Sina Sayardoost Tabrizi | Data Analytics in Upstream Operations | Best Researcher Award

Published on by Petroleum Engineering

Dr. Sina Sayardoost Tabrizi | Data Analytics in Upstream Operations | Best Researcher Award

Senior Lecturer and Director of Dean’s Office at University of Tehran | Iran

Dr. Sina Sayardoost Tabrizi is a Senior Lecturer and Director of the Dean’s Office at the University of Tehran (Kish International Campus), specializing in industrial management, artificial intelligence, and sustainable operations. He holds a Ph.D. in Industrial Management and both B.Sc. and M.Sc. degrees in Computer Engineering, establishing a strong interdisciplinary foundation bridging technology and management. With over eight years of academic experience, he has supervised more than 30 student projects and published over 15 peer-reviewed papers in Q1 and Scopus-indexed journals. Dr. Sina Sayardoost Tabrizi is the founder of the Metaverse and Emerging Technologies Laboratory, where he leads innovative projects integrating AI, data analytics, and digital transformation across education, industry, and sustainability sectors. His research spans sustainable supply chain management, dynamic network data envelopment analysis (DNDEA), machine learning, and decision-support systems, with notable contributions to the petrochemical and manufacturing industries. His scholarly output includes 8 major research projects, a co-authored academic textbook, and one patent under process for an AI-driven decision-support framework. Beyond academia, he has collaborated with national and international partners—including Muscat University—on consultancy and innovation initiatives focusing on efficiency optimization, digital learning platforms, and AI ethics. As a reviewer for international journals in operations research and a member of professional organizations such as IFORS and the Iranian Association of Management Science, he contributes actively to the global research community. His work has received recognition for integrating advanced computational models with sustainable industry practices, improving efficiency in resource-intensive systems by measurable margins. Dr. Sina Sayardoost Tabrizi commitment to interdisciplinary research, educational innovation, and technological ethics positions him as a forward-thinking academic leader dedicated to advancing responsible AI, sustainability, and data-driven decision-making for societal and industrial progress.

Profile: Google Scholar

Featured Publications

Sayardoost Tabrizi, K. S., Sabzian, A., & Moeini, A. (2024). TAM-based model for evaluating learner satisfaction of e-learning services: Case study—E-learning system of University of Tehran.

Sayardoost Tabrizi, S., Yakideh, K., Moradi, M., & Ebrahimpour, M. (2025). Clustering with machine learning and using NDEA in development planning: A case study in the petrochemical two-stage SSC.

Sayardoost Tabrizi, S., Yakideh, K., Moradi, M., & Ebrahimpour, M. (2024). Assessing sustainability of supply chain performance using machine learning and network data envelopment analysis.

Sayardoost Tabrizi, S., Sabzian, A., & Moeini, A. (2024). A hybrid model for evaluation of e-learning user satisfaction with TAM and ELQ approach.

Sayardoost Tabrizi, S., Abideen, A. Z., & Moeini, A. (2025). A novel machine learning and DNDEA framework for sustainable efficiency measurement in a circular two-stage supply chain.

Sayardoost Tabrizi, S., Yousefi, S., & Yakideh, K. (2025). Forecasting efficiency of two-stage petrochemical sustainable supply chains using deep learning and DNDEA model. Operations Research Perspectives.

Adarsh Kumar Arya | Oil and Gas | AI and Automation in Petroleum Award

Published on by Petroleum Engineering

Dr. Adarsh Kumar Arya | Oil and Gas | AI and Automation in Petroleum Award

Associate Professor at Harcourt Butler Technical University | India

Dr. Adarsh Kumar Arya is an accomplished academic and researcher with nearly two decades of expertise in chemical engineering, specializing in oil and gas pipeline engineering, natural gas optimization, and sustainable energy technologies. Currently serving as Associate Professor in the Department of Chemical Engineering at Harcourt Butler Technical University (HBTU), Kanpur, he has also held significant academic and administrative responsibilities, including Associate Dean of Incubation and Startups and coordinator roles under national higher education initiatives. He earned his Ph.D. in Chemical Engineering with a focus on natural gas pipeline optimization from the University of Petroleum and Energy Studies, Dehradun in 2015, following an M.Tech. in Chemical Engineering from HBTI Kanpur and a B.Tech. in Chemical Engineering from BIET Jhansi, complemented by specialized training in Piping Engineering from IIT Bombay. His career spans academia and industry, with professional experience at Worley Parsons on the TANAP Gas Pipeline Project, and consultancy contributions such as hydrogen compatibility studies for Indraprastha Gas Grid Limited. Dr. Arya has published extensively in reputed international journals and conference proceedings, covering areas such as multi-objective optimization of pipeline networks, hydrogen embrittlement in pipeline structures, biomass supply chain cost reduction, blockchain applications in the oil and gas industry, and corrosion mitigation in steel pipelines. He has also authored and edited multiple books on machine learning, optimization, and chemical engineering applications, alongside supervising completed and ongoing doctoral research in pipeline optimization, hydrogen transportation, and corrosion control. His scholarly work has been recognized with prestigious research awards, including the Annual Research Award (2021), a Research Excellence Award (2024) from HBTU Kanpur presented by the Hon’ble Governor of Uttar Pradesh, and a significant research grant award in 2022. With a record of five patents, consultancy projects, and contributions to curriculum design and advanced teaching, he has established himself as a thought leader in pipeline engineering and sustainable chemical processes. His research impact is reflected in 375 citations across 226 documents, 44 publications, and an h-index of 10, highlighting the depth and relevance of his contributions. Dr. Arya remains committed to advancing chemical engineering knowledge and practices through research, innovation, and mentorship, shaping both industry solutions and the next generation of engineers.

Profile: Scopus | ORCID

Featured Publications

Arya, A. K., & Kapoor, A. (2024). Environmental consequences of wind energy technologies.

Arya, A. K., Shreya, Ponnuchamy, M., Pal, D. B., & Kapoor, A. (2024). Algae biomass valorization for wastewater remediation.

Shingan, B., Pujari, M., Arya, A. K., & Singh, V. (2024). Optimizing air separation and LNG cold utilization: Energy savings, exergy efficiency, and system reliability.

Arya, A. K., Sastry, S. V. A. R., Sneha, S., Gupta, B., & Pujari, M. (2024). Recent developments in leak detection techniques for pipelines: A critical evaluation.

Mzili, T., Mzili, M., Abatal, A., & Arya, A. K. (2025). A spotted hyena algorithm for quadratic allocation problems: A novel bio-inspired solution.

Srivastava, D., & Arya, A. K. (2025). A multi-objective model to improve the profitability and reduce carbon emissions in a natural gas pipeline network.

Mzili, T., Mzili, M., Bouderba, S. I., Abatal, A., Aribowo, W., & Arya, A. K. (2025). Interoperability in Internet of Things: Taxonomies and open challenges.