Yingyuan Liu | Engineering | Women Researcher Award

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Ms. Yingyuan Liu | Engineering | Women Researcher Award

Professor | Shanghai Normal university | China

Dr. Liu Yingyuan is an accomplished researcher and faculty member specializing in the application of artificial intelligence (AI) in fluid machinery. With a strong academic foundation and extensive professional experience, she has contributed significantly to advancing machine learning models, turbulence analysis, airfoil optimization, and fault diagnosis. Currently serving at Shanghai Normal University, Dr. Liu’s expertise bridges the intersection of AI and fluid mechanics, making her a leader in her field.

Profile

Scopus

Education

Dr. Liu Yingyuan earned her Ph.D. in Fluid Machinery from Zhejiang University in 2016, where she focused on the intricate dynamics of fluid mechanics and advanced computational methods. Her undergraduate studies in Process Equipment and Control Engineering at the China University of Petroleum (East China), completed in 2011, laid a strong foundation in engineering principles and process optimization.

Experience

Dr. Liu has been a faculty member at Shanghai Normal University, where she combines her deep research expertise with her passion for teaching. Her academic career is marked by impactful research, collaborative projects, and mentorship of students, particularly in the realm of AI applications in fluid mechanics. Her contributions extend beyond academia through her active engagement in professional committees and collaborations with industry experts.

Research Interests

Dr. Liu’s research is centered on leveraging artificial intelligence technologies to address complex challenges in fluid machinery. Her interests include machine learning modeling for turbulence, optimal airfoil shape design, and fault diagnosis in fluid machinery. By integrating AI with engineering, she has developed innovative solutions that enhance the efficiency and reliability of mechanical systems.

Awards

Dr. Liu’s innovative research has garnered recognition in the academic and professional community. Notably, her studies in machine learning-driven fault diagnosis and airfoil optimization have earned her nominations for awards in engineering and AI applications. Her commitment to excellence continues to inspire peers and students alike.

Publications

  1. Liu YY, Shen JX, Yang PP, Yang XW. A CNN-PINN-DRL driven method for shape optimization of airfoils. Engineering Application of Computational Fluid Mechanics, 2025, 19(1): 2445144.
    • Cited by: Researchers developing AI-driven aerodynamics models.
  2. Shen JX, Liu YY, Wang Leqin.* A Deep Learning-Based Method for Airfoil Parametric Modeling. Chinese Journal of Engineering Design, 2024, 31(03): 292-300.
    • Cited by: Articles on parametric modeling techniques.
  3. Liu D, Liu YY. A Deep Learning-Based Fault Diagnosis Method for Fluid Machinery with Small Samples. Journal of Shanghai Normal University (Natural Sciences), 2023, 52(02): 264-271.
    • Cited by: Studies on fault diagnosis in mechanical systems.
  4. Liu YY, Gong JG, An K, Wang LQ. Cavitation Characteristics and Hydrodynamic Radial Forces of a Reversible Pump–Turbine at Pump Mode. Journal of Energy Engineering, 2020, 146(6): 04020066.
    • Cited by: Publications on hydrodynamics and pump-turbine systems.
  5. Liu Y Y, An K, Liu H, et al. Numerical and experimental studies on flow performances and hydraulic radial forces of an internal gear pump with a high pressure. Engineering Applications of Computational Fluid Mechanics, 2019, 13: 1, 1130-1143.
    • Cited by: Research focused on internal gear pump performance.
  6. Liu Y Y, Wang L Q, Zhu Z C.* Experimental and numerical studies on the effect of inlet pressure on cavitating flows in rotor pumps. Journal of Engineering Research, 2016, 4(2): 151-171.
    • Cited by: Studies on cavitation phenomena in rotor pumps.
  7. Liu Y Y, Wang L Q, Zhu Z C.* Numerical study on flow characteristics of rotor pumps including cavitation. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2015, 229(14): 2626-2638.
    • Cited by: Articles on numerical modeling of fluid flows.

Conclusion

Dr. Liu Yingyuan exemplifies the integration of advanced engineering knowledge and AI-driven innovation. Her pioneering contributions to the fields of fluid mechanics and machinery have not only pushed technological boundaries but also inspired the next generation of engineers and researchers. Dr. Liu’s work continues to serve as a cornerstone for advancements in intelligent mechanical systems, ensuring her lasting impact on both academia and industry.

Shams Al Ajrawi | Computer engineering | Best Researcher Award

Posted on by Academic achievements

Dr. Shams Al Ajrawi | Computer Engineering | Best Researcher Award

Assistant professor at Alliant International University, United States

Shams Al Ajrawi is a Lead Software Engineer and academic researcher with over a decade of experience in web application and backend development. His expertise spans across full-stack development, artificial intelligence (AI), data science, and Brain-Computer Interface (BCI) technologies. With a keen focus on solving intricate challenges, Shams has successfully led numerous industry and academic projects that have resulted in substantial financial savings and technological advancements. He has been actively involved in teaching, curriculum development, and research, playing a pivotal role in mentoring the next generation of engineers and computer scientists. His work bridges the gap between theoretical research and practical implementation, contributing to both corporate innovation and academic progress.

Profile: 

SCOPUS

Education:

Shams Al Ajrawi holds a Ph.D. in Electrical and Computer Engineering from a joint program between the University of California, San Diego, and San Diego State University, where his research focused on Brain-Computer Interface (BCI) applications. Prior to his Ph.D., he earned a Master’s degree in Electrical and Computer Engineering from the New York Institute of Technology and a Bachelor of Science in Computer Engineering from the Technological University. His academic journey is marked by a strong foundation in electrical engineering, computer science, and AI, with a specific focus on innovative applications in neuroscience and data processing.

Experience:

Shams has held prominent roles in both industry and academia. As a Lead Software Engineer at John Wiley & Sons, he led initiatives to enhance technology efficiency and reduce costs, including the integration of AI-based solutions like ChatGPT. His role also involved collaborating with corporate clients and managing cross-functional teams using Agile methodologies. In academia, he has served as an Associate Professor and Graduate Program Manager at Alliant International University, where he developed curricula, conducted research, and managed grants. Additionally, Shams is a Researcher Affiliate at UC San Diego’s Qualcomm Institute, focusing on BCI signal interpretation, and he has taught at several institutions, including San Diego State University and National University.

Research Interest:

Shams Al Ajrawi’s primary research interests lie in Brain-Computer Interface (BCI) technology, artificial intelligence, and signal processing. His work in the BCI domain has focused on improving signal extraction and classification, using techniques such as hierarchical recursive feature elimination and flexible wavelet transformation. His research aims to enhance the efficiency and accuracy of interpreting brain signals, particularly for applications related to assisting individuals with spinal cord injuries. Additionally, he explores the integration of AI and machine learning techniques in software development, cybersecurity, and data analytics, striving to develop innovative solutions that merge computational efficiency with real-world applications.

Awards:

Shams has been recognized for his contributions in both industry and academia. He received promotions and excellence awards for two consecutive years at John Wiley & Sons for his leadership and innovative approach in software engineering. In 2023, he was appointed as an Associate Professor at Alliant International University in recognition of his contributions to academia. He has also earned several professional certifications, including the ISACA certification (2023–2028) and Cisco’s CCNA certification, further solidifying his expertise in software engineering and networking.

Publications:

Shams Al Ajrawi has authored numerous papers in prestigious journals, focusing on BCI applications, RFID, and AI. Some of his notable publications include:

“Investigating Feasibility of Multiple UHF Passive RFID Transmitters Using Backscatter Modulation Scheme in BCI Applications” (2017) – Published in IEEE International Symposium on Performance Evaluation of Computer and Telecommunication Systems Cited by 35 articles.

“Bi-Directional Channel Modeling for Implantable UHF-RFID Transceivers in BCI Application” (2018) – Published in Journal of Future Generation Computer Systems, Elsevier Cited by 42 articles.

“Efficient Balance Technique for Brain-Computer Interface Applications Based on I/Q Down Converter and Time Interleaved ADCs” (2019) – Published in Informatics in Medicine Unlocked, Elsevier Cited by 30 articles.

“Hybrid MAC Protocol for Brain-Computer Interface Applications” (2020) – Published in IEEE Systems Journal Cited by 27 articles.

“Cybersecurity in Brain-Computer Interfaces: RFID-Based Design-Theoretical Framework” (2020) – Published in Informatics in Medicine Unlocked, Elsevier Cited by 22 articles.

Conclusion:

Shams Al Ajrawi stands out as a highly accomplished candidate for a “Best Researcher Award.” His rich experience, cutting-edge research, and impactful contributions across both industry and academia position him as a leading figure in his field. However, by narrowing his research focus and expanding interdisciplinary and mentorship efforts, he could enhance his candidacy even further. Overall, he appears highly suitable for the award.

Madhusmita Das | software engineering | Best Researcher Award

Posted 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.

Dr. Adekunle Akanni Adeleke – Engineering – Best Researcher Award

Posted on by Academic achievements

Dr. Adekunle Akanni Adeleke - Engineering - Best Researcher Award

NILE UNIVERSITY OF NIGERIA - Nigeria

Professional Profiles

Google Scholar

Early Academic Pursuits

Dr. Adekunle Akanni Adeleke's academic journey began with his primary education at A.U.D, Ila Orangun, followed by secondary schooling at the School of Science, Ikirun, Osun State. He pursued his tertiary education at the University of Ilorin, completing a Bachelor's degree in Mechanical Engineering in 2009. This laid the groundwork for further academic achievements, including a Master's degree in Mechanical Engineering in 2013, where he graduated with distinction, and a Ph.D. in Mechanical Engineering in 2018, demonstrating his commitment to excellence in his field.

Professional Endeavors

Following his academic pursuits, Dr. Adeleke embarked on a professional journey characterized by dedication and expertise in the field of mechanical engineering. He obtained his registration as an engineer from The Council for the Regulation of Engineering in Nigeria (COREN) in July 2018, solidifying his credentials as a recognized professional in his field. Additionally, he became a member of both The Nigerian Institution of Mechanical Engineers (NIMechE) and the Nigeria Young Academy, further establishing his presence within the engineering community.

Contributions and Research Focus On Engineering

Dr. Adeleke's research focus spans various areas within mechanical engineering, reflecting his interdisciplinary approach to problem-solving and innovation. His doctoral research likely delved into advanced topics within mechanical engineering, potentially exploring areas such as renewable energy systems, robotics, or materials science. His contributions to the field may include novel insights, methodologies, or technological advancements aimed at addressing pressing societal challenges or advancing scientific knowledge.

Accolades and Recognition In Engineering

Dr. Adeleke's academic and professional achievements have earned him recognition within the engineering community. His registration as an engineer by COREN signifies his competence and adherence to professional standards. Additionally, his memberships in esteemed organizations like NIMechE and the Nigeria Young Academy underscore his standing as a respected figure in the field of mechanical engineering.

Impact and Influence

Dr. Adeleke's work and expertise have likely had a significant impact on both academia and industry. Through his research contributions, he may have advanced the state of knowledge in his field, potentially leading to practical applications or technological innovations. His involvement in professional organizations and academic institutions further amplifies his influence, as he likely contributes to shaping the direction of engineering education, research, and practice.

Legacy and Future Contributions For Engineering

As Dr. Adeleke continues his professional journey, his legacy as a dedicated engineer and researcher is poised to grow. His contributions to mechanical engineering, whether through research, education, or professional practice, will leave a lasting impact on the field and inspire future generations of engineers. Moving forward, he is likely to continue pushing the boundaries of knowledge and innovation, further cementing his reputation as a leader in mechanical engineering.

Notable Publications

Combustion characteristics of fuel briquettes made from charcoal particles and sawdust agglomerates 2019

Evaluation of thermal decomposition characteristics and kinetic parameters of melina wood 2022

Investigation of physicochemical characteristics of selected lignocellulose biomass 2022