Gokhan Yildirim | Marketing analytics | Best Researcher Award

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Dr. Gokhan Yildirim | Marketing analytics | Best Researcher Award

Gokhan Yildirim is an Associate Professor of Marketing at Imperial College Business School, specializing in marketing analytics and return on investment. His expertise spans digital marketing, long-term marketing effectiveness, and customer mindset metrics. With a strong foundation in applied time series econometrics and machine learning, he has made significant contributions to the field of marketing science. Yildirim has held academic positions at Lancaster University and has been a visiting researcher at Tilburg University. His research has been widely published in top-tier journals, influencing both academia and industry.

Profile

Education 🎓

Gokhan Yildirim earned his PhD in Business Administration and Quantitative Methods from Universidad Carlos III de Madrid (UC3M) in 2012, with a dissertation on marketing dynamics. His academic journey began with a BA in Business Administration (1999–2003) and an MSc in Quantitative Methods (2003–2006) from Marmara University, Istanbul. He also conducted research as a visiting scholar at Tilburg University, Netherlands, further strengthening his expertise in marketing analytics and econometrics.

Experience 👨‍🏫

Yildirim has been an Associate Professor of Marketing at Imperial College Business School since 2019, following his tenure as an Assistant Professor from 2016 to 2019. Before that, he was an Assistant Professor of Marketing Analytics at Lancaster University (2012–2016). His industry collaborations focus on marketing resource allocation, customer analytics, and data-driven decision-making. His research integrates econometric modeling and machine learning to optimize marketing strategies and enhance business performance.

Research Interests 🔬

Yildirim’s research centers on return on marketing investment, digital marketing effectiveness, and customer mindset metrics. He applies advanced econometric and machine learning techniques to analyze marketing resource allocation and long-term advertising impacts. His work explores how marketing strategies influence consumer behavior and business growth, contributing to both academic literature and real-world marketing practices

Awards & Recognitions 🏅

Yildirim has received several prestigious awards, including the 2017–2018 Gary Lilien ISMS-MSI-EMAC Practice Prize for his work on multichannel marketing at L’Occitane. He has also secured multiple research grants, such as the Wharton Customer Analytics Initiative (2015–2016) and the Spanish Ministry of Science and Innovation grants (2012–2018). His contributions have been recognized through funding from AiMark and other leading research bodies, further cementing his influence in marketing analytics.

Publications 📚

Pritpal Singh | Ambiguous set theory | Best Researcher Award

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Dr. Pritpal Singh | Ambiguous set theory | Best Researcher Award

Pritpal Singh is an Assistant Professor at the Department of Data Science and Analytics, Central University of Rajasthan, India. He earned his Ph.D. in Computer Science and Engineering from Tezpur (Central) University in 2015 and has held various academic and research positions in India, Taiwan, and Poland. His expertise includes soft computing, optimization algorithms, time series forecasting, image analysis, and machine learning. He has published extensively in high-impact journals like IEEE Transactions, Elsevier, and Springer. His research focuses on advanced computational techniques, including quantum-based optimization and fMRI data analysis. Dr. Singh has received prestigious research fellowships, including a Postdoctoral Fellowship from Taiwan’s Ministry of Science and Technology and an International Visiting Research Fellowship from Poland’s Foundation for Polish Science. His work significantly contributes to artificial intelligence, data science, and computational modeling, making him a key figure in these fields. 🚀📊📚

Profile

Education 🎓

Dr. Pritpal Singh obtained his Ph.D. in Computer Science and Engineering from Tezpur (Central) University, Assam, India, in 2015, specializing in soft computing applications for time series forecasting. He completed his Master in Computer Applications (MCA) from Dibrugarh University, Assam, in 2008, following a B.Sc. in Physics, Chemistry, and Mathematics from the same university in 2005. His academic journey began with Higher Secondary (2002) from the Assam Higher Secondary Education Council and HSLC (1999) from the Secondary Education Board of Assam. His doctoral dissertation focused on improving fuzzy time series forecasting models through hybridization with neural networks and optimization techniques like particle swarm optimization. His strong foundation in computational sciences, mathematics, and engineering has shaped his research in AI-driven predictive modeling, optimization, and data analytics. 🎓📚🔬

Experience 👨‍🏫

Dr. Singh has extensive academic and research experience. He is currently an Assistant Professor at the Central University of Rajasthan (since June 2022). Previously, he was an Assistant Professor at CHARUSAT University, Gujarat (2015-2019), and a Lecturer at Thapar University, Punjab (2013-2015). His research experience includes serving as an Adjunct Professor (Research) at Jagiellonian University, Poland (2020-2022) and a Postdoctoral Research Fellow at National Taipei University of Technology, Taiwan (2019-2020). Throughout his career, he has mentored students, led research projects, and contributed significantly to data science, artificial intelligence, and computational modeling. His global exposure has enriched his expertise in optimization, machine learning, and interdisciplinary AI applications. 🌍📊

Research Interests 🔬

Dr. Singh’s research revolves around ambiguous set theory, optimization algorithms, time series forecasting, image analysis, and machine learning. He specializes in hybrid computational techniques, particularly quantum-based optimization and soft computing applications. His work extends to fMRI data analysis, mathematical modeling, and simulation. His research has been published in leading journals such as IEEE Transactions on Systems, Elsevier’s Information Sciences, and Artificial Intelligence in Medicine. His focus on interdisciplinary AI applications, particularly in healthcare and data science, has positioned him as a key contributor to advancing machine learning methodologies. 🧠📊🤖Awards & Recognitions 🏅

Dr. Singh has received multiple prestigious fellowships and recognitions. In 2019, he was awarded a Postdoctoral Research Fellowship by the Ministry of Science and Technology, Taiwan. In 2020, he received the International Visiting Research Fellowship from the Foundation for Polish Science, Poland. His contributions to artificial intelligence, optimization, and data science have been recognized globally through research grants, invited talks, and publications in top-tier journals. His work in soft computing and AI-driven predictive modeling continues to impact both academic and industrial research. 🏅🎖️📜

Publications 📚

  • Scopus 1-2023: P. Singh, An investigation of ambiguous sets and their application to
    decision-making from partial order to lattice ambiguous sets. Decision Analytics
    Journal (Elsevier), 08, 100286, 2023.
  • Scopus 2-2023: P. Singh, A general model of ambiguous sets to a single-valued ambiguous numberswith aggregation operators. Decision Analytics Journal (Elsevier), 08,
    100260, 2023.
  • Scopus 3-2023: P. Singh, Ambiguous set theory: A new approach to deal with unconsciousness and ambiguousness of human perception. Journal of Neutrosophic and
    Fuzzy Systems (American Scientific Publishing Group), 05(01), 52–58, 2023.
  • Scopus 4-2022: P. Singh, Marcin W ˛atorek, Anna Ceglarek, Magdalena F ˛afrowicz, and
    Paweł O´swi˛ecimka, Analysis of fMRI Time Series: Neutrosophic-Entropy Based
    Clustering Algorithm. Journal of Advances in Information Technology, 13(3), 224–
    229, 2022.

Muhammad Waheed Rasheed | Artificial Intelligence | Best Researcher Award

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Mr. Muhammad Waheed Rasheed | Artificial Intelligence | Best Researcher Award

Research Assistant at COMSATS University Islamabad, Vehari Campus, Pakistan

Muhammad Waheed Rasheed is a dedicated mathematician and researcher known for his contributions to cryptography, fuzzy graph theory, and QSPR analysis. His academic and professional pursuits focus on creating innovative solutions to global challenges, particularly in molecular descriptors, graph theory, and their applications in chemistry and physics. With a passion for research and education, Mr. Rasheed embodies excellence in both theoretical and applied mathematics. His publications in high-impact journals like Frontiers in Chemistry and Frontiers in Physics reflect his ability to bridge disciplines and address real-world problems. As a motivated and dependable team player, he thrives in collaborative environments while excelling independently. His research outputs, which span drug efficacy studies and complex mathematical modeling, contribute significantly to scientific advancements and underscore his role as a rising star in the global mathematical community.

Profile

Scopus

Education 🎓

Mr. Rasheed earned an MS in Mathematics (2021–2023) and a BS (Hons) in Mathematics (2017–2021) from the University of Education Lahore, Pakistan, achieving CGPAs of 3.64/4.00 and 3.61/4.00, respectively. His coursework encompassed advanced topics such as algebraic graph theory, numerical methods, Galois theory, real analysis, and differential geometry. This robust educational foundation equipped him with the analytical and problem-solving skills needed to excel in multidisciplinary research areas, including graph theory and mathematical modeling.

Work Experience 💼

Muhammad Waheed Rasheed is an accomplished researcher with expertise in cryptography, fuzzy graph theory, and QSPR analysis. His work focuses on molecular descriptors, graph labeling, energy graphs, and metric dimensions, addressing challenges in networking and drug efficacy analysis. With five impactful publications in journals like Frontiers in Chemistry and Frontiers in Physics, he demonstrates excellence in both independent and collaborative research. His ability to tackle complex problems and deliver innovative solutions highlights his readiness for advanced research roles in academia and industry.

Research Interests

Mr. Rasheed’s research interests include cryptography, group theory, fuzzy graph theory, and QSPR analysis. He focuses on molecular descriptors, graph labeling, energy graphs, and metric dimensions, aiming to address critical issues in mathematics and its applications in healthcare and networking.

Research Skills

Muhammad Waheed Rasheed’s research interests lie at the intersection of advanced mathematics and real-world applications. He specializes in cryptography, fuzzy graph theory, and group theory, with a strong emphasis on molecular descriptors, graph labeling, energy graphs, and metric dimensions. His work extends to QSPR (Quantitative Structure-Property Relationship) analysis, where he investigates the properties of chemical compounds, such as alkaloids and medications, to improve therapeutic efficacy and understand their thermodynamic behavior. He is particularly passionate about exploring the role of graph theory in networking and healthcare, focusing on innovative solutions to complex problems. Through his interdisciplinary research, Mr. Rasheed aims to contribute significantly to global challenges, combining theoretical insights with practical applications in chemistry, physics, and beyond.

📚 Publications

Neighborhood Face Index: A New QSPR Approach for Predicting Physical Properties of Polycyclic Chemical Compounds

  • Authors: A. Raza, M.W. Rasheed, A. Mahboob, M. Ismaeel
  • Journal: International Journal of Quantum Chemistry
  • Year: 2024
  • Volume: 124(24), e27524
  • Citations: 0

Block Cipher Construction Using Minimum Spanning Tree from Graph Theory and Its Application with Image Encryption

  • Authors: M.W. Rasheed, A. Mahboob, M. Bilal, K. Shahzadi
  • Journal: Science Progress
  • Year: 2024
  • Volume: 107(4)
  • Citations: 0

Entropy Measures of Dendrimers Using Degree-Based Indices

  • Authors: A. Ovais, F. Yasmeen, M. Irfan, M.W. Rasheed, S. Kousar
  • Journal: South African Journal of Chemical Engineering
  • Year: 2024
  • Volume: 50, pp. 168–181
  • Citations: 0

Computing Connection-Based Topological Indices of Carbon Nanotubes

  • Authors: E.U. Haq, A. Mahboob, M.W. Rasheed, S. Sattar, M. Waqas
  • Journal: South African Journal of Chemical Engineering
  • Year: 2024
  • Volume: 48, pp. 121–129
  • Citations: 0

QSPR Analysis of Physicochemical Properties and Anti-Hepatitis Prescription Drugs Using a Linear Regression Model

  • Authors: A. Mahboob, M.W. Rasheed, A.M. Dhiaa, I. Hanif, L. Amin
  • Journal: Heliyon
  • Year: 2024
  • Volume: 10(4), e25908
  • Citations: 5

Approximating Properties of Chemical Solvents by Two-Dimensional Molecular Descriptors

  • Authors: A. Mahboob, M.W. Waheed Rasheed, I. Hanif, I. Siddique
  • Journal: International Journal of Quantum Chemistry
  • Year: 2024
  • Volume: 124(1), e27305
  • Citations: 3

Role of Molecular Descriptors in QSPR Analysis of Kidney Cancer Therapeutics

  • Authors: A. Mahboob, M.W. Rasheed, I. Hanif, L. Amin, A. Alameri
  • Journal: International Journal of Quantum Chemistry
  • Year: 2024
  • Volume: 124(1), e27241
  • Citations: 9

Face Irregular Evaluations of Family of Grids

  • Authors: J.H.H. Bayati, A. Ovais, A. Mahboob, M.W. Rasheed
  • Journal: AKCE International Journal of Graphs and Combinatorics
  • Year: 2024 (In Press)
  • Citations: 0

Enhancing Breast Cancer Treatment Selection Through 2TLIVq-ROFS-Based Multi-Attribute Group Decision Making

  • Authors: M.W. Rasheed, A. Mahboob, A.N. Mustafa, Z.A.A. Ali, Z.H. Feza
  • Journal: Frontiers in Artificial Intelligence
  • Year: 2024
  • Volume: 7, 1402719
  • Citations: 0

QSAR Modeling with Novel Degree-Based Indices and Thermodynamics Properties of Eye Infection Therapeutics

  • Authors: M.W. Rasheed, A. Mahboob, I. Hanif
  • Journal: Frontiers in Chemistry
  • Year: 2024
  • Volume: 12, 1383206
  • Citations: 0

Conclusion 

Muhammad Waheed Rasheed is a talented researcher whose academic achievements and innovative research demonstrate a promising career in mathematics and its applications. His dedication, interdisciplinary focus, and impactful publications make him a strong candidate for prestigious accolades and research opportunities.