Shanshan Wang | Machine Learning and Statistics | Best Researcher Award

Published on by Statistics

Best Researcher Award

Shanshan Wang,
University of Jinan

Shanshan Wang
Affiliation University of Jinan
Country China
Citations 1,094
h-index 12
i10 Index 13
Subject Area Computer Science and Technology
Event World Statistics Awards
ORCID 0000-0002-8620-9766

Shanshan Wang is a researcher affiliated with the University of Jinan, China, whose academic profile is situated within Computer Science and Technology. Available bibliometric information records 1,094 citations, an h-index of 12, and an i10 index of 13, providing measurable indicators of research visibility and scholarly influence.[1][2]

Abstract

Shanshan Wang, affiliated with the University of Jinan in China, is presented as a candidate for the Best Researcher Award based on documented academic indicators and a research focus in Computer Science and Technology. The profile records 1,094 citations, h-index 12, and i10 index 13, supporting assessment of scholarly activity.[1][2]

Keywords

  • Shanshan Wang
  • University of Jinan
  • Computer Science and Technology
  • Research Excellence
  • Bibliometric Impact
  • Best Researcher Award
  • World Statistics Awards

Introduction

Shanshan Wang is a researcher at the University of Jinan, China, working within Computer Science and Technology. The available academic indicators provide a quantitative basis for reviewing scholarly activity, including 1,094 citations, an h-index of 12, and an i10 index of 13. These measures support a structured assessment of research development.[1][2]

Research Profile

Wang’s research profile is associated with Computer Science and Technology and reflects an academic career focused on research and scholarly dissemination. Bibliometric information indicates sustained citation activity and documented influence within the scholarly record. The profile is additionally connected with ORCID identifier 0000-0002-8620-9766, supporting researcher identity and publication disambiguation.[1][2]

Research Contributions

Wang’s documented contribution is represented through research activity in Computer Science and Technology and its associated scholarly impact. The available citation indicators suggest that published research has received attention from subsequent academic work. An h-index of 12 and i10 index of 13 provide complementary measures for evaluating citation distribution and the presence of repeatedly cited publications.[1]

Publications

Wang’s scholarly publications form an important component of the research profile and provide the primary basis for evaluating academic contributions. The supplied information confirms a Google Scholar profile containing the researcher’s indexed works, while the available bibliometric indicators record 1,094 citations and an i10 index of 13. Individual DOI details should be verified against source records.[1][3]

Research Impact

Research impact can be assessed through citation activity, publication visibility, and sustained scholarly recognition. Wang’s reported total of 1,094 citations and h-index of 12 indicates that the researcher’s work has been referenced across the academic literature. These indicators provide quantitative evidence for considering the reach and influence of contributions within Computer Science and Technology.[1]

Award Suitability

The available profile supports consideration of Shanshan Wang for a Best Researcher Award through a combination of institutional affiliation, subject-area relevance, citation performance, and identifiable scholarly output. The reported h-index of 12, i10 index of 13, and 1,094 citations provide measurable evidence for evaluation, subject to the award’s formal eligibility and verification procedures.[1][2]

Conclusion

Shanshan Wang’s academic profile demonstrates research engagement in Computer Science and Technology, supported by measurable citation indicators and researcher-identification records. The reported 1,094 citations, h-index of 12, and i10 index of 13 establish a quantitative foundation for recognition. Final award assessment should consider verified publications, originality, contribution, and documented research significance.[1][2]

References

  1. ORCID. (n.d.). ORCID record for Shanshan Wang, ORCID 0000-0002-8620-9766.

    https://orcid.org/0000-0002-8620-9766

  2. Google Scholar. (n.d.). Shanshan Wang — Google Scholar profile and publications.

    https://scholar.google.com/citations?hl=zh-CN&user=GMgHNBUAAAAJ&view_op=list_works&sortby=pubdate

  3. World Statistics Awards. (n.d.). World Statistics Awards.

    https://statisticsaward.com/

Costin Untaroiu | Statistical Modeling and Simulation | Innovative Research Award

Published on by Statistics

 

Innovative Research Award

Costin Untaroiu
Affiliation Virginia Tech
Country United States
Scopus ID 8626670800
Documents 148
Citations 2,601
h-index 28
Subject Area Tire-Soil Simulations
Event World Statistics Awards
ORCID 0000-0002-1813-669X

Costin Untaroiu,
Virginia Tech.

Costin Untaroiu is a professor at Virginia Tech whose research integrates biomechanics, solid mechanics, dynamics, and tire–soil modeling. His work applies computational and experimental methods to transportation safety, injury biomechanics, and terrain interaction, providing interdisciplinary approaches for understanding complex mechanical systems and improving simulation-based engineering analysis, design, and practice today. [1]

Abstract

Costin Untaroiu’s research combines computational mechanics, biomechanics, transportation safety, and tire–soil simulation. His work includes numerical modeling, experimental validation, finite-element analysis, and soil characterization. The research portfolio demonstrates interdisciplinary engagement with technically complex engineering problems and provides a scholarly basis for consideration for an Innovative Research Award. [1] [2]

Keywords

  • Costin Untaroiu
  • Innovative Research Award
  • Tire–Soil Simulation
  • Computational Mechanics
  • Biomechanics
  • Finite-Element Modeling
  • Transportation Safety
  • Virginia Tech

Introduction

Costin Untaroiu is a Virginia Tech professor whose research integrates biomechanics, solid mechanics, dynamics, and tire–soil modeling. His work applies computational and experimental methods to transportation safety, injury biomechanics, and terrain interaction, providing interdisciplinary approaches for understanding complex mechanical systems and improving simulation-based engineering analysis, design, and practice today. [1]

Research Profile

Untaroiu’s research profile spans biomechanics, tissue engineering, dynamics and control, solid mechanics, and tire–soil modelling. At Virginia Tech, he is associated with the Center for Injury Biomechanics and contributes to research involving finite-element analysis, numerical simulation, and engineering optimization across transportation, mechanical-system applications, and interdisciplinary research today globally. [1]

Research Contributions

His contributions include numerical modeling of tire–soil interaction, soil constitutive parameter identification, pedestrian injury analysis, and finite-element representations of human body structures. Recent work addresses soil compaction and tire loading through laboratory testing and validated numerical approaches, demonstrating a research program that connects computational mechanics with engineering problems today across applications. [2] [3]

Publications

Untaroiu has contributed to a substantial body of peer-reviewed research across biomechanics, transportation safety, and terramechanics. Representative publications address soil constitutive modeling, tire–soil interaction, pedestrian finite-element modeling, and material characterization. These studies demonstrate methodological breadth and continued engagement with simulation, validation, experimental measurement, and engineering applications internationally in peer-reviewed literature. [1] [3] [4]

Research Impact

The research has relevance to transportation safety, vehicle and tire engineering, agricultural machinery, and computational biomechanics. Studies combining experimental measurements with numerical models can support improved prediction, validation, and design decisions. His publication record and indexed research activity indicate sustained scholarly engagement across interdisciplinary engineering domains at Virginia Tech and beyond. [1] [2] [3]

Award Suitability

The Innovative Research Award recognizes researchers whose work demonstrates methodological originality, interdisciplinary value, and meaningful engineering relevance. Untaroiu’s documented research in tire–soil modeling, biomechanics, numerical simulation, and validation aligns with these dimensions. His record of peer-reviewed publications and research leadership provides a substantive basis for consideration under an innovation-focused academic recognition framework. [1] [2] [3]

Conclusion

Costin Untaroiu represents an interdisciplinary research profile connecting computational mechanics, biomechanics, transportation safety, and tire–soil simulation. His work combines modeling, experimentation, and validation to address technically complex problems. The documented research portfolio provides a strong scholarly foundation for recognition through an Innovative Research Award within an engineering-focused academic context overall. [1] [3] [4]

References

  1. Virginia Tech. (n.d.). Costin Untaroiu — Biomedical Engineering and Mechanics. Virginia Tech.

    https://bme.vt.edu/people/faculty/untaroiu-c.html

  2. Shokanbi, A., Jasoliya, D., & Untaroiu, C. (2025). Parameter Identification of Soil Material Model for Soil Compaction Under Tire Loading: Laboratory vs. In-Situ Cone Penetrometer Test Data. Agriculture, 15(20), 2142.

    https://doi.org/10.3390/agriculture15202142

  3. Untaroiu, C. D. (2013). The Influence of the Specimen Shape and Loading Conditions on the Parameter Identification of a Viscoelastic Brain Model. Computational and Mathematical Methods in Medicine, 2013, 460413.

    https://doi.org/10.1155/2013/460413

  4. Untaroiu, C. D., Pak, W., Meng, Y., Schap, J., Koya, B., & Gayzik, F. (2018). A Finite Element Model of a Midsize Male for Simulating Pedestrian Accidents. Journal of Biomechanical Engineering, 140(1).

    https://doi.org/10.1115/1.4037854

  5. Elsevier. (n.d.). Scopus author details: Costin Untaroiu, Author ID 8626670800. Scopus.

    https://www.scopus.com/pages/authors/86266

Esra Cakir | Fuzzy Statistics and Uncertainty Modelling | Innovative Research Award

Published on by Statistics

Innovative Research Award

Esra Cakir,
Affiliation Galatasaray University
Country Turkey
Scopus ID 57210106850
Documents 50
Citations 286
h-index 9
Subject Area Fuzzy set theory
Event World Statistics Awards
ORCID 0000-0003-4134-7679

Esra Cakir,
Galatasaray University

Esra Cakir, affiliated with Galatasaray University, has contributed to research in fuzzy set theory through scholarly publications addressing mathematical modeling, uncertainty analysis, and decision-making methodologies. Her publication record, citation performance, and continuing academic engagement demonstrate sustained contributions to statistics and applied mathematical sciences within an international research environment.[1]

Abstract

Esra Cakir’s academic activities focus on fuzzy set theory and related statistical methodologies that support uncertainty modeling, optimization, and intelligent decision-making. Her research portfolio reflects continued publication in peer-reviewed journals and measurable scholarly influence through citations, contributing to mathematical sciences and interdisciplinary statistical applications.[1] [2]

Keywords

Fuzzy Set Theory, Statistics, Decision Making, Mathematical Modeling, Optimization, Uncertainty Analysis, Applied Mathematics, Data Analysis, Intelligent Systems, Scientific Research.[2]

Introduction

Esra Cakir has established an academic presence through research in fuzzy set theory, emphasizing mathematical approaches for uncertainty and decision analysis. Her work supports statistical modeling and interdisciplinary applications while contributing to peer-reviewed scientific literature that advances quantitative research methodologies across multiple domains.[1] [2]

Research Profile

Affiliated with Galatasaray University, Esra Cakir has authored fifty indexed publications and accumulated 286 citations with an h-index of nine. Her research addresses fuzzy systems, mathematical reasoning, and statistical techniques, demonstrating consistent scholarly productivity and international academic visibility through recognized indexing databases.[1] [3]

Research Contributions

Her contributions include developing and applying fuzzy set methodologies for uncertainty evaluation, decision support, and mathematical analysis. These studies encourage improved analytical frameworks across statistics and related disciplines while promoting interdisciplinary collaboration and methodological refinement within contemporary quantitative research environments.[2] [3]

Publications

Esra Cakir’s publication record comprises fifty Scopus-indexed documents covering fuzzy mathematics, statistical modeling, and decision sciences. These publications demonstrate continuing research activity, collaboration with academic peers, and dissemination of findings through internationally recognized scholarly journals and conference proceedings.[1] [4]

Research Impact

With 286 citations and an h-index of nine, her research demonstrates measurable academic influence. Citation performance indicates that her published studies continue supporting subsequent investigations, reflecting sustained relevance within fuzzy set theory, statistical methodologies, and interdisciplinary mathematical research communities.[1] [3]

Award Suitability

The Innovative Research Award appropriately recognizes sustained scholarly productivity, meaningful publication output, and contributions to fuzzy set theory. Her documented research achievements, citation record, and continuing engagement with advanced statistical methodologies align with the objectives of international academic recognition programs.[1] [2]

Conclusion

Esra Cakir’s academic profile reflects continuous contributions to fuzzy set theory through publications, citations, and collaborative research. Her scholarly achievements demonstrate professional consistency and support her recognition within the World Statistics Awards as a researcher contributing to contemporary statistical and mathematical sciences.[1] [3]

References

  1. Elsevier. (n.d.). Scopus author details: Esra Cakir, Author ID 57210106850. Scopus.

    https://www.scopus.com/pages/authors/57210106850

  2. ORCID. (n.d.). Esra Cakir ORCID Record: 0000-0003-4134-7679.

    https://orcid.org/0000-0003-4134-7679

  3. Çakır, E. (2026). Energy-efficient and sustainable milk-run optimization for e-scooter battery routing under fuzzy time windows. IEEE Transactions on Industry Applications.

    https://doi.org/10.1109/TIA.2026.3680469

  4. World Statistics Awards. (n.d.). Innovative Research Award.

    https://statisticsaward.com

Pei Zhang | Machine Learning and Statistics | Innovative Research Award

Published on by Statistics

Innovative Research Award

Pei Zhang,
Tianjin University

Pei Zhang
Affiliation Tianjin University
Country China
Scopus ID 56137754500
Documents 259
Citations 6861
h-index 37
Subject Area Artificial intelligence applications in power systems; power system planning and operation; reliability assessment; stability and control; risk assessment.
Event World Statistics Awards
ORCID 0000-0001-9706-2854

The Innovative Research Award recognizes scholarly excellence demonstrated through impactful research, sustained publication activity, and contributions to scientific advancement. Pei Zhang’s research portfolio reflects significant work in artificial intelligence applications for power systems, reliability assessment, operational planning, and risk analysis, supporting consideration for recognition within the World Statistics Awards.[1]

Abstract

Pei Zhang has established an extensive research record focusing on artificial intelligence, power system reliability, planning, operation, and stability. His scholarly output demonstrates sustained contributions through peer-reviewed publications, interdisciplinary collaborations, and measurable citation performance, indicating notable influence within modern electrical power engineering research.[1]

Keywords

  • Artificial Intelligence
  • Power Systems
  • Reliability Assessment
  • Power System Planning
  • Risk Assessment
  • World Statistics Awards

Introduction

Pei Zhang’s research centers on advancing intelligent methodologies for modern power systems through artificial intelligence, operational optimization, reliability analysis, and stability evaluation. His work supports efficient energy management while addressing practical engineering challenges and contributing to the scientific literature in electrical power engineering and data-driven decision making.[2]

Research Profile

Affiliated with Tianjin University, Pei Zhang has produced an extensive publication portfolio indexed in Scopus. His research spans artificial intelligence applications, power system planning, operational optimization, reliability assessment, stability analysis, and quantitative risk evaluation, reflecting sustained academic productivity across multidisciplinary engineering domains.[1]

Research Contributions

Research contributions include developing analytical models, optimization techniques, and intelligent computational approaches that improve power system reliability and operational efficiency. His studies integrate advanced algorithms with engineering applications, supporting informed planning, secure system operation, and evidence-based decision-making for evolving energy infrastructures.[3]

Publications

The Scopus database records 259 scholarly publications authored or co-authored by Pei Zhang. These publications appear in recognized international journals and conference proceedings, covering artificial intelligence, electrical engineering, energy systems, optimization, reliability evaluation, and advanced computational methodologies with significant citation visibility.[1]

Research Impact

With 6,861 citations and an h-index of 37, Pei Zhang’s publications demonstrate sustained scholarly influence. Citation metrics indicate broad recognition within the research community, while interdisciplinary collaborations contribute to advances in intelligent power systems, engineering reliability, and practical energy management solutions.[1]

Award Suitability

Based on publication volume, citation performance, interdisciplinary research, and internationally indexed scholarly output, Pei Zhang demonstrates qualifications consistent with evaluation for the Innovative Research Award. His sustained scientific productivity and measurable research impact align with commonly recognized academic excellence criteria.[1]

Conclusion

Pei Zhang has developed a distinguished academic profile through continuous research in artificial intelligence and power systems. His publication record, citation metrics, and engineering contributions collectively demonstrate meaningful scholarly influence, providing a strong academic foundation for consideration within international research recognition programs.[1]

References

  1. Elsevier. (n.d.). Scopus Author Details: Pei Zhang, Author ID 56137754500. Scopus.https://www.scopus.com/authid/detail.uri?authorId=56137754500

  2. Zhang, P., Liu, C., Chu, Z., Cao, J., & Li, C. (2026). Time-domain simulation based on physics-informed DeepONet. Energy and AI.

    https://doi.org/10.1016/j.egyai.2026.100838

  3. Deng, F., Wang, Z., Shen, Y., Wang, J., Luo, W., Wei, B., Li, Z., & Zhang, P. (2026). Interval prediction of distributed photovoltaic power integrating spatial collaborative training and data fluctuation trend perception. Sustainable Energy, Grids and Networks, 46, 102163.

    https://doi.org/10.1016/j.segan.2026.102163

Yiran Li | Multivariate Statistical Analysis | Young Researcher Award

Published on by Statistics

Dr. Yiran Li | Multivariate Statistical Analysis | Young Researcher Award

Korea University | South Korea

A researcher in counseling education with an interdisciplinary foundation in counseling psychology, social psychology, and public health, their academic work focuses on understanding complex psychosocial dynamics affecting individuals and communities. Their research emphasizes critical areas such as workplace bullying, post-traumatic stress disorder symptoms, emotional dysregulation, and non-suicidal self-injury, integrating these with protective factors like mindfulness and compassionate engagement. Utilizing advanced quantitative approaches, including longitudinal designs and autoregressive cross-lagged models, their work contributes to identifying causal relationships and long-term behavioral patterns. Their scholarly interests extend to collective flourishing, social capital, and strategic human resource management, highlighting the intersection between mental health and organizational environments. Ongoing research includes panel data studies on multicultural adolescents, aiming to explore developmental, social, and psychological outcomes in diverse populations. With experience in teaching and academic research, they contribute to higher education through both instruction and institutional research initiatives. Their work has been recognized through multiple academic honors, particularly for excellence in quantitative research and contributions to human resource development and management. Overall, their research advances evidence-based understanding of trauma, resilience, and social well-being within both individual and organizational contexts.

Citation Metrics (Scopus)

80
60
40
20
0

Citations
47

Documents
12

h-index
4

Citations

Documents

h-index


View SCOPUS Profile

Featured Publications

Jinfa Zhang | Statistical Applications in Engineering | Research Excellence Award

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Dr. Jinfa Zhang | Statistical Applications in Engineering | Research Excellence Award

China University of Petroleum (Beijing) | China 

The research profile reflects a strong and continuous focus on petroleum engineering, Statistical Applications in Engineering with specialized expertise in rock mechanics, geomechanics, lost circulation control, reservoir stimulation, and enhanced oil and gas recovery. Advanced doctoral research concentrates on the mechanical behavior of reservoir rocks, wellbore stability, and lost circulation mechanisms, integrating theoretical modeling with practical engineering applications. Master’s-level research emphasized oil and gas reservoir stimulation technologies, enhanced recovery methods, numerical reservoir simulation, and optimization techniques, supported by a strong academic performance and rigorous coursework in advanced reservoir engineering, fluid phase equilibria, and simulation software applications. Undergraduate training provided a solid foundation in drilling engineering, completion engineering, rock mechanics, porous media flow, oilfield chemistry, and production engineering. The research experience is complemented by extensive proficiency in industry-standard professional software for fracturing design, reservoir simulation, curve fitting, programming, and geospatial analysis, enabling comprehensive data-driven studies. Practical exposure through geological fieldwork and petroleum production training strengthened the ability to connect theoretical research with field-scale operations. Academic excellence is demonstrated through competitive scholarships, innovation and design competitions, and national-level recognitions, highlighting strong research capability, interdisciplinary technical skills, and potential for impactful contributions to petroleum engineering research and technology development.

Citation Metrics (Scopus)

40
30
20
10
0

Citations
23

Documents
9

h-index
2

Citations

Documents

h-index


View Scopus Profile

Featured Publications

Jian Xia | Artificial Intelligence in Statistics | Research Excellence Award

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Dr. Jian Xia | Artificial Intelligence in Statistics | Research Excellence Award

Hubei University of Automotive Industry | China

Dr. Jian Xia is a dedicated materials scientist specializing in next-generation electronic and photonic devices, with a strong academic foundation and a growing record of impactful research. He obtained his Ph.D. degree from the School of Materials Science and Engineering at Huazhong University of Science and Technology, where he developed expertise in resistive switching devices, phase-change materials, and advanced optical memory technologies. After completing his doctoral studies, he joined the Hubei University of Automotive Technology as a lecturer, contributing actively to both teaching and research in the field of electronic materials and integrated circuit design. Dr. Xia’s research interests encompass memristors, phase-change memory, and photonic neuromorphic devices, all of which hold promising applications in high-performance computing, data storage, and artificial intelligence hardware. He has undertaken notable research projects, including the Open Fund of the Hubei Key Laboratory of Energy Storage and Power Battery and the Doctoral Scientific Research Foundation of Hubei University of Automotive Technology. With a citation index of 361 and a research portfolio of 20 SCI-indexed publications, Dr. Xia has contributed articles to leading international journals such as Nature Communications, Laser & Photonics Reviews, ACS Photonics, Applied Physics Letters, IEEE Electron Device Letters, and Science China Materials. His innovative contributions are further demonstrated by nine patents that are either published or under review, highlighting his commitment to advancing practical and technologically significant developments in electronic device engineering. Although he has yet to hold editorial appointments or professional memberships, his scholarly influence continues to grow through strong research visibility and future collaboration potential. Dr. Xia maintains an active academic presence on platforms such as ResearchGate and continues to advance pioneering research aimed at developing energy-efficient, high-density, and neuromorphic computing devices to meet the evolving demands of modern information technology.

Citation Metrics (Scopus)

400
300
200
100
0

Citations
361

Documents
7

h-index
5

Citations

Documents

h-index


View Scopus Profile

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Vikas Mehta | Statistical Computing and Programming | Research Excellence Award

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Dr. Vikas Mehta | Statistical Computing and Programming | Research Excellence Award

Korean National Institute for International Education | South Korea

Dr. Vikas Mehta is a structural engineer and researcher specializing in seismic performance optimization, sustainable construction materials, and the application of advanced computational and machine learning methodologies to civil infrastructure systems. He completed his Ph.D. in Civil Engineering at Keimyung University, South Korea, where his award-winning doctoral research introduced innovative modifier-based and data-driven techniques for improving shear strength prediction and design accuracy in reinforced concrete beam-column joints. His expertise spans nonlinear finite element modeling, fragility analysis, physics-informed and graph-based machine learning, geospatial analytics, and performance-based seismic assessment, supported by strong proficiency in ETABS, OpenSees, SeismoSoft, Abaqus, MATLAB, Q-GIS, SPSS, Python, PyTorch, WEKA, and OriginPro. Dr. Mehta serves as a Postdoctoral Researcher at the Chonnam National University R&BD Foundation, contributing to advanced safety technologies for nuclear power plant structures under extreme hazard scenarios, including buckling resistance enhancement, retrofit optimization, and complex wind–terrain interaction studies. His professional background includes academic appointments in structural and construction engineering, where he taught subjects in earthquake engineering, finite element analysis, and structural systems while supervising graduate research and contributing to curriculum and laboratory development. Dr. Mehta has authored a substantial body of SCI-indexed research on seismic damage prediction, torsional behavior modeling, hybrid AI-mechanics frameworks, recycled and sustainable materials, computational methods, and structural performance evaluation, complemented by multiple patents in construction materials, damping devices, and waste-based composites. He has presented at leading international and national conferences and contributed to funded collaborative research, including projects involving global academic and industry partners. His professional affiliations include membership in ASCE, the Institute of Physics (AMInstP), IAEME (Fellow), and licensure as a Class-A engineer under the Himachal Pradesh Town and Country Planning Act. Dr. Mehta’s contributions to structural engineering and computational mechanics continue to gain international visibility, reflected in an h-index of 7, over 172 citations, and more than 19 published documents, underscoring his growing influence in machine learning–driven structural design, seismic resilience, and sustainable construction innovation.

Profiles: Scopus | Orcid

Featured Publications

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Corrigendum to “Adaptive simulation and data-driven hybrid modeling for predicting shear strength and failure modes of interior reinforced concrete beam-column joints”.

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Predictive framework for shear strength and failure modes of exterior reinforced concrete beam–column joints using machine learning. Structural Concrete. h.

Sagar, G. S., Mukthi, S., & Mehta, V. (2025). Analyzing compressive, flexural, and tensile strength of concrete incorporating used foundry sand: Experimental and machine learning insights. Archives of Computational Methods in Engineering.

Mehta, V., Thakur, M. S., & Chey, M. H. (2025). Enhancing seismic design accuracy of RC beam-column joints: Modifier-based approach for shear strength predictions. Structures.

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Adaptive simulation and data-driven hybrid modeling for predicting shear strength and failure modes of interior reinforced concrete beam-column joints. Structures.

Michael Pitton | Descriptive and Inferential Statistics | Best Researcher Award

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Prof. Dr. Michael Pitton | Descriptive and Inferential Statistics | Best Researcher Award

Medical University of Mainz | Germany

Professor Dr. Michael Pitton is a distinguished German physician-scientist and expert in diagnostic and interventional radiology. A graduate of the Johannes Gutenberg University Mainz, he completed his medical studies and advanced clinical training in internal medicine, cardiology, radiology, and neuroradiology at leading German university hospitals, including the University Medical Center Mainz and the Deutsches Herzzentrum Berlin. His academic achievements include a habilitation on functional and morphological aspects of endovascular aneurysm therapy, followed by his appointment as university lecturer and senior consultant in interventional radiology. Professor Pitton has held successive leadership positions and currently serves as the Acting Director of the Department of Diagnostic and Interventional Radiology and Head of the Section of Interventional Radiology at the University Medical Center Mainz. He also holds European Board Certification in Interventional Radiology (EBIR) and the European Certification for Endovascular Specialists (CIRSE) and is a certified DEGIR instructor across all modules. Combining clinical excellence with managerial insight, he earned a Master of Health Business Administration, reflecting his engagement in healthcare management and innovation. Professor Pitton has an extensive scientific record, with approximately 127 publications, an h-index of around 33, and more than 6,771 citations, underscoring his influence in vascular and interventional radiology. His research contributions have advanced the understanding and treatment of aneurysms, transjugular intrahepatic portosystemic shunt (TIPS) interventions, and image-guided oncologic therapies. Recognized with numerous national and international awards, his work bridges academic medicine, translational research, and health leadership. Professor Pitton exemplifies excellence in clinical radiology, academic scholarship, and interdisciplinary collaboration, contributing significantly to the development of interventional radiology in Europe.

Profiles: Scopus | Orcid

Featured Publications

Graafen, D., Bart, W., Halfmann, M. C., Müller, L., Hobohm, L., Yang, Y., Neufang, A., Espinola-Klein, C., Pitton, M. B., Kloeckner, R., Varga-Szemes, A., & Emrich, T. (2022). In vitro and in vivo optimized reconstruction for low-keV virtual monoenergetic photon-counting detector CT angiography of lower legs.

Gairing, S. J., Kuchen, R., Müller, L., Cankaya, A., Weerts, J., Kapucu, A., Sachse, S., Zimpel, C., Stoehr, F., Pitton, M. B., Mittler, J., Straub, B. K., Marquardt, J. U., Schattenberg, J. M., Labenz, C., Kloeckner, R., Weinmann, A., Galle, P. R., Wörns, M. A., & Foerster, F. (2022.). 13C-Methacetin breath test predicts survival in patients with hepatocellular carcinoma undergoing transarterial chemoembolization.

Müller, L., Hahn, F., Mähringer-Kunz, A., Stoehr, F., Gairing, S. J., Foerster, F., Weinmann, A., Galle, P. R., Mittler, J., Pinto Dos Santos, D., Pitton, M. B., Düber, C., Fehrenbach, U., Auer, T. A., Gebauer, B., & Kloeckner, R. (2022). Prevalence and clinical significance of clinically evident portal hypertension in patients with hepatocellular carcinoma undergoing transarterial chemoembolization.

Yohanna Kusuma | Multivariate Statistical Analysis | Best Researcher Award

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Dr. Yohanna Kusuma | Multivariate Statistical Analysis | Best Researcher Award

The Royal Melbourne Hospital-The University of Melbourne | Australia

Dr. Yohanna Kusuma is an Australian-trained, internationally recognised neurologist and academic whose clinical and research work bridges acute stroke, neuroimaging, neurosonology, and movement disorders, with a strong translational focus across the Asia-Pacific region. She obtained her neurology specialist qualification from the University of Indonesia with honours, completed advanced fellowships in neurosonology and stroke at leading institutions in Singapore, and earned a PhD from Deakin University supported by an international scholarship, focusing on advanced CT-perfusion imaging in acute ischaemic stroke and the influence of ethnicity on imaging and clinical outcomes. She holds Fellowship of the Royal Australasian College of Physicians, qualifying her as a Consultant Neurologist in Australia. Dr Kusuma serves as Chief Investigator of the AI-powered SERENA platform for real-time stroke triage and decision support, leads the multinational APEX registry on acute ischaemic stroke with cancer spanning nine Asia–Pacific countries, and co-supervises PhD and honours students at Deakin University. She holds senior appointments in both Australia and Indonesia, including Senior Consultant Neurology at Metropolitan Medical Centre Hospital in Jakarta and Senior Research Fellow at The University of Melbourne. Her professional leadership includes representing Indonesia on the Asia Pacific Stroke Organisation and the Asian Stroke Advisory Panel, serving on the Education Council of the Australian Stroke Academy, and having previously served as a Co-opted Board Member of the World Stroke Organisation. Actively engaged in education and training, she has organised and delivered numerous neurosonology and stroke imaging workshops across the Asia-Pacific. Her research output is extensive, with an h-index of 4 and 144 citations, 13 peer-reviewed publications, book chapters, and international presentations. Dr Kusuma exemplifies a clinician-scientist who integrates cutting-edge imaging, neurosonology, and translational stroke research while advancing global collaborations in academic neurology, clinical innovation, and medical education.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications