Fei Yang | Engineering | Best Researcher Award

Published on by Academic Achievements

Prof. Dr. Fei Yang | Engineering | Best Researcher Award

Prof. Dr. Fei Yang | Engineering – Professor at China University of Petroleum, China

Dr. Fei Yang is a distinguished researcher in petroleum engineering, affiliated with the China University of Petroleum (East China), Qingdao. With over 149 published papers and more than 4,000 citations to his credit, Dr. Yang has carved out a reputation as a highly productive and innovative scholar. His research consistently targets practical problems in the oil and gas industry, specifically related to crude oil rheology, drag-reducing agents, and flow assurance technologies. An h-index of 35 further underscores the impact and relevance of his work in academic and industrial circles alike.

Profile Verified:

Scopus

Education:

Dr. Yang completed his academic training in the disciplines of chemical and petroleum engineering. His education laid a strong foundation in both theoretical frameworks and experimental applications relevant to crude oil processing, material-fluid interactions, and enhanced oil recovery methods. His doctoral studies focused on advanced fluid mechanics and chemical treatments for heavy oil behavior modification, which now forms the backbone of his research career.

Experience:

Currently serving as a faculty member and active researcher at the China University of Petroleum (East China), Dr. Yang brings years of hands-on research and academic experience. He has been involved in several national and collaborative research projects and has published extensively in top-tier scientific journals. Dr. Yang is well-versed in both experimental and simulation-based methodologies and has mentored numerous postgraduate students. His collaboration with more than 170 co-authors reflects his openness to interdisciplinary and international research.

Research Interests:

Dr. Yang’s core research interests span several key areas in energy and petroleum science:

  • Rheology and emulsification of crude oil

  • Pipeline drag reduction technologies

  • CO₂-enhanced oil recovery methods

  • Nanoparticle–asphaltene interactions

  • Flow assurance and thermal conductivity of waxy oils

  • Development of novel surfactants for corrosion and flow improvement

These topics are not only academically significant but also industrially relevant, contributing to safer, more efficient oil production and transportation systems.

Awards:

While no specific awards are currently listed under Dr. Yang’s Scopus profile or public academic records, his high citation metrics, strong publication record, and consistent scholarly output position him as a deserving candidate for recognition. His eligibility for the Best Researcher Award is well-supported by tangible academic performance indicators such as peer-reviewed articles in high-impact journals, collaborative output, and global research visibility.

Selected Publications:

📘 Enhancing shear resistance in ultrahigh-molecular-weight polyolefin drag-reducing agents via siloxane bond integration – Energy, 2025 (Cited by 0)
🔬 Rheological properties and coalescence stability of degassed crude oil emulsion: Influence of supercritical CO₂ treatment – Journal of CO₂ Utilization, 2025 (Cited by 1)
🧪 Modification Effect of Asphaltene Subfractions with Different Polarities on Three kinds of Solid Nanoparticles and Their Costabilization of Crude Oil Emulsion – Energy & Fuels, 2025 (Cited by 1)
🛢️ Influence of CO₂ Treatment Pressure on the Chemical Composition and Rheological Properties of Degassed Waxy Crude Oil – ACS Omega, 2024 (Cited by 3)
🔥 Mechanism study on rheological response of thermally pretreated waxy crude oil – Geoenergy Science and Engineering, 2024 (Cited by 1)
🧴 Synthesis and Performance Evaluation of Multialkylated Aromatic Amide Oligomeric Surfactants as Corrosion Inhibitor/Drag Reducing Agents for Natural Gas Pipeline – ACS Omega, 2024 (Cited by 0)
❄️ Morphology of Wax Crystals Affects the Rheological Properties and Thermal Conductivity of Waxy Oils – Industrial & Engineering Chemistry Research, 2024 (Cited by 0)

Conclusion:

Dr. Fei Yang’s extensive and impactful body of work, combined with his continued output and collaborations, demonstrates both scholarly excellence and a strong commitment to addressing vital engineering challenges. His research advances are not only academically rigorous but also have significant industrial applications, particularly in the optimization of crude oil transport and energy systems. Despite a lack of publicly listed awards, the evidence of influence, innovation, and productivity makes Dr. Yang a strong and well-qualified candidate for the Best Researcher Award. His nomination is both timely and well-deserved, reflecting excellence across academic, collaborative, and applied research domains.

 

 

 

Madhusmita Das | software engineering | Best Researcher Award

Published on by Academic Achievements

Ms. Madhusmita Das | software engineering | Best Researcher Award

Research Scholar, National Institute of Technology Karnataka, Surathkal, India

Madhusmita Das is a Ph.D. candidate at the Institute of Technology Karnataka, Surathkal, focusing on reliability assessment of safety-critical systems through advanced machine learning models and bio-optimization algorithms. With a solid foundation in data science, she excels in analyzing user behavior and engagement, translating insights into impactful business strategies and research outcomes.

Profile

Scopus

Strengths for the Award

Diverse Research Interests and Publications: Madhusmita Das has a broad range of research interests encompassing machine learning, bio-optimization algorithms, reliability analysis, and verification methods. Her work spans numerous relevant topics, including safety-critical systems, software defect prediction, and reliability assessment of drone systems. This wide-ranging expertise is evident in her substantial number of high-impact publications across various prestigious conferences and journals.

Impactful Contributions: Her research on “Hybrid Bio-Optimized Algorithms for Hyperparameter Tuning in Machine Learning Models” and other related works demonstrates her ability to apply complex algorithms to practical problems, making significant contributions to the field of machine learning and system reliability.

Recognition and Awards: The provisional selection for the “Best Researcher Award” for her work in hybrid bio-optimized algorithms reflects her recognition in the academic community. Her technical paper presentation at state levels and qualified GATE also underscore her expertise and commitment to her field.

Extensive Experience and Skills: Madhusmita’s background in programming, big data technologies, machine learning, and data visualization tools is robust. Her skills in managing research from inception to publication further demonstrate her comprehensive approach and capability.

Areas for Improvement

Research Diversity and Novelty: While her research is extensive, focusing on a few emerging or less explored areas could enhance the novelty of her contributions. This might involve delving into cutting-edge topics like quantum computing applications in machine learning or the integration of AI with emerging technologies.

Broader Impact and Collaboration: Strengthening collaborations with other researchers or institutions could broaden the impact of her work. Collaborations can lead to interdisciplinary research opportunities, potentially increasing the scope and application of her findings.

Public Engagement: Expanding efforts to disseminate research findings to non-specialist audiences or through popular science platforms could enhance the visibility and impact of her work. Engaging in public lectures, webinars, or media could further her influence.

Education 🎓

Madhusmita is pursuing her Ph.D. in Computer Science/Information Technology at the Institute of Technology Karnataka, Surathkal (2019-Present), with a CGPA of 8.67. Her research covers topics such as verification & validation, reliability analysis, and bio-optimization algorithms. She completed her M.Tech. with honors from NIT Raipur in 2012 and her B.Tech. from SOA University, Bhubaneswar, in 2008.

Experience 💼

Madhusmita has served as an Assistant Professor at MVJ College of Engineering, Bangalore (Nov 2013 – Nov 2016), and Sanjeevani College of Engineering, Pune (Jul 2012 – Nov 2013). Her work spans teaching, research, and project mentoring, contributing significantly to the academic and research communities.

Research Interests 🔬

Her research interests include verification and validation methods, formal techniques, risk analysis, system reliability, and software defect prediction. She is also passionate about machine learning and computational intelligence, focusing on bio-optimization algorithms and optimization techniques.

Awards 🏆

Madhusmita was provisionally selected for the “Best Researcher Award” for her work on hybrid bio-optimized algorithms in machine learning, set to be awarded in 2024. She also earned recognition for her state-level presentation on AI in 2011 and qualified GATE in 2010.

Publications Top Notes📚

Hybrid Bio-Optimized Algorithms for Hyperparameter Tuning in Machine Learning Models: A Software Defect Prediction Case Study, Mathematics, 2024, MDPI.

Formal Specification and Verification of Drone System using TLA+: A Case Study, 2022 IEEE/ACIS 23rd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2022, pp. 156-161.

Reliability Assessment of a Drone Communication System using Truncated Markov Analysis, 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2023, pp. 1-6.

Fault Tree Analysis: A Review on Analysis, Simulation Tools, and Reliability Dataset for Safety-critical Systems, International Conference on Mining for a Greener Future: Technological developments and Sustainable Practices (ICMFGF 2024), 2024, NITK Surathkal, India.

Safety Assessment of Railway Crossing Junction Via Petri Nets, 5th International Conference on Innovative Trends In Information Technology ICITIIT’24, 2024, IIIT Kottayam, India, pp. 1-8.

Conclusion

Madhusmita Das is a strong candidate for the Best Researcher Award due to her significant contributions to machine learning, data science, and system reliability. Her extensive publication record, impactful research, and recognized achievements highlight her as a leading figure in her field. Addressing areas for improvement, such as exploring novel research avenues and enhancing public engagement, could further strengthen her candidacy and broaden the impact of her work.