Kaikai Zhang | Leadership Development | Research Excellence Award | 2860 Published on 23/03/2026 by Human Resources Management Kaikai Zhang | Leadership Development | Research Excellence Award Associate Professor | The University of China University of Mining and Technology | China Dr. Kaikai Zhang is a prominent researcher in environmental science, with expertise in contamination remediation and biogeochemical processes. His work focuses on understanding and mitigating the impacts of heavy metals and persistent organic pollutants in soil and groundwater systems. He has developed innovative approaches involving biochar materials, microbial remediation, and advanced chemical treatments to improve environmental sustainability. His research integrates laboratory investigations with practical applications, ensuring long-term effectiveness of remediation strategies. With 23 publications, 996 citations, and an h-index of 14, his contributions demonstrate strong scientific impact and international recognition. His studies provide valuable insights into pollutant transformation, degradation mechanisms, and sustainable environmental solutions, supporting global efforts toward ecological restoration, pollution control, and the advancement of efficient and scalable remediation technologies. Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index View Scopus Profile View ORCID Profile View Research Gate Profile Featured Publications Engineered Biochar Composite with Minerals: Organo-Mineral Interactions, Physicochemical Changes, and Practical Applications – Water Research, 2026 Synergistic Pyrogenic Carbon-Microbial Dehalogenator for Removal of Persistent “Forever Chemicals” – Environmental Research, 2026
Dr. Kaikai Zhang is a prominent researcher in environmental science, with expertise in contamination remediation and biogeochemical processes. His work focuses on understanding and mitigating the impacts of heavy metals and persistent organic pollutants in soil and groundwater systems. He has developed innovative approaches involving biochar materials, microbial remediation, and advanced chemical treatments to improve environmental sustainability. His research integrates laboratory investigations with practical applications, ensuring long-term effectiveness of remediation strategies. With 23 publications, 996 citations, and an h-index of 14, his contributions demonstrate strong scientific impact and international recognition. His studies provide valuable insights into pollutant transformation, degradation mechanisms, and sustainable environmental solutions, supporting global efforts toward ecological restoration, pollution control, and the advancement of efficient and scalable remediation technologies. Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index View Scopus Profile View ORCID Profile View Research Gate Profile Featured Publications Engineered Biochar Composite with Minerals: Organo-Mineral Interactions, Physicochemical Changes, and Practical Applications – Water Research, 2026 Synergistic Pyrogenic Carbon-Microbial Dehalogenator for Removal of Persistent “Forever Chemicals” – Environmental Research, 2026
Dr. Kaikai Zhang is a prominent researcher in environmental science, with expertise in contamination remediation and biogeochemical processes. His work focuses on understanding and mitigating the impacts of heavy metals and persistent organic pollutants in soil and groundwater systems. He has developed innovative approaches involving biochar materials, microbial remediation, and advanced chemical treatments to improve environmental sustainability. His research integrates laboratory investigations with practical applications, ensuring long-term effectiveness of remediation strategies. With 23 publications, 996 citations, and an h-index of 14, his contributions demonstrate strong scientific impact and international recognition. His studies provide valuable insights into pollutant transformation, degradation mechanisms, and sustainable environmental solutions, supporting global efforts toward ecological restoration, pollution control, and the advancement of efficient and scalable remediation technologies. Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index View Scopus Profile View ORCID Profile View Research Gate Profile Featured Publications Engineered Biochar Composite with Minerals: Organo-Mineral Interactions, Physicochemical Changes, and Practical Applications – Water Research, 2026 Synergistic Pyrogenic Carbon-Microbial Dehalogenator for Removal of Persistent “Forever Chemicals” – Environmental Research, 2026
Dr. Kaikai Zhang is a prominent researcher in environmental science, with expertise in contamination remediation and biogeochemical processes. His work focuses on understanding and mitigating the impacts of heavy metals and persistent organic pollutants in soil and groundwater systems. He has developed innovative approaches involving biochar materials, microbial remediation, and advanced chemical treatments to improve environmental sustainability. His research integrates laboratory investigations with practical applications, ensuring long-term effectiveness of remediation strategies. With 23 publications, 996 citations, and an h-index of 14, his contributions demonstrate strong scientific impact and international recognition. His studies provide valuable insights into pollutant transformation, degradation mechanisms, and sustainable environmental solutions, supporting global efforts toward ecological restoration, pollution control, and the advancement of efficient and scalable remediation technologies. Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index View Scopus Profile View ORCID Profile View Research Gate Profile Featured Publications Engineered Biochar Composite with Minerals: Organo-Mineral Interactions, Physicochemical Changes, and Practical Applications – Water Research, 2026 Synergistic Pyrogenic Carbon-Microbial Dehalogenator for Removal of Persistent “Forever Chemicals” – Environmental Research, 2026
Dr. Kaikai Zhang is a prominent researcher in environmental science, with expertise in contamination remediation and biogeochemical processes. His work focuses on understanding and mitigating the impacts of heavy metals and persistent organic pollutants in soil and groundwater systems. He has developed innovative approaches involving biochar materials, microbial remediation, and advanced chemical treatments to improve environmental sustainability. His research integrates laboratory investigations with practical applications, ensuring long-term effectiveness of remediation strategies. With 23 publications, 996 citations, and an h-index of 14, his contributions demonstrate strong scientific impact and international recognition. His studies provide valuable insights into pollutant transformation, degradation mechanisms, and sustainable environmental solutions, supporting global efforts toward ecological restoration, pollution control, and the advancement of efficient and scalable remediation technologies. Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index View Scopus Profile View ORCID Profile View Research Gate Profile Featured Publications Engineered Biochar Composite with Minerals: Organo-Mineral Interactions, Physicochemical Changes, and Practical Applications – Water Research, 2026 Synergistic Pyrogenic Carbon-Microbial Dehalogenator for Removal of Persistent “Forever Chemicals” – Environmental Research, 2026
Dr. Kaikai Zhang is a prominent researcher in environmental science, with expertise in contamination remediation and biogeochemical processes. His work focuses on understanding and mitigating the impacts of heavy metals and persistent organic pollutants in soil and groundwater systems. He has developed innovative approaches involving biochar materials, microbial remediation, and advanced chemical treatments to improve environmental sustainability. His research integrates laboratory investigations with practical applications, ensuring long-term effectiveness of remediation strategies. With 23 publications, 996 citations, and an h-index of 14, his contributions demonstrate strong scientific impact and international recognition. His studies provide valuable insights into pollutant transformation, degradation mechanisms, and sustainable environmental solutions, supporting global efforts toward ecological restoration, pollution control, and the advancement of efficient and scalable remediation technologies. Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index View Scopus Profile View ORCID Profile View Research Gate Profile Featured Publications Engineered Biochar Composite with Minerals: Organo-Mineral Interactions, Physicochemical Changes, and Practical Applications – Water Research, 2026 Synergistic Pyrogenic Carbon-Microbial Dehalogenator for Removal of Persistent “Forever Chemicals” – Environmental Research, 2026
Dr. Kaikai Zhang is a prominent researcher in environmental science, with expertise in contamination remediation and biogeochemical processes. His work focuses on understanding and mitigating the impacts of heavy metals and persistent organic pollutants in soil and groundwater systems. He has developed innovative approaches involving biochar materials, microbial remediation, and advanced chemical treatments to improve environmental sustainability. His research integrates laboratory investigations with practical applications, ensuring long-term effectiveness of remediation strategies. With 23 publications, 996 citations, and an h-index of 14, his contributions demonstrate strong scientific impact and international recognition. His studies provide valuable insights into pollutant transformation, degradation mechanisms, and sustainable environmental solutions, supporting global efforts toward ecological restoration, pollution control, and the advancement of efficient and scalable remediation technologies. Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index View Scopus Profile View ORCID Profile View Research Gate Profile Featured Publications Engineered Biochar Composite with Minerals: Organo-Mineral Interactions, Physicochemical Changes, and Practical Applications – Water Research, 2026 Synergistic Pyrogenic Carbon-Microbial Dehalogenator for Removal of Persistent “Forever Chemicals” – Environmental Research, 2026
Dr. Kaikai Zhang is a prominent researcher in environmental science, with expertise in contamination remediation and biogeochemical processes. His work focuses on understanding and mitigating the impacts of heavy metals and persistent organic pollutants in soil and groundwater systems. He has developed innovative approaches involving biochar materials, microbial remediation, and advanced chemical treatments to improve environmental sustainability. His research integrates laboratory investigations with practical applications, ensuring long-term effectiveness of remediation strategies. With 23 publications, 996 citations, and an h-index of 14, his contributions demonstrate strong scientific impact and international recognition. His studies provide valuable insights into pollutant transformation, degradation mechanisms, and sustainable environmental solutions, supporting global efforts toward ecological restoration, pollution control, and the advancement of efficient and scalable remediation technologies. Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index View Scopus Profile View ORCID Profile View Research Gate Profile Featured Publications Engineered Biochar Composite with Minerals: Organo-Mineral Interactions, Physicochemical Changes, and Practical Applications – Water Research, 2026 Synergistic Pyrogenic Carbon-Microbial Dehalogenator for Removal of Persistent “Forever Chemicals” – Environmental Research, 2026
Dr. Kaikai Zhang is a prominent researcher in environmental science, with expertise in contamination remediation and biogeochemical processes. His work focuses on understanding and mitigating the impacts of heavy metals and persistent organic pollutants in soil and groundwater systems. He has developed innovative approaches involving biochar materials, microbial remediation, and advanced chemical treatments to improve environmental sustainability. His research integrates laboratory investigations with practical applications, ensuring long-term effectiveness of remediation strategies. With 23 publications, 996 citations, and an h-index of 14, his contributions demonstrate strong scientific impact and international recognition. His studies provide valuable insights into pollutant transformation, degradation mechanisms, and sustainable environmental solutions, supporting global efforts toward ecological restoration, pollution control, and the advancement of efficient and scalable remediation technologies. Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index View Scopus Profile View ORCID Profile View Research Gate Profile Featured Publications Engineered Biochar Composite with Minerals: Organo-Mineral Interactions, Physicochemical Changes, and Practical Applications – Water Research, 2026 Synergistic Pyrogenic Carbon-Microbial Dehalogenator for Removal of Persistent “Forever Chemicals” – Environmental Research, 2026
Dr. Kaikai Zhang is a prominent researcher in environmental science, with expertise in contamination remediation and biogeochemical processes. His work focuses on understanding and mitigating the impacts of heavy metals and persistent organic pollutants in soil and groundwater systems. He has developed innovative approaches involving biochar materials, microbial remediation, and advanced chemical treatments to improve environmental sustainability. His research integrates laboratory investigations with practical applications, ensuring long-term effectiveness of remediation strategies. With 23 publications, 996 citations, and an h-index of 14, his contributions demonstrate strong scientific impact and international recognition. His studies provide valuable insights into pollutant transformation, degradation mechanisms, and sustainable environmental solutions, supporting global efforts toward ecological restoration, pollution control, and the advancement of efficient and scalable remediation technologies. Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index View Scopus Profile View ORCID Profile View Research Gate Profile Featured Publications Engineered Biochar Composite with Minerals: Organo-Mineral Interactions, Physicochemical Changes, and Practical Applications – Water Research, 2026 Synergistic Pyrogenic Carbon-Microbial Dehalogenator for Removal of Persistent “Forever Chemicals” – Environmental Research, 2026
Dr. Kaikai Zhang is a prominent researcher in environmental science, with expertise in contamination remediation and biogeochemical processes. His work focuses on understanding and mitigating the impacts of heavy metals and persistent organic pollutants in soil and groundwater systems. He has developed innovative approaches involving biochar materials, microbial remediation, and advanced chemical treatments to improve environmental sustainability. His research integrates laboratory investigations with practical applications, ensuring long-term effectiveness of remediation strategies. With 23 publications, 996 citations, and an h-index of 14, his contributions demonstrate strong scientific impact and international recognition. His studies provide valuable insights into pollutant transformation, degradation mechanisms, and sustainable environmental solutions, supporting global efforts toward ecological restoration, pollution control, and the advancement of efficient and scalable remediation technologies. Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index View Scopus Profile View ORCID Profile View Research Gate Profile Featured Publications Engineered Biochar Composite with Minerals: Organo-Mineral Interactions, Physicochemical Changes, and Practical Applications – Water Research, 2026 Synergistic Pyrogenic Carbon-Microbial Dehalogenator for Removal of Persistent “Forever Chemicals” – Environmental Research, 2026
Dr. Kaikai Zhang is a prominent researcher in environmental science, with expertise in contamination remediation and biogeochemical processes. His work focuses on understanding and mitigating the impacts of heavy metals and persistent organic pollutants in soil and groundwater systems. He has developed innovative approaches involving biochar materials, microbial remediation, and advanced chemical treatments to improve environmental sustainability. His research integrates laboratory investigations with practical applications, ensuring long-term effectiveness of remediation strategies. With 23 publications, 996 citations, and an h-index of 14, his contributions demonstrate strong scientific impact and international recognition. His studies provide valuable insights into pollutant transformation, degradation mechanisms, and sustainable environmental solutions, supporting global efforts toward ecological restoration, pollution control, and the advancement of efficient and scalable remediation technologies. Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index View Scopus Profile View ORCID Profile View Research Gate Profile Featured Publications Engineered Biochar Composite with Minerals: Organo-Mineral Interactions, Physicochemical Changes, and Practical Applications – Water Research, 2026 Synergistic Pyrogenic Carbon-Microbial Dehalogenator for Removal of Persistent “Forever Chemicals” – Environmental Research, 2026
Dr. Kaikai Zhang is a prominent researcher in environmental science, with expertise in contamination remediation and biogeochemical processes. His work focuses on understanding and mitigating the impacts of heavy metals and persistent organic pollutants in soil and groundwater systems. He has developed innovative approaches involving biochar materials, microbial remediation, and advanced chemical treatments to improve environmental sustainability. His research integrates laboratory investigations with practical applications, ensuring long-term effectiveness of remediation strategies. With 23 publications, 996 citations, and an h-index of 14, his contributions demonstrate strong scientific impact and international recognition. His studies provide valuable insights into pollutant transformation, degradation mechanisms, and sustainable environmental solutions, supporting global efforts toward ecological restoration, pollution control, and the advancement of efficient and scalable remediation technologies. Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index View Scopus Profile View ORCID Profile View Research Gate Profile Featured Publications Engineered Biochar Composite with Minerals: Organo-Mineral Interactions, Physicochemical Changes, and Practical Applications – Water Research, 2026 Synergistic Pyrogenic Carbon-Microbial Dehalogenator for Removal of Persistent “Forever Chemicals” – Environmental Research, 2026
Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index
Citation Metrics ( Scopus ) 1400 1200 1000 800 400 200 0 Citations 996 h-index 23 h-index 14 Citations Documents h-index
Juho Kim | Rewards & Recognition | Research Excellence Award Published on 20/03/202620/03/2026 by Human Resources Management Mr. Juho Kim | Rewards & Recognition | Research Excellence Award Assistant Manager | The University of Taurus Asset Management | South Korea Mr. Juho Kim is a finance researcher specializing in quantitative and empirical finance, with a strong focus on corporate innovation, financial policy, and data-driven analysis. His research integrates large-scale datasets, including patent, financial, and market data, to examine firm behavior and innovation dynamics. He has demonstrated expertise in econometric modeling, data cleaning, and statistical programming to generate robust empirical insights. As an author and co-author, he has contributed three significant research works: “Top-down Flow of Innovation within Industry”, “The Impact of Working Hours on Innovation,” and “Do Chaebol Customers Prefer Innovative Suppliers and What Happens Next?”. His work provides valuable contributions to understanding innovation processes and financial decision-making in contemporary economic systems. View ORCID Profile Featured Publications Top-down Flow of Innovation Within Industry – Applied Economics, 2026 Do Chaebol Customers Prefer Innovative Suppliers—and What Happens Next? – SSRN Preprint, 2025 The Impact of Working Hours on Innovation: Lessons from the 2018 Korean Working-Hours Reform – SSRN Preprint, 2025
Mr. Juho Kim is a finance researcher specializing in quantitative and empirical finance, with a strong focus on corporate innovation, financial policy, and data-driven analysis. His research integrates large-scale datasets, including patent, financial, and market data, to examine firm behavior and innovation dynamics. He has demonstrated expertise in econometric modeling, data cleaning, and statistical programming to generate robust empirical insights. As an author and co-author, he has contributed three significant research works: “Top-down Flow of Innovation within Industry”, “The Impact of Working Hours on Innovation,” and “Do Chaebol Customers Prefer Innovative Suppliers and What Happens Next?”. His work provides valuable contributions to understanding innovation processes and financial decision-making in contemporary economic systems. View ORCID Profile Featured Publications Top-down Flow of Innovation Within Industry – Applied Economics, 2026 Do Chaebol Customers Prefer Innovative Suppliers—and What Happens Next? – SSRN Preprint, 2025 The Impact of Working Hours on Innovation: Lessons from the 2018 Korean Working-Hours Reform – SSRN Preprint, 2025
Mr. Juho Kim is a finance researcher specializing in quantitative and empirical finance, with a strong focus on corporate innovation, financial policy, and data-driven analysis. His research integrates large-scale datasets, including patent, financial, and market data, to examine firm behavior and innovation dynamics. He has demonstrated expertise in econometric modeling, data cleaning, and statistical programming to generate robust empirical insights. As an author and co-author, he has contributed three significant research works: “Top-down Flow of Innovation within Industry”, “The Impact of Working Hours on Innovation,” and “Do Chaebol Customers Prefer Innovative Suppliers and What Happens Next?”. His work provides valuable contributions to understanding innovation processes and financial decision-making in contemporary economic systems. View ORCID Profile Featured Publications Top-down Flow of Innovation Within Industry – Applied Economics, 2026 Do Chaebol Customers Prefer Innovative Suppliers—and What Happens Next? – SSRN Preprint, 2025 The Impact of Working Hours on Innovation: Lessons from the 2018 Korean Working-Hours Reform – SSRN Preprint, 2025
Mr. Juho Kim is a finance researcher specializing in quantitative and empirical finance, with a strong focus on corporate innovation, financial policy, and data-driven analysis. His research integrates large-scale datasets, including patent, financial, and market data, to examine firm behavior and innovation dynamics. He has demonstrated expertise in econometric modeling, data cleaning, and statistical programming to generate robust empirical insights. As an author and co-author, he has contributed three significant research works: “Top-down Flow of Innovation within Industry”, “The Impact of Working Hours on Innovation,” and “Do Chaebol Customers Prefer Innovative Suppliers and What Happens Next?”. His work provides valuable contributions to understanding innovation processes and financial decision-making in contemporary economic systems. View ORCID Profile Featured Publications Top-down Flow of Innovation Within Industry – Applied Economics, 2026 Do Chaebol Customers Prefer Innovative Suppliers—and What Happens Next? – SSRN Preprint, 2025 The Impact of Working Hours on Innovation: Lessons from the 2018 Korean Working-Hours Reform – SSRN Preprint, 2025
Mr. Juho Kim is a finance researcher specializing in quantitative and empirical finance, with a strong focus on corporate innovation, financial policy, and data-driven analysis. His research integrates large-scale datasets, including patent, financial, and market data, to examine firm behavior and innovation dynamics. He has demonstrated expertise in econometric modeling, data cleaning, and statistical programming to generate robust empirical insights. As an author and co-author, he has contributed three significant research works: “Top-down Flow of Innovation within Industry”, “The Impact of Working Hours on Innovation,” and “Do Chaebol Customers Prefer Innovative Suppliers and What Happens Next?”. His work provides valuable contributions to understanding innovation processes and financial decision-making in contemporary economic systems. View ORCID Profile Featured Publications Top-down Flow of Innovation Within Industry – Applied Economics, 2026 Do Chaebol Customers Prefer Innovative Suppliers—and What Happens Next? – SSRN Preprint, 2025 The Impact of Working Hours on Innovation: Lessons from the 2018 Korean Working-Hours Reform – SSRN Preprint, 2025
Mr. Juho Kim is a finance researcher specializing in quantitative and empirical finance, with a strong focus on corporate innovation, financial policy, and data-driven analysis. His research integrates large-scale datasets, including patent, financial, and market data, to examine firm behavior and innovation dynamics. He has demonstrated expertise in econometric modeling, data cleaning, and statistical programming to generate robust empirical insights. As an author and co-author, he has contributed three significant research works: “Top-down Flow of Innovation within Industry”, “The Impact of Working Hours on Innovation,” and “Do Chaebol Customers Prefer Innovative Suppliers and What Happens Next?”. His work provides valuable contributions to understanding innovation processes and financial decision-making in contemporary economic systems. View ORCID Profile Featured Publications Top-down Flow of Innovation Within Industry – Applied Economics, 2026 Do Chaebol Customers Prefer Innovative Suppliers—and What Happens Next? – SSRN Preprint, 2025 The Impact of Working Hours on Innovation: Lessons from the 2018 Korean Working-Hours Reform – SSRN Preprint, 2025
Mr. Juho Kim is a finance researcher specializing in quantitative and empirical finance, with a strong focus on corporate innovation, financial policy, and data-driven analysis. His research integrates large-scale datasets, including patent, financial, and market data, to examine firm behavior and innovation dynamics. He has demonstrated expertise in econometric modeling, data cleaning, and statistical programming to generate robust empirical insights. As an author and co-author, he has contributed three significant research works: “Top-down Flow of Innovation within Industry”, “The Impact of Working Hours on Innovation,” and “Do Chaebol Customers Prefer Innovative Suppliers and What Happens Next?”. His work provides valuable contributions to understanding innovation processes and financial decision-making in contemporary economic systems. View ORCID Profile Featured Publications Top-down Flow of Innovation Within Industry – Applied Economics, 2026 Do Chaebol Customers Prefer Innovative Suppliers—and What Happens Next? – SSRN Preprint, 2025 The Impact of Working Hours on Innovation: Lessons from the 2018 Korean Working-Hours Reform – SSRN Preprint, 2025
Mr. Juho Kim is a finance researcher specializing in quantitative and empirical finance, with a strong focus on corporate innovation, financial policy, and data-driven analysis. His research integrates large-scale datasets, including patent, financial, and market data, to examine firm behavior and innovation dynamics. He has demonstrated expertise in econometric modeling, data cleaning, and statistical programming to generate robust empirical insights. As an author and co-author, he has contributed three significant research works: “Top-down Flow of Innovation within Industry”, “The Impact of Working Hours on Innovation,” and “Do Chaebol Customers Prefer Innovative Suppliers and What Happens Next?”. His work provides valuable contributions to understanding innovation processes and financial decision-making in contemporary economic systems. View ORCID Profile Featured Publications Top-down Flow of Innovation Within Industry – Applied Economics, 2026 Do Chaebol Customers Prefer Innovative Suppliers—and What Happens Next? – SSRN Preprint, 2025 The Impact of Working Hours on Innovation: Lessons from the 2018 Korean Working-Hours Reform – SSRN Preprint, 2025
Mr. Juho Kim is a finance researcher specializing in quantitative and empirical finance, with a strong focus on corporate innovation, financial policy, and data-driven analysis. His research integrates large-scale datasets, including patent, financial, and market data, to examine firm behavior and innovation dynamics. He has demonstrated expertise in econometric modeling, data cleaning, and statistical programming to generate robust empirical insights. As an author and co-author, he has contributed three significant research works: “Top-down Flow of Innovation within Industry”, “The Impact of Working Hours on Innovation,” and “Do Chaebol Customers Prefer Innovative Suppliers and What Happens Next?”. His work provides valuable contributions to understanding innovation processes and financial decision-making in contemporary economic systems. View ORCID Profile Featured Publications Top-down Flow of Innovation Within Industry – Applied Economics, 2026 Do Chaebol Customers Prefer Innovative Suppliers—and What Happens Next? – SSRN Preprint, 2025 The Impact of Working Hours on Innovation: Lessons from the 2018 Korean Working-Hours Reform – SSRN Preprint, 2025
Mr. Juho Kim is a finance researcher specializing in quantitative and empirical finance, with a strong focus on corporate innovation, financial policy, and data-driven analysis. His research integrates large-scale datasets, including patent, financial, and market data, to examine firm behavior and innovation dynamics. He has demonstrated expertise in econometric modeling, data cleaning, and statistical programming to generate robust empirical insights. As an author and co-author, he has contributed three significant research works: “Top-down Flow of Innovation within Industry”, “The Impact of Working Hours on Innovation,” and “Do Chaebol Customers Prefer Innovative Suppliers and What Happens Next?”. His work provides valuable contributions to understanding innovation processes and financial decision-making in contemporary economic systems. View ORCID Profile Featured Publications Top-down Flow of Innovation Within Industry – Applied Economics, 2026 Do Chaebol Customers Prefer Innovative Suppliers—and What Happens Next? – SSRN Preprint, 2025 The Impact of Working Hours on Innovation: Lessons from the 2018 Korean Working-Hours Reform – SSRN Preprint, 2025
Mr. Juho Kim is a finance researcher specializing in quantitative and empirical finance, with a strong focus on corporate innovation, financial policy, and data-driven analysis. His research integrates large-scale datasets, including patent, financial, and market data, to examine firm behavior and innovation dynamics. He has demonstrated expertise in econometric modeling, data cleaning, and statistical programming to generate robust empirical insights. As an author and co-author, he has contributed three significant research works: “Top-down Flow of Innovation within Industry”, “The Impact of Working Hours on Innovation,” and “Do Chaebol Customers Prefer Innovative Suppliers and What Happens Next?”. His work provides valuable contributions to understanding innovation processes and financial decision-making in contemporary economic systems. View ORCID Profile Featured Publications Top-down Flow of Innovation Within Industry – Applied Economics, 2026 Do Chaebol Customers Prefer Innovative Suppliers—and What Happens Next? – SSRN Preprint, 2025 The Impact of Working Hours on Innovation: Lessons from the 2018 Korean Working-Hours Reform – SSRN Preprint, 2025
Mr. Juho Kim is a finance researcher specializing in quantitative and empirical finance, with a strong focus on corporate innovation, financial policy, and data-driven analysis. His research integrates large-scale datasets, including patent, financial, and market data, to examine firm behavior and innovation dynamics. He has demonstrated expertise in econometric modeling, data cleaning, and statistical programming to generate robust empirical insights. As an author and co-author, he has contributed three significant research works: “Top-down Flow of Innovation within Industry”, “The Impact of Working Hours on Innovation,” and “Do Chaebol Customers Prefer Innovative Suppliers and What Happens Next?”. His work provides valuable contributions to understanding innovation processes and financial decision-making in contemporary economic systems. View ORCID Profile Featured Publications Top-down Flow of Innovation Within Industry – Applied Economics, 2026 Do Chaebol Customers Prefer Innovative Suppliers—and What Happens Next? – SSRN Preprint, 2025 The Impact of Working Hours on Innovation: Lessons from the 2018 Korean Working-Hours Reform – SSRN Preprint, 2025
Mr. Juho Kim is a finance researcher specializing in quantitative and empirical finance, with a strong focus on corporate innovation, financial policy, and data-driven analysis. His research integrates large-scale datasets, including patent, financial, and market data, to examine firm behavior and innovation dynamics. He has demonstrated expertise in econometric modeling, data cleaning, and statistical programming to generate robust empirical insights. As an author and co-author, he has contributed three significant research works: “Top-down Flow of Innovation within Industry”, “The Impact of Working Hours on Innovation,” and “Do Chaebol Customers Prefer Innovative Suppliers and What Happens Next?”. His work provides valuable contributions to understanding innovation processes and financial decision-making in contemporary economic systems. View ORCID Profile Featured Publications Top-down Flow of Innovation Within Industry – Applied Economics, 2026 Do Chaebol Customers Prefer Innovative Suppliers—and What Happens Next? – SSRN Preprint, 2025 The Impact of Working Hours on Innovation: Lessons from the 2018 Korean Working-Hours Reform – SSRN Preprint, 2025
Alvaro Peña Fritz | HR Technology and Digital Transformation | Industry Impact Award Published on 18/03/202618/03/2026 by Human Resources Management Dr. Alvaro Peña Fritz | HR Technology and Digital Transformation | Industry Impact Award Director Doctorado Industria Inteligente | The University of Pontificia Universidad Católica De Valparaíso | Chile Dr. Alvaro Peña Fritz is an active contributor to engineering and applied computational research, with a strong emphasis on optimization techniques, intelligent systems, and data-driven methodologies. With a record of 67 scientific publications, 375 citations, and an h-index of 10, his work reflects solid academic influence and growing recognition. His research focuses on integrating machine learning, metaheuristic algorithms, and advanced modeling approaches to address complex problems in engineering, infrastructure, and industrial systems. He has contributed to interdisciplinary domains including transportation systems, geotechnical analysis, and smart technologies. His publications demonstrate a balance between theoretical innovation and practical application, supporting efficient, sustainable, and intelligent solutions to modern engineering challenges while contributing to the advancement of computational methods in real-world scenarios. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 375 h-index 67 h-index 10 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Shadow Fading Prediction at 18 GHz through Physics-Guided Learning in Vegetative Corridors – Scientific Reports, 2026 From Lab Forces to Field Lifespans: How Rock and Operating Parameters Govern TBM Disc Cutter Wear – Rock Mechanics Bulletin, 2026 Variational Mechanics for Mining Infrastructure Design: From Hamilton’s Principle to Physics-Constrained Optimization – Review Article, 2026 Interpretable Binary Classification Under Constraints for Financial Compliance Modeling – Mathematics, 2026 Designing Accessible and Comfortable Bus Interiors for Sustainable and Smart Urban Mobility – Sustainability Switzerland, 2026
Dr. Alvaro Peña Fritz is an active contributor to engineering and applied computational research, with a strong emphasis on optimization techniques, intelligent systems, and data-driven methodologies. With a record of 67 scientific publications, 375 citations, and an h-index of 10, his work reflects solid academic influence and growing recognition. His research focuses on integrating machine learning, metaheuristic algorithms, and advanced modeling approaches to address complex problems in engineering, infrastructure, and industrial systems. He has contributed to interdisciplinary domains including transportation systems, geotechnical analysis, and smart technologies. His publications demonstrate a balance between theoretical innovation and practical application, supporting efficient, sustainable, and intelligent solutions to modern engineering challenges while contributing to the advancement of computational methods in real-world scenarios. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 375 h-index 67 h-index 10 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Shadow Fading Prediction at 18 GHz through Physics-Guided Learning in Vegetative Corridors – Scientific Reports, 2026 From Lab Forces to Field Lifespans: How Rock and Operating Parameters Govern TBM Disc Cutter Wear – Rock Mechanics Bulletin, 2026 Variational Mechanics for Mining Infrastructure Design: From Hamilton’s Principle to Physics-Constrained Optimization – Review Article, 2026 Interpretable Binary Classification Under Constraints for Financial Compliance Modeling – Mathematics, 2026 Designing Accessible and Comfortable Bus Interiors for Sustainable and Smart Urban Mobility – Sustainability Switzerland, 2026
Dr. Alvaro Peña Fritz is an active contributor to engineering and applied computational research, with a strong emphasis on optimization techniques, intelligent systems, and data-driven methodologies. With a record of 67 scientific publications, 375 citations, and an h-index of 10, his work reflects solid academic influence and growing recognition. His research focuses on integrating machine learning, metaheuristic algorithms, and advanced modeling approaches to address complex problems in engineering, infrastructure, and industrial systems. He has contributed to interdisciplinary domains including transportation systems, geotechnical analysis, and smart technologies. His publications demonstrate a balance between theoretical innovation and practical application, supporting efficient, sustainable, and intelligent solutions to modern engineering challenges while contributing to the advancement of computational methods in real-world scenarios. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 375 h-index 67 h-index 10 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Shadow Fading Prediction at 18 GHz through Physics-Guided Learning in Vegetative Corridors – Scientific Reports, 2026 From Lab Forces to Field Lifespans: How Rock and Operating Parameters Govern TBM Disc Cutter Wear – Rock Mechanics Bulletin, 2026 Variational Mechanics for Mining Infrastructure Design: From Hamilton’s Principle to Physics-Constrained Optimization – Review Article, 2026 Interpretable Binary Classification Under Constraints for Financial Compliance Modeling – Mathematics, 2026 Designing Accessible and Comfortable Bus Interiors for Sustainable and Smart Urban Mobility – Sustainability Switzerland, 2026
Dr. Alvaro Peña Fritz is an active contributor to engineering and applied computational research, with a strong emphasis on optimization techniques, intelligent systems, and data-driven methodologies. With a record of 67 scientific publications, 375 citations, and an h-index of 10, his work reflects solid academic influence and growing recognition. His research focuses on integrating machine learning, metaheuristic algorithms, and advanced modeling approaches to address complex problems in engineering, infrastructure, and industrial systems. He has contributed to interdisciplinary domains including transportation systems, geotechnical analysis, and smart technologies. His publications demonstrate a balance between theoretical innovation and practical application, supporting efficient, sustainable, and intelligent solutions to modern engineering challenges while contributing to the advancement of computational methods in real-world scenarios. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 375 h-index 67 h-index 10 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Shadow Fading Prediction at 18 GHz through Physics-Guided Learning in Vegetative Corridors – Scientific Reports, 2026 From Lab Forces to Field Lifespans: How Rock and Operating Parameters Govern TBM Disc Cutter Wear – Rock Mechanics Bulletin, 2026 Variational Mechanics for Mining Infrastructure Design: From Hamilton’s Principle to Physics-Constrained Optimization – Review Article, 2026 Interpretable Binary Classification Under Constraints for Financial Compliance Modeling – Mathematics, 2026 Designing Accessible and Comfortable Bus Interiors for Sustainable and Smart Urban Mobility – Sustainability Switzerland, 2026
Dr. Alvaro Peña Fritz is an active contributor to engineering and applied computational research, with a strong emphasis on optimization techniques, intelligent systems, and data-driven methodologies. With a record of 67 scientific publications, 375 citations, and an h-index of 10, his work reflects solid academic influence and growing recognition. His research focuses on integrating machine learning, metaheuristic algorithms, and advanced modeling approaches to address complex problems in engineering, infrastructure, and industrial systems. He has contributed to interdisciplinary domains including transportation systems, geotechnical analysis, and smart technologies. His publications demonstrate a balance between theoretical innovation and practical application, supporting efficient, sustainable, and intelligent solutions to modern engineering challenges while contributing to the advancement of computational methods in real-world scenarios. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 375 h-index 67 h-index 10 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Shadow Fading Prediction at 18 GHz through Physics-Guided Learning in Vegetative Corridors – Scientific Reports, 2026 From Lab Forces to Field Lifespans: How Rock and Operating Parameters Govern TBM Disc Cutter Wear – Rock Mechanics Bulletin, 2026 Variational Mechanics for Mining Infrastructure Design: From Hamilton’s Principle to Physics-Constrained Optimization – Review Article, 2026 Interpretable Binary Classification Under Constraints for Financial Compliance Modeling – Mathematics, 2026 Designing Accessible and Comfortable Bus Interiors for Sustainable and Smart Urban Mobility – Sustainability Switzerland, 2026
Dr. Alvaro Peña Fritz is an active contributor to engineering and applied computational research, with a strong emphasis on optimization techniques, intelligent systems, and data-driven methodologies. With a record of 67 scientific publications, 375 citations, and an h-index of 10, his work reflects solid academic influence and growing recognition. His research focuses on integrating machine learning, metaheuristic algorithms, and advanced modeling approaches to address complex problems in engineering, infrastructure, and industrial systems. He has contributed to interdisciplinary domains including transportation systems, geotechnical analysis, and smart technologies. His publications demonstrate a balance between theoretical innovation and practical application, supporting efficient, sustainable, and intelligent solutions to modern engineering challenges while contributing to the advancement of computational methods in real-world scenarios. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 375 h-index 67 h-index 10 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Shadow Fading Prediction at 18 GHz through Physics-Guided Learning in Vegetative Corridors – Scientific Reports, 2026 From Lab Forces to Field Lifespans: How Rock and Operating Parameters Govern TBM Disc Cutter Wear – Rock Mechanics Bulletin, 2026 Variational Mechanics for Mining Infrastructure Design: From Hamilton’s Principle to Physics-Constrained Optimization – Review Article, 2026 Interpretable Binary Classification Under Constraints for Financial Compliance Modeling – Mathematics, 2026 Designing Accessible and Comfortable Bus Interiors for Sustainable and Smart Urban Mobility – Sustainability Switzerland, 2026
Dr. Alvaro Peña Fritz is an active contributor to engineering and applied computational research, with a strong emphasis on optimization techniques, intelligent systems, and data-driven methodologies. With a record of 67 scientific publications, 375 citations, and an h-index of 10, his work reflects solid academic influence and growing recognition. His research focuses on integrating machine learning, metaheuristic algorithms, and advanced modeling approaches to address complex problems in engineering, infrastructure, and industrial systems. He has contributed to interdisciplinary domains including transportation systems, geotechnical analysis, and smart technologies. His publications demonstrate a balance between theoretical innovation and practical application, supporting efficient, sustainable, and intelligent solutions to modern engineering challenges while contributing to the advancement of computational methods in real-world scenarios. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 375 h-index 67 h-index 10 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Shadow Fading Prediction at 18 GHz through Physics-Guided Learning in Vegetative Corridors – Scientific Reports, 2026 From Lab Forces to Field Lifespans: How Rock and Operating Parameters Govern TBM Disc Cutter Wear – Rock Mechanics Bulletin, 2026 Variational Mechanics for Mining Infrastructure Design: From Hamilton’s Principle to Physics-Constrained Optimization – Review Article, 2026 Interpretable Binary Classification Under Constraints for Financial Compliance Modeling – Mathematics, 2026 Designing Accessible and Comfortable Bus Interiors for Sustainable and Smart Urban Mobility – Sustainability Switzerland, 2026
Dr. Alvaro Peña Fritz is an active contributor to engineering and applied computational research, with a strong emphasis on optimization techniques, intelligent systems, and data-driven methodologies. With a record of 67 scientific publications, 375 citations, and an h-index of 10, his work reflects solid academic influence and growing recognition. His research focuses on integrating machine learning, metaheuristic algorithms, and advanced modeling approaches to address complex problems in engineering, infrastructure, and industrial systems. He has contributed to interdisciplinary domains including transportation systems, geotechnical analysis, and smart technologies. His publications demonstrate a balance between theoretical innovation and practical application, supporting efficient, sustainable, and intelligent solutions to modern engineering challenges while contributing to the advancement of computational methods in real-world scenarios. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 375 h-index 67 h-index 10 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Shadow Fading Prediction at 18 GHz through Physics-Guided Learning in Vegetative Corridors – Scientific Reports, 2026 From Lab Forces to Field Lifespans: How Rock and Operating Parameters Govern TBM Disc Cutter Wear – Rock Mechanics Bulletin, 2026 Variational Mechanics for Mining Infrastructure Design: From Hamilton’s Principle to Physics-Constrained Optimization – Review Article, 2026 Interpretable Binary Classification Under Constraints for Financial Compliance Modeling – Mathematics, 2026 Designing Accessible and Comfortable Bus Interiors for Sustainable and Smart Urban Mobility – Sustainability Switzerland, 2026
Dr. Alvaro Peña Fritz is an active contributor to engineering and applied computational research, with a strong emphasis on optimization techniques, intelligent systems, and data-driven methodologies. With a record of 67 scientific publications, 375 citations, and an h-index of 10, his work reflects solid academic influence and growing recognition. His research focuses on integrating machine learning, metaheuristic algorithms, and advanced modeling approaches to address complex problems in engineering, infrastructure, and industrial systems. He has contributed to interdisciplinary domains including transportation systems, geotechnical analysis, and smart technologies. His publications demonstrate a balance between theoretical innovation and practical application, supporting efficient, sustainable, and intelligent solutions to modern engineering challenges while contributing to the advancement of computational methods in real-world scenarios. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 375 h-index 67 h-index 10 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Shadow Fading Prediction at 18 GHz through Physics-Guided Learning in Vegetative Corridors – Scientific Reports, 2026 From Lab Forces to Field Lifespans: How Rock and Operating Parameters Govern TBM Disc Cutter Wear – Rock Mechanics Bulletin, 2026 Variational Mechanics for Mining Infrastructure Design: From Hamilton’s Principle to Physics-Constrained Optimization – Review Article, 2026 Interpretable Binary Classification Under Constraints for Financial Compliance Modeling – Mathematics, 2026 Designing Accessible and Comfortable Bus Interiors for Sustainable and Smart Urban Mobility – Sustainability Switzerland, 2026
Dr. Alvaro Peña Fritz is an active contributor to engineering and applied computational research, with a strong emphasis on optimization techniques, intelligent systems, and data-driven methodologies. With a record of 67 scientific publications, 375 citations, and an h-index of 10, his work reflects solid academic influence and growing recognition. His research focuses on integrating machine learning, metaheuristic algorithms, and advanced modeling approaches to address complex problems in engineering, infrastructure, and industrial systems. He has contributed to interdisciplinary domains including transportation systems, geotechnical analysis, and smart technologies. His publications demonstrate a balance between theoretical innovation and practical application, supporting efficient, sustainable, and intelligent solutions to modern engineering challenges while contributing to the advancement of computational methods in real-world scenarios. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 375 h-index 67 h-index 10 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Shadow Fading Prediction at 18 GHz through Physics-Guided Learning in Vegetative Corridors – Scientific Reports, 2026 From Lab Forces to Field Lifespans: How Rock and Operating Parameters Govern TBM Disc Cutter Wear – Rock Mechanics Bulletin, 2026 Variational Mechanics for Mining Infrastructure Design: From Hamilton’s Principle to Physics-Constrained Optimization – Review Article, 2026 Interpretable Binary Classification Under Constraints for Financial Compliance Modeling – Mathematics, 2026 Designing Accessible and Comfortable Bus Interiors for Sustainable and Smart Urban Mobility – Sustainability Switzerland, 2026
Dr. Alvaro Peña Fritz is an active contributor to engineering and applied computational research, with a strong emphasis on optimization techniques, intelligent systems, and data-driven methodologies. With a record of 67 scientific publications, 375 citations, and an h-index of 10, his work reflects solid academic influence and growing recognition. His research focuses on integrating machine learning, metaheuristic algorithms, and advanced modeling approaches to address complex problems in engineering, infrastructure, and industrial systems. He has contributed to interdisciplinary domains including transportation systems, geotechnical analysis, and smart technologies. His publications demonstrate a balance between theoretical innovation and practical application, supporting efficient, sustainable, and intelligent solutions to modern engineering challenges while contributing to the advancement of computational methods in real-world scenarios. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 375 h-index 67 h-index 10 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Shadow Fading Prediction at 18 GHz through Physics-Guided Learning in Vegetative Corridors – Scientific Reports, 2026 From Lab Forces to Field Lifespans: How Rock and Operating Parameters Govern TBM Disc Cutter Wear – Rock Mechanics Bulletin, 2026 Variational Mechanics for Mining Infrastructure Design: From Hamilton’s Principle to Physics-Constrained Optimization – Review Article, 2026 Interpretable Binary Classification Under Constraints for Financial Compliance Modeling – Mathematics, 2026 Designing Accessible and Comfortable Bus Interiors for Sustainable and Smart Urban Mobility – Sustainability Switzerland, 2026
Dr. Alvaro Peña Fritz is an active contributor to engineering and applied computational research, with a strong emphasis on optimization techniques, intelligent systems, and data-driven methodologies. With a record of 67 scientific publications, 375 citations, and an h-index of 10, his work reflects solid academic influence and growing recognition. His research focuses on integrating machine learning, metaheuristic algorithms, and advanced modeling approaches to address complex problems in engineering, infrastructure, and industrial systems. He has contributed to interdisciplinary domains including transportation systems, geotechnical analysis, and smart technologies. His publications demonstrate a balance between theoretical innovation and practical application, supporting efficient, sustainable, and intelligent solutions to modern engineering challenges while contributing to the advancement of computational methods in real-world scenarios.
Dr. Alvaro Peña Fritz is an active contributor to engineering and applied computational research, with a strong emphasis on optimization techniques, intelligent systems, and data-driven methodologies. With a record of 67 scientific publications, 375 citations, and an h-index of 10, his work reflects solid academic influence and growing recognition. His research focuses on integrating machine learning, metaheuristic algorithms, and advanced modeling approaches to address complex problems in engineering, infrastructure, and industrial systems. He has contributed to interdisciplinary domains including transportation systems, geotechnical analysis, and smart technologies. His publications demonstrate a balance between theoretical innovation and practical application, supporting efficient, sustainable, and intelligent solutions to modern engineering challenges while contributing to the advancement of computational methods in real-world scenarios.
Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 375 h-index 67 h-index 10 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Shadow Fading Prediction at 18 GHz through Physics-Guided Learning in Vegetative Corridors – Scientific Reports, 2026 From Lab Forces to Field Lifespans: How Rock and Operating Parameters Govern TBM Disc Cutter Wear – Rock Mechanics Bulletin, 2026 Variational Mechanics for Mining Infrastructure Design: From Hamilton’s Principle to Physics-Constrained Optimization – Review Article, 2026 Interpretable Binary Classification Under Constraints for Financial Compliance Modeling – Mathematics, 2026 Designing Accessible and Comfortable Bus Interiors for Sustainable and Smart Urban Mobility – Sustainability Switzerland, 2026
Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 375 h-index 67 h-index 10 Citations Documents h-index
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