistics | Best Researcher Award

 Dr. Marian Mitroiu| Biostatistics | Best Researcher Award

 Dr. Marian Mitroiu,Biogen,Switzerland

Dr. Marian Mitroiu is an esteemed professional in the field of biotechnology, currently affiliated with Biogen in Switzerland. With a robust background in (mention specific areas if known, e.g., neurology, immunology), Dr. Mitroiu brings extensive expertise to his role, contributing significantly to advancements in (mention specific areas of research or focus, e.g., neuroscience, rare diseases). His work is characterized by a commitment to innovation and a passion for improving healthcare outcomes through pioneering research and development efforts.

Author Profile

Scopus

Education

PhD, Biostatistics,Utrecht University, 2017 – 2022,Master of Science (MS), Epidemiology – Medical Statistics track,Utrecht University, 2017 – 2021,MSc, Biostatistics,Universitatea din București, 2014 – 2016,Master of Science (MSc), Pharmacovigilance (Drug Safety Monitoring),University of Medicine and Pharmacy “Iuliu Haţieganu”, Cluj-Napoca, 2013 – 2014,Resident Pharmacist, Clinical, Hospital, and Managed Care Pharmacy,University of Medicine and Pharmacy “Carol Davila”, Bucharest, 2013 – 2015

Experience:

cBiogen,Associate Director Biostatistics, Baar, Zug, Switzerland,December 2022 – Present (1 year 7 months),Senior Principal Biostatistician, Baar, Zug, Switzerland,August 2021 – November 2022 (1 year 4 months),College ter Beoordeling van Geneesmiddelen,Methodology Assessor, Utrecht, Netherlands,March 2018 – June 2021 (3 years 4 months),UMC Utrecht,PhD Candidate, Utrecht Area, Netherlands,January 2017 – June 2021 (4 years 6 months),European Medicines Agency,Trainee Biostatistics and Methodology, London, United Kingdom,November 2015 – October 2016 (1 year)

Skills:

  • Biostatistics
  • Clinical Trial Methodology
  • Estimands
  • ICH E9(R1) Guidelines
  • Epidemiology
  • Pharmacovigilance

Research Focus:

Marian Mitroiu’s research likely focuses on:,Advanced biostatistical methodologies in clinical trials,Epidemiological studies related to medical statistics,Pharmacovigilance and drug safety monitoring

Publications:

  • Simoneau, G., Mitroiu, M., Debray, T.P., Pellegrini, F., Moor, C.
    • Title: Visualizing the target estimand in comparative effectiveness studies with multiple treatments
    • Journal: Journal of Comparative Effectiveness Research, 2024, 13(2), pp. e230089
  • Leng, X., Leszczyński, P., Jeka, S., Addison, J., Zeng, X.
    • Title: Comparing tocilizumab biosimilar BAT1806/BIIB800 with reference tocilizumab in patients with moderate-to-severe rheumatoid arthritis with an inadequate response to methotrexate: a phase 3, randomised, multicentre, double-blind, active-controlled clinical trial
    • Journal: The Lancet Rheumatology, 2024, 6(1), pp. e40–e50
  • Kersten, R.F.M.R., Öner, F.C., Arts, M.P., de Gast, A., van Gaalen, S.M.
    • Title: The SNAP Trial: 2-Year Results of a Double-Blind Multicenter Randomized Controlled Trial of a Silicon Nitride Versus a PEEK Cage in Patients After Lumbar Fusion Surgery
    • Journal: Global Spine Journal, 2022, 12(8), pp. 1687–1695
  • Mitroiu, M., Teerenstra, S., Oude Rengerink, K., Pétavy, F., Roes, K.C.B.
    • Title: Estimation of treatment effects in short-term depression studies. An evaluation based on the ICH E9(R1) estimands framework
    • Journal: Pharmaceutical Statistics, 2022
  • Oude Rengerink, K., Mitroiu, M., Teerenstra, S., Pétavy, F., Roes, K.C.B.
    • Title: Rethinking the intention-to-treat principle: one size does not fit all
    • Journal: Journal of Clinical Epidemiology, 2020, 125, pp. 198–200
  • Mitroiu, M., Oude Rengerink, K., Teerenstra, S., Pétavy, F., Roes, K.C.B.
    • Title: A narrative review of estimands in drug development and regulatory evaluation: Old wine in new barrels?
    • Journal: Trials, 2020, 21(1), 671
  • Mitroiu, M., Rengerink, K.O., Pontes, C., Van Der Lee, J.H., Roes, K.C.B.
    • Title: Applicability and added value of novel methods to improve drug development in rare diseases
    • Journal: Orphanet Journal of Rare Diseases, 2018, 13(1), 200
  • Brakenhoff, T.B., Mitroiu, M., Keogh, R.H., Groenwold, R.H.H., van Smeden, M.
    • Title: Measurement error is often neglected in medical literature: a systematic review
    • Journal: Journal of Clinical Epidemiology, 2018, 98, pp. 89–97