Dr. Dawei Qiu | Smart Grid | Best Researcher Award

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Dr. Dawei Qiu | Smart Grid | Best Researcher Award

Lecturer, University of Exeter, United Kingdom

Dr. Dawei Qiu is a distinguished scholar in smart energy systems, currently serving as a Lecturer at the University of Exeter, UK 🏫. With a strong background in electrical engineering and power systems, he specializes in AI-driven reinforcement learning, market design for low-carbon energy transition, and resilience enhancement of energy systems ⚡. His extensive research contributions in smart grids and power systems have earned him recognition in academia, with a Google Scholar citation count of 2,109, an h-index of 24, and an h10-index of 35 📊.

Publication Profile

Google Scholar

🎓 Education

Dr. Qiu holds a Ph.D. in Electrical Engineering from Imperial College London (2016–2020) 🎓, where he conducted pioneering research on local flexibility’s impact on electricity retailers under the supervision of Prof. Goran Strbac. Prior to this, he completed his M.Sc. in Power System Engineering from University College London (2014–2015) and obtained his B.Eng. in Electrical and Electronic Engineering from Northumbria University at Newcastle (2010–2014) ⚙️. His academic journey has been shaped by esteemed mentors, including Dr. Ben Hanson and Dr. Zhiwei (David) Gao, IEEE Fellow.

💼 Experience

Dr. Qiu’s professional career spans academia and research institutions, where he has contributed significantly to energy systems innovation 🌍. Before joining the University of Exeter in 2024, he was a Research Fellow at Imperial College London (2023–2024), specializing in market design for low-carbon energy systems. He also served as a Research Associate at the same institution from 2020 to 2023 🔬. His work in smart grids and energy resilience has been instrumental in shaping sustainable and intelligent power infrastructure.

🏆 Awards and Honors

Dr. Qiu’s research excellence has been acknowledged through various accolades 🏅. His contributions to smart energy systems, AI-driven reinforcement learning, and low-carbon market design have positioned him as a leading researcher in the field. His studies have been published in top-tier journals, and his work has received high citations, demonstrating its impact on the global research community 🌟.

🔬 Research Focus

Dr. Qiu’s research is centered on leveraging artificial intelligence and reinforcement learning for power and energy applications 🤖. His work explores market mechanisms for cost-effective and sustainable energy transitions, as well as the resilience enhancement of energy systems in response to climate change 🌍. His expertise in AI-driven optimization and machine learning applications in energy systems makes him a key contributor to the advancement of smart grid technologies.

🔚 Conclusion

Dr. Dawei Qiu is a leading researcher in smart energy systems, with a strong academic background and impactful contributions to power systems engineering 🔬. His expertise in AI-driven market optimization, reinforcement learning, and resilient energy systems has made him a valuable asset to the research community 🌍. With his ongoing work at the University of Exeter, he continues to drive innovation in low-carbon and intelligent energy solutions ⚡.

🔗 Publications

A knowledge-based safe reinforcement learning approach for real-time automatic control in a smart energy hub – Applied Energy (Under review, 2025) 🔗 Link

Enhanced Meta Reinforcement Learning for Resilient Transient Stabilization – IEEE Transactions on Power Systems (Under review, 2025) 🔗 Link

Machine learning-based economic model predictive control for energy hubs with variable energy efficiencies – Energy (First round revision, 2024) 🔗 Link

A Review of Resilience Enhancement Measures for Hydrogen-penetrated Multi-energy Systems – Proceedings of the IEEE (Under review, 2025) 🔗 Link

Coordinated Optimal Dispatch Based on Dynamic Feasible Operation Region Aggregation – IEEE Transactions on Smart Grid (First round revision, 2024) 🔗 Link

A Sequential Multi-Agent Reinforcement Learning Method for Coordinated Reconfiguration of Substation and MV Distribution Networks – IEEE Transactions on Power Systems (Under review, 2024) 🔗 Link

Enhancing Microgrid Resilience through a Two-Layer Control Framework for Electric Vehicle Integration and Communication Load Management – IEEE Internet of Things Journal (Under review, 2024) 🔗 Link

Coordinated Electric Vehicle Control in Microgrids Towards Multi-Service Provisions: A Transformer Learning-based Risk Management Strategy – Energy (Under review, 2024) 🔗 Link

Adaptive Resilient Control Against False Data Injection Attacks for a Multi-Energy Microgrid Using Deep Reinforcement Learning – IEEE Transactions on Network Science and Engineering (Under review, 2024) 🔗 Link

Jin Wang | Renewable Energy Technologies Award | Best Researcher Award

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Dr. Jin Wang | Renewable Energy Technologies Award | Best Researcher Award

Doctoral candidate, Taiyuan University of Technology, China

Jin Wang, a doctoral candidate at Taiyuan University of Technology, is a promising researcher in the field of electrical engineering. Born on June 1, 1996, Jin is a member of the Han nationality and is deeply focused on coastal renewable energy generation. He is working towards his Ph.D. in Electrical Engineering and has actively contributed to advancing knowledge in energy systems. With a strong academic foundation and hands-on research experience, Jin is making significant strides in his field. 🧑‍🎓⚡🌍

Publication Profile

ORCID

Education:

Jin Wang completed his undergraduate degree in Electrical Engineering at Taiyuan University of Technology in 2020. Following this, he embarked on his Ph.D. journey at the same university, with an expected completion date in 2025. His academic career is distinguished by a dedication to innovation and the pursuit of sustainable energy solutions. 🎓🔌

Experience:

Jin Wang has been involved in a variety of research projects at Taiyuan University of Technology, with a focus on energy systems for polar regions and coastal renewable energy generation. He has also gained practical experience by contributing to national and provincial-level projects, particularly on clean, low-carbon energy systems. 💼🌱

Awards and Honors:

Jin has received several certifications that highlight his commitment to excellence. These include his achievements in English proficiency (CET-6, CET-4), as well as certifications in hydrogen energy technology and industrial technology enhancement. 🏅🎖️

Research Focus:

Jin’s research primarily revolves around coastal renewable energy generation, with specific attention to energy systems in extreme environments, such as polar regions. His work includes projects on energy systems for coastal research stations, hybrid energy systems, and proton exchange membrane fuel cells (PEMFC) in standalone systems. 🔋🌊

Conclusion:

Jin Wang is a dedicated researcher with a clear focus on sustainable energy solutions for challenging environments. His academic background, along with his involvement in cutting-edge research projects, positions him to make significant contributions to the field of renewable energy. 🌍💡

Publications:

Application and effect analysis of renewable energy in a small standalone automatic observation system deployed in the polar regions – AIP Advances, 2022, Author ranking: 1

Improving Proton Exchange Membrane Fuel Cell Operational Reliability Through Cabin-Based Fuzzy Control in Coastal Standalone Observation Systems in Antarctica – Journal of Marine Science and Engineering, 2025, Author ranking: 1

A Multi-Objective Scheduling Strategy for a Hybrid Energy System for Antarctic Coastal Research Stations – Journal of Marine Science and Engineering, 2024, Author ranking: 3

Research on output voltage control of PEMFC based on fuzzy active disturbance rejection – Modern Electronic Technology, 2024, Author ranking: 3

Ahmed H.Ibrahim | Green technology | Best Researcher Award

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Dr. Ahmed H.Ibrahim | Green technology | Best Researcher Award

Lecturer, Azhar university, Egypt

Ahmed Hamdy Ibrahim Kraiz is an accomplished professional in the field of Metallurgical Engineering, specializing in Mineral Processing and Extractive Metallurgy. Born on February 10, 1987, in Mansoura, Egypt, he holds a Ph.D. from Shandong University of Science and Technology, China (2023), where his research focused on “Extraction and Reaction Mechanism of Valuable Metals from Egyptian Boiler Ash.” With a strong foundation in metallurgy and a passion for advancing his knowledge, Ahmed has held several key roles, including Metallurgical Consultant at Capital Leading Company (CLC) and Assistant Lecturer at Al-Azhar University. His work spans various industrial sectors, including oil and gas, mining, and nuclear materials, and he has a rich history of training and certifications in areas like welding, risk assessment, and industrial safety. 💼🎓

Publication Profile

ORCID

Education:

Ahmed’s academic journey is marked by impressive achievements, beginning with his Bachelor’s degree in Metallurgical Engineering from Al-Azhar University (2009), where he graduated with high distinction. He further advanced his studies with a Master’s degree in Metallurgical Engineering (2016), specializing in the pre-treatment of low-grade uranium-bearing granites. His most recent achievement is a Ph.D. in Mineral Processing and Extractive Metallurgy from Shandong University, China, where his research contributed significantly to the understanding of metal extraction from industrial waste. 🎓📚

Experience:

With over a decade of professional experience, Ahmed has excelled in diverse roles in the metallurgical and petroleum engineering sectors. Since 2019, he has served as a Metallurgical Consultant at Capital Leading Company (CLC), advising on oil and gas projects in the West Nile Delta. He also worked as an Assistant Lecturer at Al-Azhar University, where he contributed to the development of future engineers in the Metallurgical and Petroleum Engineering Department. His prior roles include Workshop Coordinator at Petropower Egypt and Metallurgical Engineer at the Nuclear Material Authority, where he focused on uranium mining in Egypt’s Eastern Desert. 🛠️📊

Awards and Honors:

Ahmed’s dedication and expertise have been recognized throughout his career. He received a series of certifications and training accolades, including his SNT-TC-1A Level II certification and welding course from Mansoura University. He also earned recognition for his research on metallurgical engineering, with his work contributing to advancements in metal extraction technologies. 🏆🔬

Research Focus:

Ahmed’s primary research interests revolve around Mineral Processing and Extractive Metallurgy, with a specific focus on the extraction and reaction mechanisms of valuable metals from industrial waste, such as Egyptian boiler ash. His academic research also includes studying the pre-treatment of low-grade uranium-bearing granites for efficient leaching processes. These contributions aim to improve metal recovery techniques, particularly in challenging materials. 🧪🔍

Conclusion:

Ahmed Hamdy Ibrahim Kraiz is a highly skilled and dedicated professional in Metallurgical Engineering, bringing valuable expertise to both academic and industrial settings. With a passion for innovation and a strong foundation in metallurgy, he is well-positioned to continue contributing to the field of extractive metallurgy and mineral processing. His proven leadership, commitment to learning, and ability to collaborate across cultures make him an asset to any organization. 🌍🤝

Publications:

IDRISS DAGAL | Electrical Engineering | Best Researcher Award

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Dr. IDRISS DAGAL | Electrical Engineering | Best Researcher Award

Assistant Professor, Istanbul Beykent University, Turkey

Dr. Idriss Dagal, an Assistant Professor at Istanbul Beykent University, is a researcher and engineer from Chad specializing in Electrical Engineering, Renewable Energy, and Artificial Intelligence. With a career spanning over a decade, he has worked in various roles, including Aircraft Engineer and Lecturer, and has contributed extensively to the field of electrical systems, power electronics, and optimization algorithms. His academic journey includes a Ph.D. from Yıldız Technical University, Istanbul, Turkey, where he also completed his MSc in Avionics Engineering. Dr. Dagal has authored over 30 publications and is an active reviewer for renowned journals. 🌍💡

Publication Profile

ORCID

Education:

Dr. Dagal holds a Bachelor of Science (B.S.) degree in Industrial and Maintenance Engineering from Mongo Polytechnic University (Chad, 2006), a Master of Science (M.Sc.) in Aviation Engineering from Ethiopian Airlines Aviation School (Ethiopia, 2010), and a Ph.D. in Electrical Engineering from Yıldız Technical University (Turkey, 2022). He is currently pursuing a second M.Sc. in Avionics Engineering at Yıldız Technical University. 🎓📚

Experience:

Dr. Dagal’s professional experience spans multiple countries and roles, including serving as an Aircraft Maintenance Engineer in Chad, a Lecturer at various institutions in Chad, and a Sales Engineer in Turkey. Since 2024, he has been serving as an Assistant Professor at Istanbul Beykent University, Turkey, specializing in electrical engineering, renewable energy, and avionics. 🛠️✈️

Awards and Honors:

Dr. Dagal has received several prestigious awards, including the Chad’s Government National Scholarship (2003), Ethiopian Airlines Aviation School International Scholarship (2008), Turkish Government International Scholarship (2015), Young Research Scholarship Award for Eurasia Research (2019), and the Leadership Skills African Civic Engagement Academy (2022). 🏆🌟

Research Focus:

Dr. Dagal’s research interests are centered on optimization algorithms, artificial intelligence, renewable energy systems, power electronics, and aircraft control systems. His doctoral research focused on optimizing photovoltaic battery charging systems using hybrid particle swarm-based algorithms. He has a strong background in developing control mechanisms for sustainable energy systems and dynamic systems in aviation. 🔋🔧🚀

Conclusion:

Dr. Idriss Dagal is an accomplished academic and researcher who combines his expertise in electrical and aerospace engineering with a deep commitment to renewable energy and technology optimization. His interdisciplinary work continues to contribute to advancements in energy systems, aircraft control, and smart technologies. 🌱💻

Publications 

Energy transfer from PV panel to Battery via Buck-Boost Converter, International Journal of Technology and Science, Vol. 5, Issue 3, pp. 46-60, 26 November 2019. DOI

Improved salp swarm algorithm based on particle swarm optimization for maximum power point tracking of optimal photovoltaic systems, International Journal of Energy Research, 2022; 1-18. DOI: 10.1002/er.7753. Impact Factor: 4.3, Q1.

MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization (PSOSSO) algorithm for battery charging through Simulink, Scientific Reports Journal, 2022; 12:2664. DOI. Impact Factor: 3.8, Q1.

A Novel Hybrid Series Salp Particle Swarm Optimization (SSPSO) for Standalone Battery Charging Applications, Ain Shams Engineering Journal, 2022; 13:10174. DOI. Impact Factor: 6, Q1.

Improved Particle Swarm Optimization based Buck-Boost converter (IPSOBBC) for Photovoltaic System Application, Recent Advances in Science & Engineering (RASE), 2022.

Transformer rail-tapped buck-boost converter design-based feedback controller for battery charging systems, Energy Storage Journal, 2022; e414, DOI. ESCI.

Secure and Optimized Satellite Image Sharing based on Chaotic eπ Map and Racah Moments” Expert Systems with Applications, Volume 236, February 2024, 121247, DOI: 10.1016/j.eswa.2023.121247. Impact Factor: 7.5, Q1.

Hybrid SSA-PSO-based intelligent direct sliding-mode control for extracting maximum photovoltaic output power and regulating the DC-bus voltage, International Journal of Hydrogen Energy, Volume 51, Part C, 2 January 2024, Pages 348-370, DOI. Impact Factor: 8.1, Q1.

An Improved Constant Current Step-based Grey Wolf Optimization Algorithm for Photovoltaic Systems, Journal of Intelligent & Fuzzy Systems, 2024, DOI. Impact Factor: 1.7, Q3.

A Modified Multi-Stepped Constant Current Based on Grey Wolf Algorithm for Photovoltaics Applications, Springer, Electrical Engineering, 2024, DOI. Impact Factor: 1.6, Q3.

Jian Sun | Smart Grid Control | Best Researcher Award

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Assoc. Prof. Dr. Jian Sun | Smart Grid Control | Best Researcher Award

Associate Professor, Southwest University, China

Jian Sun is an Associate Professor in the School of Electronic and Information Engineering at Southwest University, Chongqing, China. With a strong academic and research background in automation and electrical engineering, his work focuses on control systems, reinforcement learning, and grid frequency regulation. Over the years, he has made significant contributions to the field through his publications and innovative approaches to tackling complex power grid challenges. 📚🔬

Publication Profile

ORCID

Education

Jian Sun earned his Ph.D. in Automation from Chongqing University in December 2014. He also completed a visiting Ph.D. program at the University of Wisconsin-Madison, USA, in 2014, specializing in Electrical and Computer Engineering. Prior to his doctoral studies, he obtained a Master’s degree in Automation and a Bachelor’s degree in the same field from Chongqing University. 🎓🌍

Experience

Jian Sun has extensive academic and research experience, currently serving as an Associate Professor at Southwest University. His expertise spans areas like frequency regulation in power systems, energy storage systems, and adaptive control techniques. He has published numerous papers in prestigious journals and has contributed to several interdisciplinary research projects. His work often combines advanced reinforcement learning techniques with cyber-physical systems. 💼🔧

Awards and Honors

Throughout his career, Jian Sun has received recognition for his outstanding research and contributions to the field. His work has been widely cited and appreciated by both academic and industry professionals. He continues to push the boundaries of research in smart grids, energy management, and reinforcement learning. 🏆📈

Research Focus

Jian Sun’s research focuses on developing adaptive and resilient control strategies for smart grids, particularly in the context of frequency regulation. His work includes the integration of Vehicle-to-Grid (V2G) technologies, reinforcement learning for DoS attack resilience, and advanced control systems for energy-efficient power grids. He aims to improve the stability and security of power systems in the face of cyber threats and dynamic load conditions. ⚡🧠

Conclusion

Jian Sun’s academic journey and research have contributed to advancements in smart grid technology, power system regulation, and control theory. His continued dedication to addressing critical challenges in energy systems positions him as a leading figure in his field. His research aims to make power systems smarter, more efficient, and resilient to emerging threats. 🌐🔋

Publications 

Load Forecasting for Commercial Buildings Using BiLSTM–Transformer Network and Cyber–Physical Cognitive Control Systems
Published Year: 2024
Journal: Symmetry
Cited by: Crossref

An Adaptive V2G Capacity-Based Frequency Regulation Scheme With Integral Reinforcement Learning Against DoS Attacks
Published Year: 2024
Journal: IEEE Transactions on Smart Grid
Cited by: Crossref

Cooperative Grid Frequency Control Under Asymmetric V2G Capacity via Switched Integral Reinforcement Learning
Published Year: 2024
Journal: International Journal of Electrical Power & Energy Systems
Cited by: Crossref

Resilient Frequency Regulation for DoS Attack Intensity Adaptation via Predictive Reinforcement V2G Control Learning
Published Year: 2024
Journal: IEEE Transactions on Smart Grid
Cited by: Crossref

Safe Online Integral Reinforcement Learning for Control Systems via Controller Decomposition
Published Year: 2023
Journal: Arabian Journal for Science and Engineering
Cited by: Crossref

A DoS Attack-Resilient Grid Frequency Regulation Scheme via Adaptive V2G Capacity-Based Integral Sliding Mode Control
Published Year: 2023
Journal: IEEE Transactions on Smart Grid
Cited by: Crossref

A DoS Attack Intensity-Aware Adaptive Critic Design of Frequency Regulation for EV-Integrated Power Grids
Published Year: 2023
Journal: International Journal of Electrical Power & Energy Systems
Cited by: Crossref

Structural Scheduling of Transient Control Under Energy Storage Systems by Sparse-Promoting Reinforcement Learning
Published Year: 2022
Journal: IEEE Transactions on Industrial Informatics
Cited by: Crossref

A Sparse Neural Network-Based Control Structure Optimization Game under DoS Attacks for DES Frequency Regulation of Power Grid
Published Year: 2019
Journal: Applied Sciences
Cited by: Crossref

A Stable Distributed Neural Controller for Physically Coupled Networked Discrete-Time System via Online Reinforcement Learning
Published Year: 2018
Journal: Complexity
Cited by: Crossref

Frequency Regulation of Power Systems with Self-Triggered Control under the Consideration of Communication Costs
Published Year: 2017
Journal: Applied Sciences
Cited by: Crossref

 

Joao Paulo Neto Torres | energy | Best Researcher Award

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Assist. Prof. Dr.  Joao Paulo Neto Torres | energy | Best Researcher Award

Professor, Academia mIlitar, Portugal

🌟 João Torres, a distinguished researcher from Portugal 🇵🇹, specializes in laser technology, semiconductors, and numerical methods. As a dedicated educator, he serves as an Assistant Professor at Academia Militar and Instituto Superior Técnico, contributing to engineering and technology fields. His passion for innovation is reflected in his impactful research and numerous publications in prominent journals.

Publication Profile

Google Scholar

Education

🎓 João Torres holds a PhD in Electrical and Computer Engineering (2014) and an MSc in Chemical Engineering (2008) from the Universidade Técnica de Lisboa Instituto Superior Técnico, along with a Bachelor’s degree in Physics (2004) from the Universidade de Lisboa Faculdade de Ciências. His multidisciplinary academic background supports his pioneering work in advanced engineering concepts. 📚

Experience

💼 João Torres has over 15 years of professional experience in academia and research. He has been affiliated with Academia Militar (2019–present), Universidade Técnica de Lisboa Instituto Superior Técnico (2012–present), and Fundação para a Ciência e Tecnologia (2016–2018). His contributions span teaching electronics fundamentals, researching electrical and computer engineering, and advancing strategic projects. 🌐

Research Interests

🔬 João’s research focuses on cutting-edge topics like laser applications, semiconductors, and numerical methods, with a special interest in improving photovoltaic systems, energy harvesting, and advanced optical systems. 🌞

Awards 

Dr. Torres has received 6 notable awards and honors, recognizing his contributions to engineering and technology. His accolades highlight his impact on academia, research, and innovation.

Publications

Step-Up DC-DC Converter Supplied by a Thermoelectric Generator for IoT Applications (2024)
Energies – DOI: 10.3390/en17215288

The influence of sand on the performance of CdTe photovoltaic modules of different colours and transparencies (2024)
Energy Systems – DOI: 10.1007/s12667-022-00523-6

The Modeling of Concentrators for Solar Photovoltaic Systems (2024)
Energies – DOI: 10.3390/en17133201

Metallic nanostructures inclusion to improve energy harvesting in silicon (2024)
Optical Materials: X – DOI: 10.1016/j.omx.2024.100298

Wavelength multiplexing system based on ring resonators (2024)
Results in Optics – DOI: 10.1016/j.rio.2024.100651

Experimental Analysis of the Light Wavelength’s Impact on the Performance of a Silicon Solar Cell (2024)
Energies – DOI: 10.3390/en17092090

 

Xuejun Du | Environmental Science | Best Researcher Award

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Dr. Xuejun Du | Environmental Science | Best Researcher Award

Engineer, CECEP Engineering and Technology Research Institute Co. Ltd, China

Xuejun Du is an Engineer at CECEP Engineering and Technology Research Institute Co. Ltd. His expertise lies in improving salt-affected soils, particularly in the Songnen Plain of China, using agricultural and industrial wastes. His research focuses on soil carbon/nitrogen cycling and microbial processes, enhancing crop yields in salt-affected areas.

Profile

Scopus

Education 📚

Xuejun Du holds specialized training in soil science and agricultural technology, complemented by practical field experience in ecological restoration and agricultural sustainability.

Experience 💼

With extensive experience in research and innovation, Xuejun Du has led numerous projects on soil improvement and published extensively in international journals.

Research Interests 🔬

Xuejun Du’s research interests include soil improvement mechanisms, carbon/nitrogen cycling in soil, and microbial community dynamics in saline environments.

Awards 🏆

Xuejun Du’s pioneering work in salt-affected soil improvement earned him recognition from the Chinese Agricultural Society for his contributions to ecological restoration.

Publications 

Key Technology and Application of Rapid Desalination Ecological Restoration of Saline-alkali Land in Songnen Plain, China

Long-term rice cultivation increases contributions of plant and microbial-derived carbon to soil organic carbon in saline-sodic soils

Responses of soil carbon cycling microbial functional genes to nitrogen and phosphorus addition in saline-sodic soils

A cationic quantum dot-based ratiometric fluorescent probe to visually detect berberine hydrochloride in human blood serums

Effects of a new type of soil amendment on physical and chemical properties of soda alkali-saline soil and yield of the rice

 

Joseph Arhavbarien | Green Operations | Best Researcher Award

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Dr. Joseph Arhavbarien | Green Operations | Best Researcher Award

Director / Researcher, Rockedge Ventures (UK) Ltd, United Kingdom

🌱📊 Dr. Joseph Arhavbarien is an accomplished researcher with a Ph.D. in Business and Management from the University of Bedfordshire, UK. With over three decades of industrial experience, he focuses on green processes, sustainable operations, and supply chain management. Transitioning to academia, he combines his rich industrial background with his academic expertise to teach and conduct research, applying quantitative techniques to explore green value internalisation.

Profile

ORCID

📚 Education:

🎓 Dr. Arhavbarien holds a Ph.D. in Business and Management from the University of Bedfordshire (2023). He earned his MBA in International Business from the University of East London (2015) and a B.Sc. (Hons) in Microbiology from the University of Lagos, Nigeria (1989). Additionally, he has a Certificate in Agile Project Management from the University of Oxford (2023).

💼 Experience:

💼 Dr. Arhavbarien’s diverse professional journey includes roles in retail, manufacturing, logistics, and consultancy. Notably, he has worked with Tesco, Morrisons, Gosh Food Ltd, and FedEx, where he led teams, managed operations, and drove continuous improvement initiatives. His expertise spans statistical analysis, project management, and sustainable business practices.

🔬 Research Interests:

🔍📈 Dr. Arhavbarien’s research interests are centered on green value internalisation, sustainable operations, and supply chain resilience. He employs quantitative methods and tools like Qualtrics and SPSS/AMOS to analyze data, aiming to develop green criteria for stakeholder engagement and enhance eco-efficiency in industrial operations.

🏆 Awards:

🏆 Dr. Arhavbarien has been recognized for his academic and professional contributions. A notable achievement includes guiding an M.Sc. student to win the 2023 Logistics Research Network CILT (UK)’s MSc Dissertation of the Year award, reflecting his ability to inspire and mentor students.

Publications

📚 “An investigation of antecedents and consequences of green value internalisation among sampled UK enterprises” – Journal of Environmental Management, 2024

📄 “An examination of antecedents of green value internalisation for firm-level supply chain collaboration” – British Academy of Management (BAM) 2022 Conference, Alliance Manchester Business School, UK.

📄 “Green supply chain management: an investigation of firm-level antecedents of green value internalisation” – 29th European Operations Management Association (EurOMA) Conference, Berlin, Germany, 2022.📄 “An investigation of firm-level antecedents of green value internalisation for Upstream-Downstream supply chain interactions” – 32nd Production and Operations Management Society (POMS) Conference (online), 2022.