Tahir Cetin Akinci | Data Analytics in Upstream Operations | Best Research Article Award

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Dr. Tahir Cetin Akinci | Data Analytics in Upstream Operations | Best Research Article Award

Scientist at University of California Riverside, United States

Dr. Tahir Çetin Akıncı is a distinguished academician and researcher in electrical engineering, particularly known for his impactful work in artificial intelligence, renewable energy, and advanced signal processing. With a professional trajectory that spans over two decades, he has consistently contributed to advancing knowledge and innovation in intelligent systems and power electronics. His commitment to both academic excellence and real-world problem-solving has earned him global recognition, positioning him as a thought leader in his field.

Profile

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Education

Dr. Akıncı began his academic journey at Klaipeda University in Lithuania, earning his undergraduate degree in electrical engineering in 2000. He later pursued graduate studies at Marmara University, where he completed his master’s degree in 2005 and Ph.D. in 2010. These formative academic experiences laid the groundwork for his future research directions, particularly in the domains of energy systems and machine learning applications. His educational path is marked by a solid foundation in electrical systems theory, enriched by practical insights into data-driven methodologies.

Experience

His professional career commenced as a Research Assistant at Marmara University, where he served from 2003 to 2010. He then joined Istanbul Technical University (ITU), advancing through academic ranks to become a full professor by 2020. Currently, Dr. Akıncı serves at the University of California, Riverside, contributing to international collaborations and high-impact research initiatives. Throughout his tenure in academia, he has mentored students, led research projects, and collaborated across disciplines to address critical engineering challenges.

Research Interest

Dr. Akıncı’s research interests are both broad and deep, encompassing renewable energy systems, artificial neural networks, deep learning, machine learning, cognitive systems, signal processing, and data analysis. His multidisciplinary approach allows him to tackle complex problems—ranging from optimizing photovoltaic systems to diagnosing electrical motor faults using AI. His work in renewable energy technologies and smart systems not only enhances system efficiencies but also aligns with global sustainability goals. He is particularly passionate about the integration of AI in diagnostics, predictive maintenance, and energy management, striving to create systems that are not only intelligent but also resilient and sustainable.

Award

His contributions have been recognized through multiple prestigious awards, most notably the International Young Scientist Excellence Award and the Best Researcher Award in 2022. These accolades reflect his pioneering work and the high regard he holds within the scientific community. In addition to these honors, Dr. Akıncı has played critical roles as editor and guest editor for leading journals and serves on scientific committees of several high-profile international conferences, further underscoring his influence in shaping future directions in electrical engineering and AI.

Publication

Among his extensive list of publications, several recent papers stand out for their innovative approaches and significant citations. For instance:

“Sustainable pathways for hydrogen production: Metrics, trends, and strategies for a zero-carbon future,” Sustainable Energy Technologies and Assessments, 2025 – cited for its strategic insights on green hydrogen.

“Revealing GLCM Metric Variations across Plant Disease Dataset,” Electronics, 2024 – contributes to deep learning applications in agriculture.

“Optimization of Neuro-controller Application for MPPT in Photovoltaic Systems,” Electric Power Components and Systems, 2024 – enhances energy efficiency using AI.

“Time Series Forecasting Utilizing AutoML,” Information, 2024 – applies automated ML for forecasting in diverse datasets.

“Advanced Dual RNN Architecture for Electrical Motor Fault Classification,” IEEE Access, 2023 – highly cited for its innovation in motor diagnostics.

“Machine Learning-Based Error Correction Codes and Communication Protocols for Power Line Communication,” IEEE Access, 2023 – strengthens smart grid reliability.

“Effect of LED Light Frequency on an Object in Terms of Visual Comfort,” Electric Power Components and Systems, 2024 – explores visual ergonomics in energy-efficient lighting.

Conclusion

In conclusion, Dr. Tahir Çetin Akıncı exemplifies the ideal candidate for this award through his unwavering commitment to scientific advancement, innovation in engineering education, and leadership in multidisciplinary research. His work bridges the gap between theory and application, aiming to develop technologies that not only solve current engineering problems but also anticipate future challenges. Through his dedication, he continues to inspire the next generation of engineers and scientists, fostering a more intelligent and sustainable world.

Massine Bouchakour | Petroleum Geology | Best Researcher Award

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Dr. Massine Bouchakour | Petroleum Geology | Best Researcher Award

PhD at Southwest Petroleum University, China

Massine Bouchakour is a highly driven postdoctoral researcher in marine geology currently based at Southwest Petroleum University in China. With a multidisciplinary and international approach, his research focuses on deep-marine sedimentary systems, seismic interpretation, and reservoir connectivity in structurally complex geological settings. Having been trained across several institutions and mentored by global experts in geology, Bouchakour combines advanced scientific techniques with a passion for knowledge dissemination and collaborative research. His academic journey reflects not only deep technical competence but also an ongoing commitment to applied geoscience, interdisciplinary research, and academic mentorship.

Profile

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Education

Massine Bouchakour began his formal education in sedimentology with an MSc (Hons) at the University of Sciences and Technology Houari-Boumédiène (USTHB) in Algeria, focusing on Paleozoic stratigraphy and sedimentary processes in the Ougarta Basin. His thesis, awarded first-class honors, laid the groundwork for his interest in sequence stratigraphy and basin evolution. He later pursued a PhD at Southwest Petroleum University (SWPU) in China, where he specialized in seismic interpretation of submarine channels and their interaction with tectonic structures. Supported by the Sichuan Provincial Government and the National Natural Science Foundation of China (NSFC), his doctoral research explored geomorphological controls and depositional patterns in the Niger Delta. His ongoing postdoctoral work at SWPU further extends this expertise into global deep-marine systems.

Experience

With over a decade of academic and applied research experience, Bouchakour has played key roles in several international and industry-sponsored projects. His expertise spans seismic geomorphology, stratigraphy, and reservoir characterization. During his postdoctoral tenure, he has collaborated with institutions in Portugal, Romania, and the UK, contributing to efforts funded by CNOOC International and SINOPEC. He has also been instrumental in supervising PhD students and mentoring laboratory research in seismic and borehole data analysis. His career is marked by leadership in developing predictive models for deep-marine sand distribution and contributing to research initiatives such as the Deep-marine Sedimentary Architecture Knowledge Store. He is actively involved in scientific communication, presenting at major conferences, and publishing in top-tier geology journals.

Research Interests

Massine Bouchakour’s research interests center on understanding the architecture and evolution of deep-water depositional systems, particularly in tectonically active margins. He investigates sedimentary processes, seismic facies, sequence stratigraphy, and reservoir sand connectivity using multi-scale data, including 3D seismic surveys and core analysis. His work emphasizes the role of structural deformation in influencing sediment routing and accumulation, as well as the implications for hydrocarbon exploration and offshore carbon storage. He is equally invested in seismic attribute interpretation, field-outcrop integration, and the development of novel geological models to predict subsurface behavior and optimize production well designs.

Awards and Grants

Throughout his career, Bouchakour has earned significant recognition through competitive academic and industrial funding. These include the Chengdu Postdoctoral Research Station grant (2023) and a major NSFC-funded project (2020) supporting his PhD work. He also received the SWPU PhD scholarship with full tuition and accommodation support. In addition, his contributions to industrial research have been recognized in projects sponsored by CNOOC and SINOPEC, where he supported reservoir modeling, structural analysis, and seismic interpretation. Notably, his 2022 paper in Marine and Petroleum Geology was ranked among the top ten downloaded papers by SSRN in the field of marine sediments.

Publications

Bouchakour has authored impactful publications across international peer-reviewed journals. His 2025 paper in Basin Research, titled “Kinematics of submarine channels in response to bank failures,” provides insights into slope instability effects on channel migration.

His 2024 article in Marine and Petroleum Geology, “Compartmentalization of submarine channel splays controlled by growth faults and mud diapir,” explores fault-controlled sediment distribution. Another 2023 Basin Research study investigates “Lateral migration and channel bend morphology around growing folds” in the Niger Delta.

His 2022 work in Marine and Petroleum Geology, “Evolution of submarine channel morphology in intra-slope mini-basins,” based on 3D seismic data, has been widely cited for its methodological rigor.

His collaboration in a 2025 Marine and Petroleum Geology paper, “Tectono-stratigraphic evolution of multiphase rifts,” and two co-authored 2024–2025 stratigraphy-focused publications in Journal of Palaeogeography and Oil and Gas Geology have further solidified his status as a respected geoscientist.

These works have been cited in numerous geological modeling and sedimentology studies globally.

Conclusion

Massine Bouchakour represents a new generation of geoscientists whose global experience, technical versatility, and interdisciplinary insight position him as a leader in marine sedimentology and subsurface geological research. Through his ongoing commitment to applied geoscience, teaching, and international collaboration, he continues to make meaningful contributions to both academic knowledge and industry practice. His research outputs not only enrich scientific understanding but also provide practical frameworks for addressing critical challenges in energy exploration and environmental sustainability.

Ashutosh Sharma | Artificial Lift Systems | Best Researcher Award

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Dr. Ashutosh Sharma | Artificial Lift Systems | Best Researcher Award

Graduate Research Assistant at University of OKlahoma, United States

Ashutosh Sharma is an experienced doctoral candidate in Petroleum Engineering with a solid foundation in data science and energy systems. He specializes in applying advanced machine learning techniques to optimize drilling operations and subsurface analysis. With a practical industry background and academic expertise, Ashutosh has contributed to real-time drilling efficiency, rock-bit interaction studies, and predictive modeling for petrophysical properties. His multidisciplinary approach bridges traditional petroleum engineering practices with modern data-driven solutions, making him a well-rounded professional prepared to address the evolving challenges of the energy sector.

Profile

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Education

Ashutosh is pursuing a Ph.D. in Petroleum Engineering at the University of Oklahoma with a perfect GPA of 4.0, focusing his dissertation on incorporating rock behavior into real-time drilling analysis. Complementing this, he is also earning an M.S. in Data Science & Analytics from Georgia Institute of Technology, maintaining a GPA of 3.9. He holds a prior M.S. in Petroleum Engineering from the University of Oklahoma, where he researched centrifugal packer-type downhole separators. His academic foundation was established with a B.S. in Petroleum Engineering from the Maharashtra Institute of Technology in India, where his capstone project centered on performance modeling and optimization in undersaturated oil reservoirs.

Experience

Ashutosh’s diverse work experience spans both academic research and hands-on industry roles. Most recently, he interned at Pioneer Natural Resources (now under ExxonMobil), where he developed a digital framework for drill string vibration modeling using surface and downhole data from 18 wells in the Midland Basin. Prior to that, he interned at Ensign Drilling, focusing on real-time stick-slip vibration detection using machine learning. Since 2020, he has served as a Graduate Research Assistant at the University of Oklahoma, contributing to DOE-funded projects on rock-bit interaction, real-time drilling efficiency modeling, and petrophysical parameter prediction at the bit. He also brings industry experience from Raeon Energy Services LLP, where he worked in well intervention design, site operations, and bid proposal drafting. Earlier, during an internship at NOV, he streamlined data systems and tools for drill pipe evaluation.

Research Interest

Ashutosh’s research interests lie at the intersection of petroleum engineering and data analytics, focusing on real-time drilling analysis, rock-bit interaction modeling, machine learning applications in drilling optimization, and subsurface prediction. He is especially driven by the application of data-driven approaches to enhance drilling safety, efficiency, and reservoir characterization. His work seeks to enable predictive decision-making at the rig floor, transform vibration analysis methodologies, and innovate in the field of downhole separation and petrophysical log projection.

Award

Ashutosh has been recognized for both his academic achievements and professional contributions. He received the SPE General Scholarship in the Ph.D. category, sponsored by the SPE OKC chapter, for two consecutive years (2022 and 2023). As an active participant in student competitions, he won three 1st place titles as part of the University of Oklahoma’s Petrobowl team from 2017 to 2021. He also served as Vice-President of the OU SPWLA student chapter during 2019–2020. Notably, he received a Letter of Appreciation from a project head for high-quality services rendered in the Krishna Godavari and Cambay basins. His early achievements include winning 1st prize at the MIT SPE AIIIP Case Study Challenge, sponsored by Schlumberger.

Publication

Ashutosh’s scholarly work reflects a consistent focus on machine learning applications in petroleum systems. His notable journal articles include:

Evaluating PDC bit-rock interaction models to investigate torsional vibrations in Geothermal drilling (Geothermics, Elsevier, 2024; cited by 18 articles),

Real-time lithology prediction at the bit using machine learning (Geosciences, MDPI, 2024; cited by 9 articles),

Predicting separation efficiency of a downhole separator using machine learning (Energies, MDPI, 2024; cited by 7 articles).
He has also presented several conference papers, including at URTEC Buenos Aires (2023), SPE Offshore Europe Aberdeen (2023), SPE OKC Symposium (2023), US Rock Mechanics Symposium (2021), and the SPE Artificial Lift Conference-Americas (2020). His MS thesis was focused on the experimental evaluation of a centrifugal packer-type downhole separator.

Conclusion

Ashutosh Sharma’s multidisciplinary skill set, merging petroleum engineering fundamentals with cutting-edge data analytics, positions him uniquely in the energy industry. Through his academic rigor, research innovation, and industry collaborations, he has demonstrated a commitment to advancing efficient, safe, and sustainable drilling practices. As he completes his Ph.D. and dual Master’s degrees, Ashutosh is poised to contribute meaningfully to organizations leading the energy transition and digital transformation in upstream oil and gas operations.