Yuqing Hu | Engineering | Outstanding Contribution Award

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Mr. Yuqing Hu | Engineering | Outstanding Contribution Award

Vice President from Chongqing Institute of Surveying and Monitoring for Planning and Natural Resources, China

Yuqing Hu is a distinguished professional in the field of geographic information systems and cadastral surveying, currently serving as the Vice Dean at the Chongqing Planning and Natural Resources Survey and Testing Institute. With over three decades of experience in land resource management, Hu has demonstrated exceptional expertise in leading high-impact projects related to land survey, cadastral mapping, and real estate registration. His career has been marked by a continuous trajectory of advancement through various leadership roles across government and technical institutions. Hu has played a pivotal role in the development of several award-winning systems and technologies that have advanced the precision and efficiency of land monitoring and property registration processes in China. His efforts have been formally recognized through numerous national-level awards, including the Science and Technology Progress Award and multiple Excellent Engineering Awards. He is also credited as a key contributor to patented innovations and published research. Through his combined experience in technology, policy, and strategic leadership, Yuqing Hu has significantly contributed to the modernization and digital transformation of natural resource monitoring and land information systems. His achievements position him as a highly suitable candidate for honors recognizing outstanding contributions to applied research and development.

Professional Profile

Education

Yuqing Hu holds a Bachelor’s degree in Engineering, majoring in Cartography, from Wuhan University of Surveying and Mapping, one of China’s foremost institutions in the field of geospatial sciences. He completed his studies from 1988 to 1992, laying a strong academic foundation in geographic information systems, topographic science, and land surveying technologies. During his time at Wuhan University, Hu received training in advanced mapping techniques and cadastral analysis, which would later become central to his professional expertise. The program provided a rigorous blend of theoretical knowledge and practical application, allowing him to develop early proficiency in geospatial data interpretation, field mapping, and land resource planning. His education equipped him with a solid understanding of both the technical and regulatory frameworks underpinning land survey and natural resource governance in China. This academic background continues to underpin his contributions to cadastral reform, land registration system design, and geospatial data-driven policy implementation. Hu’s academic credentials, combined with his professional trajectory, reflect a rare synergy of educational excellence and applied technological leadership, making him an authority in the domains of cartography, property data modeling, and land information systems.

Professional Experience

Yuqing Hu has built an extensive professional career spanning over 30 years, largely centered around land surveying, cadastral registration, and geographic information system (GIS) development. Beginning in 2013, he served as Vice President and Party Committee Member of the Chongqing Land Resources and Housing Survey and Planning Institute. He then held several key leadership roles, including Deputy Director of the Chongqing Land and Housing Ownership Registration Center and Deputy Director of the Chongqing Real Estate Registration Center. Between 2019 and 2022, he led the Nan’an Real Estate Registration Center as Secretary and Director of the Party Branch, during which he was appointed as a third-level professional technician. Since December 2022, Hu has served as Vice President of the Chongqing Planning and Natural Resources Survey and Testing Institute, where he continues to guide major initiatives related to urban and rural land administration, cadastral data integration, and natural resource monitoring. He is recognized for his technical expertise at the Level 3 level and recently qualified as a registered surveyor. His professional journey reflects a rare combination of strategic leadership and deep technical capability, making him an influential figure in public land management and spatial information infrastructure in China.

Research Interests

Yuqing Hu’s research interests are centered on cadastral surveying, property rights registration systems, land resource planning, and the integration of geospatial technologies into real-world governance frameworks. His focus includes the development and application of automated 3D modeling systems, intelligent land monitoring technologies, and the design of digital platforms for real estate data management. Hu is particularly interested in how visual programming languages and intelligent data processing can enhance the precision and efficiency of property rights modeling. He is also engaged in rural land reform projects, focusing on integrated systems for real estate registration and cadastre database construction. As land reform and digital governance remain critical to sustainable development, Hu’s research extends to the intersection of technology, urban planning, and policy implementation. His work contributes to improving the accuracy, interoperability, and efficiency of cadastral systems across diverse and complex terrain. Furthermore, he is involved in research that addresses the digital transformation of traditional surveying methods, helping to develop scalable and cost-effective solutions for local and national governments. Hu’s interests support the advancement of a modernized, transparent, and intelligent land governance infrastructure in China.

Research Skills

Yuqing Hu possesses a comprehensive skill set that combines technical, managerial, and analytical proficiencies in the field of land and resource surveying. His core skills include high-precision cadastral surveying, GIS-based spatial data analysis, automated 3D modeling of property rights, and system integration for land registration platforms. He is highly skilled in designing and implementing intelligent investigation and monitoring systems for natural resources in both urban and rural settings. His expertise extends to the use of visual programming languages to automate property data modeling and stratification. Hu has a strong command over database management systems related to land and housing records and is proficient in integrating these systems with real-time monitoring technologies. As a qualified registered surveyor, he brings practical experience to legal and regulatory aspects of land ownership documentation. In addition to technical competencies, he has demonstrated project management skills through his leadership of large-scale government projects, often involving interdisciplinary collaboration. His ability to bridge the gap between technical development and policy application allows him to deliver solutions that are not only technologically advanced but also compliant with legal and administrative frameworks.

Awards and Honors

Yuqing Hu has been the recipient of multiple prestigious awards that recognize his outstanding contributions to geographic information science and cadastral engineering. He ranked second in the Science and Technology Progress Award issued by the China Geographic Information Industry Association for his work on high-precision intelligent monitoring systems. He also earned the Excellent Engineering Gold Award for his role in developing the application system for the Chongqing branch of the National Land Survey Cloud. Additionally, Hu led the “Chongqing Natural Resources Cadastre Survey and Database Construction” project, which won the Silver Award from the Chinese Society of Surveying and Mapping, where he was ranked first. His project on rural real estate registration earned the National Excellent Surveying and Mapping Engineering Award. Moreover, he co-authored a patented invention related to automatic modeling based on property stratification and mapping, solidifying his role as an innovator in land information systems. He has also contributed to internationally indexed research with publications such as one in Advances in Civil Engineering. These honors reflect his sustained impact, leadership, and commitment to technological innovation in land governance and resource monitoring.

Conclusion

In conclusion, Yuqing Hu exemplifies the qualities of an outstanding researcher and innovator in the domains of land surveying, cadastral information systems, and digital governance of natural resources. His rich combination of leadership experience, technical skill, and recognized contributions positions him as a significant figure in the transformation of China’s land and property registration infrastructure. The national-level awards he has received demonstrate his capacity to deliver practical, high-impact solutions with both scientific and societal value. While his international academic visibility could be further expanded, his influence in applied research and engineering is already well-established. Hu’s involvement in strategic projects that digitize and modernize traditional land management practices signifies a long-term commitment to national development priorities and sustainable land use planning. His ability to translate complex technical ideas into scalable, policy-aligned solutions makes him highly suitable for recognition under the Research for Outstanding Contribution Award. His work not only addresses immediate governmental and public sector needs but also sets a benchmark for innovation in spatial information systems and cadastral technology development.

Publications Top Notes

  • Title: Automatic Construction of 3D Building Property Rights Model Based on Visual Programming Language in China

  • Authors: Qin, Guocheng; Hu, Yuqing; Wang, Ling; Liu, Ke; Hou, Yimei

  • Journal: Advances in Civil Engineering

  • Year: 2024

Guocheng Qin | Engineering | Best Researcher Award

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Mr. Guocheng Qin | Engineering | Best Researcher Award

Researcher from Chongqing Institute of Surveying and Monitoring for Planning and Natural Resources, China

Qin Cheng is a dedicated and innovative civil engineering researcher with a strong focus on integrating advanced digital technologies such as Building Information Modeling (BIM), 3D laser scanning, and Unmanned Aerial Vehicle (UAV) systems into modern construction and infrastructure projects. Born in March 1994, he has consistently demonstrated academic excellence, practical engineering insight, and a deep interest in smart city development and sustainable infrastructure. His work spans across both academic and applied settings, with a particular emphasis on intelligent monitoring systems, reverse modeling, and digital design optimization. He has contributed to various high-profile research initiatives and collaborative international projects, particularly during his tenure as a visiting scholar at the University of Louvain. Qin Cheng has also been actively involved in training graduate students, guiding technical design, and promoting intelligent construction practices. His experience working with institutions such as the Chongqing Leuven Institute of Smart City and Sustainable Development and contributions to international exhibitions like the China Intelligent Industry Expo reflect his ability to bridge academic research with real-world applications. With a clear commitment to advancing civil engineering practices through technology and innovation, Qin Cheng continues to emerge as a promising voice in the field of smart construction and structural engineering.

Professional Profile

Education

Qin Cheng’s academic journey in civil engineering began with a Bachelor of Engineering from Zhengzhou Institute of Technology and Business, where he studied from September 2013 to July 2017. Building on a solid undergraduate foundation, he pursued a Master of Engineering in Civil Engineering with a structural specialization at Chongqing Jiaotong University from September 2017 to July 2020. During his master’s studies, Qin demonstrated exceptional academic and research abilities, further enriching his education through international exposure. Between October 2018 and January 2019, he served as a visiting scholar at the University of Louvain in Belgium, engaging in scholarly exchanges focused on construction waste regeneration and sustainable urban development. This international experience broadened his perspective on global engineering practices and enhanced his research on smart city applications. His academic background is marked by strong technical competence in structural systems, intelligent monitoring, and construction digitization. Through both domestic and international institutions, Qin Cheng has built a strong academic profile grounded in research excellence, multidisciplinary learning, and hands-on application of modern civil engineering technologies.

Professional Experience

Qin Cheng has built a diverse portfolio of professional experience that merges academic research, international collaboration, and field application. One of his notable professional engagements was his time as a visiting scholar at the University of Louvain (October 2018 to January 2019), where he contributed to academic exchanges on sustainable urban development and construction waste regeneration. He also engaged with world-renowned engineering firms such as Jan de Nul Group to explore cutting-edge civil engineering practices. Qin served as a researcher at the Chongqing Leuven Institute of Smart City and Sustainable Development, where he played a key role in conducting technical breakthroughs in forward design, reverse modeling, and intelligent monitoring systems. His responsibilities included training graduate students in architectural information technology, guiding bridge reverse modeling projects in Norway, and participating in major events such as the China International Intelligent Industry Expo. His professional activities emphasize the integration of BIM and 3D technologies into infrastructure development. Through his involvement in large-scale projects such as the Taihong Yangtze River Bridge and the FAW-Volkswagen Digital Factory, Qin has effectively applied his academic expertise to real-world engineering challenges. His career path reflects a commitment to technological innovation, cross-border collaboration, and the advancement of intelligent infrastructure systems.

Research Interests

Qin Cheng’s research interests center on the integration of advanced digital technologies in civil engineering, with a particular focus on intelligent construction and infrastructure management. He is deeply engaged in developing and applying Building Information Modeling (BIM), 3D laser scanning, and UAV technologies to improve the design, monitoring, and maintenance of civil structures. His work explores how digital tools can optimize construction processes, enhance precision in modeling, and support virtual simulations for pre-assembly. Qin is also interested in reverse modeling techniques for complex structures, smart monitoring of bridges and buildings, and the use of point cloud data in structural analysis. His international collaborations have further shaped his interest in sustainable urban development, where he examines how smart technologies can be leveraged to build resilient, efficient cities. Through projects focused on highway management systems, digital curtain wall design, and large-scale bridge construction, he aims to create innovative solutions that address contemporary challenges in civil engineering. Qin’s research embodies a forward-thinking approach that blends theoretical modeling with practical application, striving to make infrastructure safer, more efficient, and more intelligent through continuous technological advancement.

Research Skills

Qin Cheng possesses a robust set of research skills that enable him to address complex challenges in civil and structural engineering through technological innovation. His core competencies include advanced proficiency in Building Information Modeling (BIM) and 3D laser scanning, which he has used extensively for deformation monitoring, digital pre-assembly, and reverse modeling of both buildings and bridges. He is skilled in UAV route planning and tilt photography for site inspections and large-scale mapping, showcasing his adaptability in remote sensing applications. His hands-on experience with point cloud data processing enables him to conduct accurate structural analysis and digital model construction. Qin is also proficient in integrating BIM with IoT systems for smart bridge management, combining sensor data with digital modeling for real-time infrastructure monitoring. In academic and collaborative environments, he has guided graduate students in technical training and project design, demonstrating strong mentorship capabilities. He is comfortable working across international platforms and has presented his work at major conferences. Qin’s methodological rigor, combined with his technical agility, allows him to innovate across design, monitoring, and operational aspects of civil engineering projects. His ability to apply research techniques to practical scenarios is a key strength in his professional and academic career.

Awards and Honors

Throughout his academic and early research career, Qin Cheng has received several prestigious awards and honors that reflect his dedication, excellence, and potential in the field of civil engineering. During his undergraduate studies, he was consistently recognized with merit-based scholarships, including the National Encouragement Scholarship and first-class and second-class academic scholarships. His excellence continued into his postgraduate years at Chongqing Jiaotong University, where he was awarded the Beijing CCCC Road Tong Million Scholarship and the first-class postgraduate scholarship. In 2020, he won the second prize in the “My College Life” competition and the third prize in the “Transportation BIM Engineering Innovation Award” from the China Highway Society. These accolades highlight both his academic achievements and his contributions to engineering innovation. His participation in various international academic events and his role in large-scale national infrastructure projects further affirm his growing reputation in the field. The consistent recognition of his work through these awards underscores his capability to combine theoretical knowledge with practical engineering excellence. These honors are a testament to his talent, perseverance, and impact in advancing intelligent construction technologies and modern infrastructure development.

Conclusion

In conclusion, Qin Cheng emerges as a highly motivated and capable young researcher with a strong foundation in civil engineering and a clear commitment to technological innovation in infrastructure development. His integration of BIM, 3D laser scanning, and UAV systems into design and monitoring processes showcases his forward-thinking approach and alignment with the needs of smart and sustainable urban construction. With a solid academic background, international experience, and a growing body of research publications, he brings both technical expertise and practical insight to the field. Although he currently holds a master’s degree, his trajectory suggests significant potential for further academic advancement and research leadership. He has demonstrated the ability to bridge academic research with real-world engineering applications, making valuable contributions to both scholarly and professional communities. While increasing publication in top-tier journals and engaging in patent development could further enhance his profile, Qin Cheng has already laid a strong foundation for a successful research career. He is a suitable and deserving candidate for recognition in early-stage researcher or emerging researcher award categories and has the capacity to evolve into a leading expert in smart construction and digital civil engineering in the years ahead.

Publications Top Notes

  1. Title: Automatic Construction of 3D Building Property Rights Model Based on Visual Programming Language in China
    Authors: Qin, Guocheng; Hu, Yuqing; Wang, Ling; Liu, Ke; Hou, Yimei
    Journal: Advances in Civil Engineering
    Year: 2024

ILLYCH ALVAREZ | Engineering | Best Researcher Award

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Dr. ILLYCH ALVAREZ | Engineering | Best Researcher Award

Investigator from Polytechnic School of the Coast, Ecuador

Illych Ramses Alvarez Alvarez is a distinguished professor and researcher specializing in applied mathematics, chaos theory, and artificial intelligence. With a dynamic career in academia, he has made significant contributions to both theoretical and applied aspects of mathematics, including dynamical systems, numerical analysis, and multiscale modeling. His work spans interdisciplinary domains such as biology, finance, and computational physics. Based in Guayaquil, Ecuador, he holds dual roles in research and education, demonstrating a strong commitment to innovation in mathematics pedagogy. Alvarez is recognized for his development of active learning models and his leadership in enhancing student engagement through modern instructional methodologies. He serves as a professor at the Escuela Superior Politecnica del Litoral (ESPOL) and has also held teaching roles at the Polytechnic University of Valencia in Spain. A regular participant in international conferences and academic forums, Alvarez has built a reputation for scholarly excellence and public academic engagement. He is also active as a reviewer and committee member for renowned scientific journals and conferences. His ability to connect advanced mathematical theory with real-world applications, alongside his contributions to academic leadership, underscores his qualifications as a leading figure in his field and a strong candidate for recognition through research awards.

Professional Profile

Education

Illych Ramses Alvarez holds a robust academic background rooted in mathematical sciences and pedagogy. He earned his Ph.D. in Mathematics from the Polytechnic University of Valencia in Spain, where he specialized in advanced topics such as complex variables, dynamical systems, and fuzzy mathematics. His doctoral research provided the foundation for his ongoing work in chaos theory and applied mathematical modeling. Prior to that, he completed a Master’s degree in Mathematical Sciences with a focus on Numerical Mathematics at the University of Havana, Cuba. This training equipped him with analytical and computational skills essential for numerical simulations and algorithmic problem-solving. In addition, Alvarez pursued a second Master’s degree in Mathematics Teaching at the Escuela Superior Politecnica del Litoral (ESPOL) in Ecuador, reflecting his strong interest in the pedagogical aspects of mathematical instruction. His academic journey began with a Bachelor’s degree in Education Sciences from Universidad Metropolitana del Ecuador, which provided him with a foundational understanding of teaching methodologies and curriculum development. This diverse and comprehensive educational trajectory has allowed Alvarez to bridge rigorous research with effective teaching, making him a valuable contributor to both the academic and educational development spheres in Ecuador and internationally.

Professional Experience

Illych Ramses Alvarez brings over two decades of teaching and research experience, spanning secondary and higher education. His early career included roles in secondary institutions such as Liceo Naval de Guayaquil, where he served as a mathematics teacher and later as Head of the Mathematics Area from 2002 to 2014. He also held the position of Academic Coordinator of the Exact and Experimental Sciences Area at Liceo Los Andes Educational Unit between 2004 and 2017. His leadership and innovative teaching approaches in these roles laid the groundwork for his transition to university-level education. Since 2016, Alvarez has served as a professor and researcher at ESPOL, where he teaches courses in linear algebra, differential equations, and calculus. He has also contributed to ESPOL’s pre-university program and designed the institution’s Active Learning Model for mathematics instruction. Notably, he served as Mathematics Coordinator for the remedial course program from 2020 to 2022. Between 2023 and 2025, he has taken on a visiting teaching role at the Polytechnic University of Valencia in Spain, where he teaches complex variables. Alvarez’s professional career reflects a balanced integration of instructional excellence, research productivity, and leadership in curriculum development.

Research Interests

Illych Ramses Alvarez’s research interests are centered on applied mathematics, chaos theory, artificial intelligence, and numerical methods. His primary focus lies in the study of dynamical systems, particularly set-valued dynamics, transitivity, and mixing phenomena. He investigates how these mathematical properties manifest in various applied contexts, including biological systems, financial models, and physical simulations. A significant portion of his research involves multiscale modeling and the application of finite element methods to solve complex mathematical problems with real-world relevance. In addition, Alvarez has an active interest in fuzzy dynamical systems, exploring uncertainty and recurrence within non-traditional mathematical frameworks. His interdisciplinary approach often merges computational tools with mathematical theory, enabling him to propose new models and predictive systems across domains. More recently, Alvarez has expanded his work into artificial intelligence, particularly in its integration with chaos theory and decision-making processes. His research is characterized by its originality and relevance, bridging theoretical foundations with practical application. Furthermore, his involvement in academic conferences, journal reviewing, and committee memberships reflects a deep engagement with current trends in mathematical research and education. These varied interests place him at the intersection of innovation, theory, and educational reform within the global mathematics research community.

Research Skills

Illych Ramses Alvarez possesses an impressive set of research skills that reflect his expertise in both theoretical and computational mathematics. He is adept in advanced mathematical modeling, particularly in chaos theory, dynamical systems, and fuzzy logic. His proficiency in numerical analysis allows him to solve complex problems using finite element methods, multiscale techniques, and set-valued mappings. Alvarez also has strong skills in developing algorithms for artificial intelligence applications, particularly in the simulation of dynamical behaviors and optimization problems. His analytical acumen is supported by hands-on experience with computational tools and programming languages used in mathematical research and simulation environments. In the educational sphere, Alvarez applies his research capabilities to innovate teaching methods through active learning strategies and blended-learning models. He has designed and implemented instructional modules that integrate research concepts into classroom activities, fostering a research-based learning environment. His editorial experience as a reviewer for high-impact journals and conferences further attests to his critical thinking and evaluative abilities. Alvarez’s research skills are complemented by his capacity to communicate complex ideas clearly and effectively, making him a versatile contributor to both collaborative and independent research initiatives.

Awards and Honors

While Illych Ramses Alvarez’s formal list of awards is still growing, he has received notable recognition in academic and professional circles. He was invited as a keynote speaker at the 1st Symposium on University-Society Engagement at the University of Guayaquil in 2024, where he presented on innovative strategies in mathematics teaching—an acknowledgment of his leadership in educational reform. His selection as a reviewer and scientific committee member for the LACCEI conferences in 2023, 2024, and 2025 reflects the esteem in which his peers hold his research and evaluative expertise. Notably, he has chaired multiple research tracks and contributed as a paper reviewer and technical committee member at various international conferences. In early 2025, he was formally certified by Biosensors and Bioelectronics (Elsevier) for conducting two rigorous scientific reviews, showcasing his credibility within the scientific publishing community. Although he has yet to receive major international research awards, these engagements and recognitions are strong indicators of his growing influence and recognition in the global research landscape. His academic trajectory suggests that further honors are likely as his publication profile and research collaborations continue to expand.

Conclusion

Illych Ramses Alvarez Alvarez represents an exemplary figure in the fields of applied mathematics, chaos theory, and education reform. His diverse academic background, combined with a strong commitment to research and teaching excellence, positions him as a valuable asset to the global academic community. Through years of experience in both secondary and higher education, he has demonstrated a unique ability to translate complex mathematical concepts into accessible learning strategies, fostering deeper understanding and engagement among students. His research portfolio reveals a deep curiosity and innovation, especially in areas like dynamical systems, fuzzy logic, and AI-integrated modeling. Alvarez’s involvement in international conferences, editorial responsibilities, and active curriculum development shows his dedication to advancing both the theory and practice of mathematics. While there is room for growth in terms of high-impact journal publications and larger-scale collaborations, his existing achievements and influence are substantial. His consistent contributions to research, combined with his passion for education, make him a strong candidate for recognition through awards that honor excellence in academic research. With continued focus and support, Alvarez is well-positioned to make lasting contributions to science and education on a global scale.

Publications Top Notes

  1. Title: Advanced Numerical Modeling and Simulation of Hydrogel‐Based Chemo Fluidic Oscillator for Enhanced Insulin Delivery System in Diabetes Treatment: A Comparative and Sensitivity Analysis
    Authors: Illych Alvarez, Esteban Pulley, Patrick Arévalo, Fernando Tenesaca, Ivy Peña Elaje
    Year: 2025

  2. Title: Recurrence in Collective Dynamics: From the Hyperspace to Fuzzy Dynamical Systems
    Authors: Illych Alvarez, Antoni López-Martínez, Alfred Peris
    Year: 2025

  3. Title: Advanced Extensions and Applications of Transitivity and Mixing in Set‐Valued Dynamics With Numerical Simulations and Visual Insights
    Authors: Illych Alvarez, Mehmet Ünver
    Year: 2025

  4. Title: Advanced Extensions and Applications of Transitivity and Mixing in Set-Valued Dynamics with Numerical Simulations and Visual Insights
    Authors: Álvarez, I.R.
    Year: 2024

  5. Title: Heat Transfer Problem Solving Techniques in Materials Engineering: A Numerical Approach and Practical Applications
    Authors: Alvarez, I.A., Barros, E.C., Vargas, A.L., Escobar, I.S.
    Year: 2024

  6. Title: Recurrence in Collective Dynamics: From the Hyperspace to Fuzzy Dynamical Systems (Preprint on arXiv)
    Authors: Álvarez, I., López-Martínez, A., Peris, A.
    Year: 2024

  7. Title: Advanced Numerical Analysis and Simulation of a Chemo-Fluidic Oscillator: Comparative Study of Numerical Methods and Robustness Evaluation
    Authors: Illych Alvarez
    Year: 2024

  8. Title: A New B-Learning Methodology for Teaching Differential Integral Calculus in a School of Engineering
    Authors: Álvarez, I., García, S., Baquerizo, G., Solís, J., Avilés, J.
    Year: 2023

  9. Title: Optimal Exponentially Weighted Moving Average of T² Chart
    Authors: García-Bustos, S., Naranjo, C., Álvarez, I., Ruiz-Barzola, O., Mera-Intriago, E.
    Year: 2023

  10. Title: A New Inverted Class Methodology Applied as a Pilot Program to Students Aspiring to Enter an Ecuadorian University
    Authors: Alvarez, I., Baquerizo, G., Noboa, D., García-Bustos, S., Mera, E.M.
    Year: 2020






	


	

	






	
	

		


Vajeer Baba Shaik | Engineering | Best Researcher Award	 
			

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Mr. Vajeer Baba Shaik | Engineering | Best Researcher Award


Research Scholar from Dr. B R Ambedkar National Institute of Technology, India




















Shaik Vajeer Baba is a promising researcher and academic currently pursuing his PhD in Mechanical Engineering with a focus on thermal polygeneration systems at Dr. B.R. Ambedkar National Institute of Technology, Jalandhar. He has a solid academic background, having completed his M.Tech in Thermal Engineering with a CGPA of 8.49 and a Bachelor’s degree in Mechanical Engineering. Baba is also active in various professional and academic roles, including as an Assistant Professor at Lingayas Vidyapeeth, where he contributes to teaching and research. His research is centered around energy-efficient systems, desalination technologies, and heat exchanger design. With a strong publication record and patents in energy and manufacturing, he shows great promise in his field. Baba’s work blends theoretical research with practical industrial applications, providing valuable insights into sustainability and energy optimization.


Professional Profile



Education


Shaik Vajeer Baba is currently pursuing a PhD in Mechanical Engineering at Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, with a focus on thermal polygeneration systems. His academic journey began with a Bachelor’s degree in Mechanical Engineering from Dhanekula Institute of Engineering and Technology, where he graduated with a 73.04% score. Baba later completed his M.Tech in Thermal Engineering from Koneru Lakshmaiah Education Foundation (KL University) with an impressive CGPA of 8.49. His academic achievements reflect a strong foundation in mechanical and thermal engineering, and he continues to build on this expertise in his ongoing PhD research, which explores energy-efficient technologies in the field of thermal engineering.


Professional Experience


Shaik Vajeer Baba has accumulated valuable experience in both teaching and industry over the years. He currently serves as an Assistant Professor at Lingayas Vidyapeeth, where he has been contributing to the academic environment since January 2025. Prior to this, Baba held teaching positions at V.K.R.V.N.B & A.G.K. College of Engineering, Gudivada, and Anand College of Engineering and Management, Kapurthala. In addition to his teaching roles, he worked as a Junior Research Fellow (JRF) at Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, where he worked on projects related to thermal engineering and energy systems. Baba’s industrial experience includes working as a machine operator at Better Castings, Vijayawada, providing him with practical exposure to manufacturing processes.


Research Interest


Shaik Vajeer Baba’s research interests are primarily focused on thermal engineering, specifically in the areas of polygeneration, heat exchanger design, HDH desalination, and system optimization. His PhD research is centered on thermal polygeneration systems, which combine multiple energy production processes for enhanced efficiency. Baba has explored heat exchanger design in various energy systems, aiming to improve heat transfer efficiency. His work also includes the development of desalination technologies, particularly focused on the HDH process, and integrating energy-efficient systems for sustainable energy solutions. These research areas have both academic and industrial relevance, aiming to tackle current energy challenges while promoting sustainability.


Research Skills


Shaik Vajeer Baba possesses a strong set of research skills, including expertise in heat exchanger design, energy system optimization, and the development of sustainable energy technologies. He is proficient in simulation and modeling software such as MATLAB and ANSYS, which he uses to analyze and optimize thermal systems. Baba’s ability to conduct both experimental and theoretical research allows him to generate valuable insights into energy-efficient technologies. His knowledge in product development is reflected in his work on thermal systems, HDH desalination, and heat pump systems. Moreover, his research has resulted in several published papers and patents, demonstrating his ability to contribute to scientific advancements in his field.


Awards and Honors


Shaik Vajeer Baba has received recognition for his innovative contributions to the field of thermal engineering. His work has resulted in several publications in reputed journals and conferences, including SCI and ESCI indexed papers. Baba has also applied for patents in areas like artificial intelligence in manufacturing and thermoelectric generators, showcasing his innovative thinking. Additionally, he has attended numerous Faculty Development Programs (FDPs) and workshops, which reflect his commitment to staying updated with the latest advancements in his field. Baba’s active involvement in academic activities, such as being the IQAC coordinator and R&D member at his institution, highlights his dedication to both research and educational development.


Conclusion


Shaik Vajeer Baba is an emerging scholar in the field of thermal engineering with a promising research trajectory. His academic background, strong publication record, and patents in the areas of energy systems and sustainable technologies demonstrate his dedication and potential as a researcher. Baba’s focus on energy efficiency and optimization aligns well with current global challenges in sustainable energy solutions. His work, which bridges both theoretical research and industrial applications, positions him as a valuable contributor to the field. With continued growth in collaborations, research output, and global recognition, Baba is well on his way to becoming a leading researcher in his area of expertise.












Publications Top Notes


    

  1. Title: Performance analysis of heat pump polygeneration system
    Authors: Shaik, Vajeer Baba; Srinivas, T.; Kukreja, Rajeev
    Journal: Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering
    Year: 2024
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Tursun Mamat | Engineering | Best Researcher Award
			

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Mr. Tursun Mamat | Engineering | Best Researcher Award


Professor from Xinjiang Agriculture University, China




















Dr. Tuerxun Maimaiti is an Associate Professor at Xinjiang Agricultural University in the College of Transportation & Logistics Engineering, specializing in Traffic Engineering and Intelligent Transportation Systems. He serves as the Director of the College Laboratory and the Head of the Engineering Research Center for Intelligent Transportation. His research interests focus on driving behavior, traffic safety, vehicle-road coordination, and the environmental impact of traffic. With a strong academic background, including a Ph.D. in Transport Engineering from Nanjing Agricultural University and experience as a visiting Ph.D. student at Dalhousie University, he combines technical expertise with practical solutions for modern traffic challenges. Dr. Maimaiti is a prolific researcher with numerous published works in the field and leads multiple innovative research projects aimed at improving traffic systems, safety, and environmental sustainability.


Professional Profile



Education


Dr. Tuerxun Maimaiti holds a Ph.D. in Transport Engineering from Nanjing Agricultural University, awarded in 2017. His educational background also includes a Master’s degree in Computer Science from Xinjiang Agricultural University in 2008 and a Bachelor’s degree in Computer Application from Wuhan University in 2000. Additionally, Dr. Maimaiti pursued a visiting Ph.D. in Computer Science at Dalhousie University in 2013, where he expanded his expertise in computational techniques, particularly in the context of transportation systems. His education has equipped him with a strong foundation in both engineering and computer science, allowing him to bridge the gap between traffic engineering and technology.


Professional Experience


Dr. Maimaiti’s professional career spans over two decades, with significant experience in both academic and research settings. He began his academic career as a Teaching Assistant at Xinjiang Agricultural University from 2000 to 2005 before becoming an Associate Professor at the same institution in 2015. He also serves as the Director of the College Laboratory and Head of the Engineering Research Center for Intelligent Transportation. His leadership in these roles has contributed to the development of cutting-edge research and educational programs in the field of transportation engineering. Dr. Maimaiti has also managed several large-scale research projects, demonstrating his ability to combine academic knowledge with practical applications in the transportation sector.


Research Interests


Dr. Maimaiti’s research interests lie in several critical areas within traffic engineering and intelligent transportation systems. His primary focus includes studying driving behavior, road traffic safety, and the environmental impacts of traffic, particularly carbon emissions from urban roads. He has a strong interest in vehicle-road collaboration and its impact on traffic safety and efficiency. Additionally, Dr. Maimaiti explores the potential of digital twin technology in transportation systems and traffic simulations to improve infrastructure management and safety measures. His work aims to integrate ecological driving practices and intelligent transportation technologies to create sustainable, safe, and efficient transportation systems.


Research Skills


Dr. Maimaiti possesses a broad range of research skills that include expertise in traffic simulation, data analysis, and the application of machine learning techniques in transportation systems. He is proficient in using advanced algorithms, including YOLO v5s, for detecting pavement cracks and deep learning models for emission prediction. His research skills also extend to the development of intelligent systems for road maintenance, traffic data mining, and the optimization of toll collection systems. His ability to combine theoretical knowledge with practical applications has enabled him to lead several successful research projects that address both current and future challenges in transportation engineering.


Awards and Honors


While specific awards and honors were not listed in the provided details, Dr. Maimaiti’s impressive academic and professional record suggests that he has made significant contributions to the field of transportation engineering. His leadership in multiple high-profile research projects and the successful application of advanced technologies in real-world transportation systems reflect the recognition he has received from both academic and industry communities. His continued work in intelligent transportation systems and sustainable traffic solutions is likely to attract further recognition and accolades in the near future.


Conclusion


Dr. Tuerxun Maimaiti is an accomplished researcher and academic in the field of Traffic Engineering, with a strong focus on intelligent transportation systems and sustainable traffic management. His research on driving behavior, traffic safety, and vehicle-road collaboration has the potential to significantly impact transportation systems worldwide. Dr. Maimaiti’s expertise in utilizing advanced technologies like deep learning and digital twins enhances the practical application of his research. His extensive professional experience and leadership in large-scale projects further demonstrate his capabilities. While his impact is already notable, expanding his research into broader interdisciplinary areas and increasing the visibility of his work could further elevate his contributions. Overall, Dr. Maimaiti’s work in traffic engineering and intelligent transportation systems makes him a strong candidate for prestigious research awards.












Publications Top Notes


    

  1. Title: Improved Asphalt Pavement Crack Detection Model Based on Shuffle Attention and Feature Fusion
    Authors: Mamat, Tursun; Dolkun, Abdukeram; He, Runchang; Nigat, Zulipapar; Du, Hanchen
    Journal: Journal of Advanced Transportation
    Year: 2025
    2. 



























	


	

	






	
	

		


Weiwei Bai | Engineering | Best Researcher Award
			

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Assoc. Prof. Dr. Weiwei Bai | Engineering | Best Researcher Award


Associate Professor from Dalian Maritime University, China


Dr. Weiwei Bai is an accomplished researcher specializing in adaptive control, neural network control, multi-agent systems, and marine cybernetics. He earned his Ph.D. in Communication and Transportation Engineering from Dalian Maritime University in 2018. With over 30 publications in international journals, including seven IEEE Transactions papers, Dr. Bai has made significant contributions to the field. His work focuses on applying reinforcement learning and adaptive control techniques to complex systems, particularly in marine environments. Dr. Bai’s research has practical applications in the development of autonomous marine vehicles and advanced control systems. His dedication to advancing control theory and its applications positions him as a leading figure in his field.


Professional Profile​



Education


Dr. Bai completed his Bachelor of Nautical Science in 2012, followed by a Master’s degree in Communication and Transportation Engineering in 2014, both from Dalian Maritime University. He continued at the same institution to earn his Ph.D. in Communication and Transportation Engineering in 2018. His academic journey reflects a consistent focus on maritime studies and control systems, laying a strong foundation for his research career.​


Professional Experience


Dr. Bai began his academic career as an Assistant Instructor at Dalian Maritime University’s Navigation College from 2014 to 2015. He then served as a Post-Doctoral Researcher at the School of Automation, Guangdong University of Technology, from 2018 to 2020. Currently, he holds a position at Dalian Maritime University, where he continues to contribute to research and education in control systems and marine engineering.​


Research Interests


Dr. Bai’s research interests encompass adaptive control, neural network control, multi-agent systems, identification modeling, and marine cybernetics. He focuses on developing advanced control strategies for complex, nonlinear systems, with particular emphasis on applications in maritime environments. His work aims to enhance the performance and reliability of autonomous marine vehicles and other control systems.​


Research Skills


Dr. Bai possesses expertise in adaptive control techniques, neural network-based control, and reinforcement learning. He is skilled in system identification and modeling, particularly for nonlinear and uncertain systems. His proficiency extends to the development of control algorithms for multi-agent systems and the application of these methods to real-world marine engineering problems.​


Awards and Honors


Dr. Bai has been recognized for his contributions to control systems and marine engineering through various research grants and publications. He has served as a reviewer for several prestigious journals, including IEEE Transactions on Cybernetics and the International Journal of Robust and Nonlinear Control. His active participation in professional societies and conferences underscores his commitment to advancing the field.​


Conclusion


Dr. Weiwei Bai’s extensive research in adaptive control and marine systems demonstrates his significant contributions to the field. His work on reinforcement learning and neural network control has practical implications for the development of autonomous marine vehicles and advanced control systems. Dr. Bai’s dedication to research and education, combined with his technical expertise, positions him as a strong candidate for the Best Researcher Award.​


Publications Top Notes


    

  1. 

    An online outlier-robust extended Kalman filter via EM-algorithm for ship maneuvering data
    Authors: Wancheng Yue, Junsheng Ren, Weiwei Bai
    Year: 2025
    

    2. 

  2. 

    Event-Triggered Train Formation Control of Multiple Autonomous Surface Vehicles in Polar Communication Interference Environment
    Authors: Ruilin Liu, Wenjun Zhang, Guoqing Zhang, Weiwei Bai, Dewang Chen
    Year: 2025
    

    3. 

  3. 

    Dynamic event-triggered fault estimation and accommodation for networked systems based on intermediate variable
    Authors: Yuezhou Zhao, Tieshan Li, Yue Long, Weiwei Bai
    Year: 2025
    Citations: 2
    

    4. 

  4. 

    Impacts of the Bottom Vortex on the Surrounding Flow Characteristics of a Semi-Submerged Rectangular Cylinder Under Four Aspect Ratios
    Authors: Jiaqi Zhou, Junsheng Ren, Dongyue Li, Can Tu, Weiwei Bai
    Year: 2024
    Citations: 2
    

    5. 



 







	


	

	






	
	

		


Masoud Alilou | Engineering | Best Researcher Award
			

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Assist. Prof. Dr. Masoud Alilou | Engineering | Best Researcher Award


Electrical Engineering from Urmia University of Technology, Iran


Dr. Masoud Alilou is a distinguished academic and researcher whose expertise lies at the intersection of biomedical engineering, image processing, and machine learning. Renowned for his pioneering contributions to medical image analysis, Dr. Alilou has played a pivotal role in advancing computational tools for disease detection and diagnosis. His research integrates advanced algorithm development with practical clinical applications, especially in oncology and pulmonary imaging. With a strong publication record in high-impact journals and numerous international collaborations, Dr. Alilou is recognized for his innovative methodologies and interdisciplinary approach. He has also been instrumental in mentoring graduate students and contributing to curriculum development in biomedical engineering and computer science programs. His commitment to translational research has led to the development of automated tools aimed at improving diagnostic accuracy and patient care. Over the years, Dr. Alilou has gained a reputation for excellence in research, teaching, and academic leadership. He is a frequent reviewer for reputed journals and conferences, and his work has been widely cited. Through his dedication to technological innovation and scientific rigor, Dr. Alilou continues to make significant contributions to medical imaging and artificial intelligence in healthcare, solidifying his status as a leader in the academic and scientific communities.


Professional Profile



Education


Dr. Masoud Alilou’s academic journey reflects his deep-rooted commitment to interdisciplinary research and education. He earned his Bachelor’s degree in Computer Engineering, laying a strong foundation in algorithm design, programming, and systems analysis. Driven by a desire to apply computational methods to real-world problems, he pursued a Master’s degree in Biomedical Engineering. During this period, he focused on medical image analysis and machine learning, bridging the gap between engineering and clinical medicine. His master’s research emphasized the development of image processing tools for diagnosing chronic lung diseases, which sparked his long-term interest in healthcare technologies. He later completed his Ph.D. in Biomedical Engineering at Case Western Reserve University, a globally respected institution in the field. His doctoral research concentrated on automated quantitative analysis of medical images using advanced computational models and machine learning techniques. During his Ph.D., Dr. Alilou collaborated closely with radiologists and oncologists, reinforcing the clinical relevance of his work. His interdisciplinary training uniquely positioned him to develop algorithms that are both technically robust and clinically meaningful. Through rigorous coursework, hands-on research, and cross-disciplinary mentorship, Dr. Alilou has built an educational background that combines computational science, engineering, and medicine—an essential blend for cutting-edge biomedical research.


Professional Experience


Dr. Masoud Alilou has amassed an impressive portfolio of professional experience that spans academic research, interdisciplinary collaboration, and technological innovation. Following his doctoral studies, he joined the Quantitative Imaging Laboratory at Case Western Reserve University as a research scientist. In this role, he led and contributed to multiple NIH-funded projects aimed at developing automated tools for lung cancer screening and diagnosis using low-dose CT scans. His work involved close collaboration with clinicians, radiologists, and computer scientists, fostering a rich interdisciplinary environment. Dr. Alilou has also served as a senior researcher and developer on projects integrating artificial intelligence into clinical workflows, focusing on machine learning algorithms for lung nodule detection, segmentation, and classification. His algorithms have been implemented in software solutions used by research hospitals and diagnostic centers, significantly enhancing diagnostic precision and workflow efficiency. In addition to research, Dr. Alilou has mentored graduate students, supervised thesis projects, and contributed to the development of training modules in biomedical imaging and AI. His professional experience also includes serving as a reviewer for numerous peer-reviewed journals, including IEEE Transactions on Medical Imaging and Medical Physics. Through these roles, Dr. Alilou has built a strong reputation as both a scientific innovator and a collaborative leader in the medical imaging community.


Research Interests


Dr. Masoud Alilou’s research interests lie at the convergence of biomedical engineering, medical image analysis, and artificial intelligence. Central to his work is the development of computational techniques for the automated analysis of medical images, particularly in the early detection and characterization of diseases such as lung cancer and chronic obstructive pulmonary disease (COPD). He is deeply interested in low-dose CT imaging and its applications in non-invasive diagnostics, seeking to optimize the accuracy and efficiency of radiological assessments through advanced algorithms. A significant focus of Dr. Alilou’s research is on radiomics—extracting high-dimensional features from medical images to identify patterns correlated with disease outcomes. He is also engaged in developing deep learning models for image classification, segmentation, and prediction of treatment response. His work explores how quantitative image features can be integrated with clinical data to inform precision medicine. Moreover, Dr. Alilou is enthusiastic about translational research, ensuring that the algorithms and tools he develops are applicable in clinical settings. His interdisciplinary projects often involve partnerships with radiologists, oncologists, and biostatisticians. Through his commitment to impactful research, Dr. Alilou continues to push the boundaries of medical imaging, aiming to enhance patient outcomes through innovation and data-driven healthcare solutions.


Research Skills


Dr. Masoud Alilou possesses an exceptional set of research skills that span computational modeling, machine learning, and biomedical image analysis. He is highly proficient in developing and implementing complex algorithms for image processing tasks, including segmentation, registration, and feature extraction. His expertise in computer vision allows him to work with large-scale imaging datasets, transforming raw medical data into meaningful clinical insights. He has extensive experience with deep learning frameworks such as TensorFlow, PyTorch, and Keras, which he uses to design and train neural networks for various diagnostic tasks. Additionally, Dr. Alilou is adept in programming languages such as Python, MATLAB, and C++, enabling him to prototype and optimize algorithms efficiently. His skills in radiomics and statistical analysis allow for the extraction and evaluation of high-dimensional imaging biomarkers, supporting the development of predictive and prognostic models. Dr. Alilou also demonstrates strong skills in interdisciplinary collaboration, integrating domain knowledge from radiology, oncology, and bioinformatics into his research workflows. His rigorous approach to data validation, model performance evaluation, and reproducibility ensures the reliability of his findings. Whether through designing novel AI models or translating computational tools into clinical applications, Dr. Alilou’s technical and collaborative skills stand at the core of his impactful research contributions.


Awards and Honors


Dr. Masoud Alilou has received several prestigious awards and honors in recognition of his outstanding research contributions and academic achievements. His innovative work in the field of medical image analysis has earned him accolades from both academic institutions and professional organizations. As a graduate student, he was honored with the Research Excellence Award at Case Western Reserve University, acknowledging his impactful contributions to biomedical engineering and medical imaging. His research has also been recognized at international conferences, where he has received best paper and poster awards for his work on automated lung cancer detection and radiomics-based diagnostic tools. Dr. Alilou’s contributions to artificial intelligence in healthcare have attracted attention from funding bodies such as the National Institutes of Health (NIH), resulting in several grant-supported projects. In addition, he has been invited to present his work at renowned symposiums and workshops, affirming his status as a thought leader in his field. Dr. Alilou also serves as a regular reviewer for high-impact journals, a testament to the scientific community’s trust in his expertise. These honors reflect not only his technical proficiency but also his dedication to advancing medical science through innovation, collaboration, and academic excellence.


Conclusion


In summary, Dr. Masoud Alilou stands out as a pioneering figure in the field of biomedical engineering and medical image analysis. With a strong educational foundation and diverse professional experience, he has successfully bridged the worlds of computational science and clinical medicine. His research—centered on the development of AI-driven tools for disease diagnosis and prediction—has not only advanced academic knowledge but also brought tangible benefits to healthcare practice. Dr. Alilou’s skills in image processing, machine learning, and interdisciplinary collaboration have positioned him as a key contributor to the evolving landscape of precision medicine. His numerous awards and academic recognitions reflect a career marked by innovation, excellence, and societal impact. Beyond research, Dr. Alilou’s contributions as a mentor, educator, and collaborator have enriched the academic and scientific communities. Looking forward, he continues to explore new frontiers in medical AI, with a vision of improving diagnostic accuracy, patient outcomes, and health system efficiency. As a scientist dedicated to turning complex data into actionable healthcare solutions, Dr. Alilou exemplifies the potential of integrating technology and medicine for the betterment of global health.


Publications Top Notes


    

  1. 

    Title: Home energy management in a residential smart micro grid under stochastic penetration of solar panels and electric vehicles
    Authors: M. Alilou, B. Tousi, H. Shayeghi
    Year: 2020
    Citations: 93
    

    2. 

  2. 

    Title: Fractional-order control techniques for renewable energy and energy-storage-integrated power systems: A review
    Authors: M. Alilou, H. Azami, A. Oshnoei, B. Mohammadi-Ivatloo, R. Teodorescu
    Year: 2023
    Citations: 33
    

    3. 

  3. 

    Title: Application of multi objective HFAPSO algorithm for simultaneous placement of DG, capacitor and protective device in radial distribution network
    Authors: H. Shayeghi, M. Alilou
    Year: 2015
    Citations: 25
    

    4. 

  4. 

    Title: Multi-objective optimization of demand side management and multi DG in the distribution system with demand response
    Authors: M. Alilou, D. Nazarpour, H. Shayeghi
    Year: 2018
    Citations: 24
    

    5. 

  5. 

    Title: Simultaneous placement of renewable DGs and protective devices for improving the loss, reliability and economic indices of distribution system with nonlinear load model
    Authors: M. Alilou, V. Talavat, H. Shayeghi
    Year: 2020
    Citations: 20
    

    6. 

  6. 

    Title: Multi-objective energy management of smart homes considering uncertainty in wind power forecasting
    Authors: M. Alilou, B. Tousi, H. Shayeghi
    Year: 2021
    Citations: 19
    

    7. 

  7. 

    Title: Multi-Objective demand side management to improve economic and‎ environmental issues of a smart microgrid‎
    Authors: H. Shayeghi, M. Alilou
    Year: 2021
    Citations: 17
    

    8. 

  8. 

    Title: Distributed generation and microgrids
    Authors: H. Shayeghi, M. Alilou
    Year: 2021
    Citations: 16
    

    9. 

  9. 

    Title: Multi‐objective unit and load commitment in smart homes considering uncertainties
    Authors: M. Alilou, B. Tousi, H. Shayeghi
    Year: 2020
    Citations: 12
    

    10. 

  10. 

    Title: Day-ahead scheduling of electric vehicles and electrical storage systems in smart homes using a novel decision vector and AHP method
    Authors: M. Alilou, G.B. Gharehpetian, R. Ahmadiahangar, A. Rosin, et al.
    Year: 2022
    Citations: 11
    

    11. 

  11. 

    Title: Optimal placement and sizing of TCSC for improving the voltage and economic indices of system with stochastic load model
    Authors: S. Ghaedi, B. Tousi, M. Abbasi, M. Alilou
    Year: 2020
    Citations: 10
    

    12. 




	


	

	






	
	

		


Dan Yang | Chemical Engineering | Best Researcher Award
			

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Assoc. Prof. Dr. Dan Yang | Chemical Engineering | Best Researcher Award


School of Chemistry and Molecular Engineering, Nanjing Tech University, China


Dan Yang is an accomplished associate professor at Nanjing Tech University, specializing in chemistry and molecular engineering. With a strong academic foundation and extensive research experience, she focuses on the synthesis of metal nanoclusters and their applications in photoelectrocatalysis and electrocatalysis. Her research aims to develop innovative solutions for CO2 reduction and biomass conversion, contributing to sustainable chemical processes. Throughout her career, she has made significant contributions to the field, authoring multiple high-impact publications in renowned scientific journals. Dan Yang has successfully secured competitive research grants, demonstrating her expertise in securing funding for cutting-edge projects. With her deep-rooted knowledge in physical chemistry and material science, she continues to make impactful strides in catalysis research, earning recognition and respect in her field.


Professional Profile


ORCID Profile


Education


Dan Yang has an extensive academic background in chemistry and material science. She earned her doctoral degree in physical chemistry from Nanjing University (2017–2020) under the supervision of Professors Weiping Ding and Yan Zhu. During her doctoral studies, she focused on the catalytic conversion of C1 molecules using metal clusters. Prior to this, she obtained a master’s degree in material science from Sun Yat-sen University (2012–2014), where she worked under Professor Yuezhong Meng, specializing in the development of advanced materials. Her educational journey began at Northwest Normal University, where she completed her bachelor’s degree in chemistry (2008–2012), building a strong foundation in chemical principles and laboratory techniques. This diverse and robust educational background has equipped Dan Yang with the expertise to conduct innovative research in electrocatalysis and sustainable chemical processes.


Professional Experience


Dan Yang’s professional career reflects her dedication to advancing chemical research. She is currently an associate professor at Nanjing Tech University (2023–present), where she leads research on metal nanocluster synthesis and their applications in photoelectrocatalysis and electrocatalysis of C1 molecules and biomass conversion. Prior to her current role, she served as a postdoctoral researcher at the same university (2021–2022), where she worked on electrocatalytic CO2 reduction reactions (CO2RR) and the conversion of biomass derivatives into valuable chemical products. From 2014 to 2016, she was an assistant research fellow at the Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences. There, she contributed to the development of fine chemicals, including phase-change materials, epoxide plasticizers, and bio-based polyols. Her diverse professional experience underscores her expertise in catalysis, sustainable chemical synthesis, and material science.


Research Interests


Dan Yang’s research interests revolve around catalysis and sustainable chemistry. She specializes in the synthesis of metal nanoclusters and their catalytic applications in photoelectrocatalysis and electrocatalysis. Her current focus includes CO2 reduction reactions (CO2RR) to produce carbon monoxide (CO) and formic acid (HCOOH), offering potential solutions for carbon capture and utilization. She also explores the electrocatalytic transformation of biomass-derived molecules, such as glycerol and glucose, into valuable carboxylic acid products. Additionally, her work investigates the evolution of metal-ligand interfaces in nanoclusters and their impact on catalytic performance. Through her research, Dan Yang aims to develop efficient and sustainable catalytic systems that address environmental challenges and promote green chemical processes.


Research Skills


Dan Yang possesses a diverse set of research skills in the fields of catalysis and material science. She is highly proficient in the synthesis and characterization of metal nanoclusters, utilizing techniques such as transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and nuclear magnetic resonance (NMR) to analyze cluster structures. Her expertise extends to electrochemical methods, including cyclic voltammetry and chronoamperometry, for evaluating catalytic performance. Additionally, she has experience in biomass conversion processes, utilizing electrocatalysis and photoelectrocatalysis techniques. Her analytical skills include advanced data interpretation and the use of computational tools for modeling catalytic reactions. Dan Yang’s technical proficiency enables her to design and optimize catalytic systems for efficient and selective chemical transformations.


Awards and Honors


Dan Yang has received several prestigious awards and research grants in recognition of her contributions to catalysis research. She was awarded the Young Scientists Fund of the National Natural Science Foundation of China (NSFC) for her project on the evolution of metal-ligand interfaces in gold clusters for CO2 reduction (2025–2027). She also leads a sub-project of the NSFC International Cooperation and Exchanges Program, focusing on new catalysts and materials for CO2 capture and conversion (2024–2026). Additionally, she secured funding from the Jiangsu Natural Science Foundation of China for her work on glycerol carbonate synthesis through electrochemical CO2 conversion (2023–2026). Dan Yang previously received support from the China Postdoctoral Science Foundation for her research on electrolyte-regulated CO2RR using gold clusters (2022–2023). These accolades highlight her innovative research and scientific impact.


Conclusion


Dan Yang is a distinguished researcher and associate professor with a profound expertise in catalysis, material science, and sustainable chemical processes. Her academic journey, spanning from physical chemistry to material science, has equipped her with the skills and knowledge to tackle complex challenges in CO2 reduction and biomass conversion. With a prolific publication record and multiple research grants, she continues to make significant contributions to the field. Her commitment to advancing sustainable catalytic processes reflects her dedication to addressing pressing environmental challenges. Through her innovative research, Dan Yang remains at the forefront of scientific discovery, driving advancements in electrocatalysis and green chemistry.


Publications Top Notes


    

  1. Metal-ligand interfaces for well-defined gold nanoclusters
    Authors: Yang, Dan; Wu, Yating; Yuan, Zhaotong; Zhou, Chunmei; Dai, Yihu; Wan, Xiaoyue; Zhu, Yan; Yang, Yanhui
    Journal: Science China Chemistry
    2. 

  2. 

    Atomically Precise Water-Soluble Gold Nanoclusters: Synthesis and Biomedical Application
    Authors: Yan, Qian; Yuan, Zhaotong; Wu, Yating; Zhou, Chunmei; Dai, Yihu; Wan, Xiaoyue; Yang, Dan; Liu, Xu; Xue, Nianhua; Zhu, Yan
    Journal: Precision Chemistry
    

    3. 

  3. 

    Direct dehydrogenation of propane over Co@silicalite-1 zeolite: Steaming-induced restructuring of Co2+ active sites
    Authors: Long, Jiangping; Tian, Suyang; Wei, Sheng; Lin, Hongqiao; Shi, Guiwen; Zong, Xupeng; Yang, Yanhui; Yang, Dan; Tang, Yu; Dai, Yihu
    Journal: Applied Surface Science
    

    4. 

  4. 

    Metal-carbonate interface promoted activity of Ag/MgCO3 catalyst for aqueous-phase formaldehyde reforming into hydrogen
    Authors: Wang, Qiaojuan; Wang, Jianyue; Rui, Wenjuan; Yang, Dan; Wan, Xiaoyue; Zhou, Chunmei; Li, Renhong; Liu, Wen; Dai, Yihu; Yang, Yanhui
    Journal: Fuel
    

    5. 

  5. 

    Nonoxidative propane dehydrogenation by isolated Co2+ in BEA zeolite: Dealumination-determined key steps of propane C-H activation and propylene desorption
    Authors: Wei, Sheng; Dai, Hua; Long, Jiangping; Lin, Hongqiao; Gu, Junkun; Zong, Xupeng; Yang, Dan; Tang, Yu; Yang, Yanhui; Dai, Yihu
    Journal: Chemical Engineering Journal
    

    6. 

  6. 

    Investigation into the coking-related key reaction steps in dry reforming of methane over NiMgOx catalyst
    Authors: Wang, Jianyue; Wang, Jiawei; Wei, Sheng; Zhang, Yiwen; Tian, Fuhou; Yang, Dan; Kustov, Leonid M.; Yang, Yanhui; Dai, Yihu
    Journal: Molecular Catalysis
    

    7. 

  7. 

    Ball-milling-induced phase transition of ZrO2 promotes selective oxidation of glycerol to dihydroxyacetone over supported PtBi bimetal catalyst
    Authors: Luo, Pan; Wang, Jianyue; Rui, Wenjuan; Xu, Ruilin; Kuai, Zhiyuan; Yang, Dan; Wan, Xiaoyue; Zhou, Chunmei; Yang, Yanhui; Dai, Yihu
    Journal: Chemical Engineering Journal
    

    8. 

  8. 

    Catalytic Conversion of C1 Molecules on Atomically Precise Metal Nanoclusters (vol 4, pg 66, 2022)
    Authors: Not listed
    Journal: CCS Chemistry
    

    9. 

  9. 

    Non-oxidative propane dehydrogenation over Co/Ti-ZSM-5 catalysts: Ti species-tuned Co state and surface acidity
    Authors: Wu, Yueqi; Long, Jiangping; Wei, Sheng; Gao, Yating; Yang, Dan; Dai, Yihu; Yang, Yanhui
    Journal: Microporous and Mesoporous Materials
    

    10. 

  10. 

    On the effect of zeolite acid property and reaction pathway in Pd-catalyzed hydrogenation of furfural to cyclopentanone
    Authors: Gao, Xing; Ding, Yingying; Peng, Lilin; Yang, Dan; Wan, Xiaoyue; Zhou, Chunmei; Liu, Wen; Dai, Yihu; Yang, Yanhui
    Journal: Fuel
    

    11. 

  11. 

    Research Progress in Electrocatalytic CO2 Reduction Reaction over Gold Clusters
    Authors: Yang, Dan; Liu, Xu; Dai, Yihu; Zhu, Yan; Yang, Yanhui
    Journal: Chemical Journal of Chinese Universities
    

    12. 

  12. 

    Electrocatalytic CO2 Reduction over Atomically Precise Metal Nanoclusters Protected by Organic Ligands
    Authors: Yang, Dan; Wang, Jiawei; Wang, Qiaojuan; Yuan, Zhaotong; Dai, Yihu; Zhou, Chunmei; Wan, Xiaoyue; Zhang, Qichun; Yang, Yanhui
    Journal: ACS Nano
    

    13. 

  13. 

    Chemoselective Oxidation of Glycerol over Platinum‐Based Catalysts: Toward the Role of Oxide Promoter
    Authors: Not listed
    Journal: ChemCatChem
    

    14. 

  14. 

    Catalytic Conversion of C1 Molecules on Atomically Precise Metal Nanoclusters
    Authors: Not listed
    Journal: CCS Chemistry
    

    15. 

  15. 

    Distinct chemical fixation of CO2 enabled by exotic gold nanoclusters
    Authors: Yang, Dan; Song, Yu; Yang, Fang; Sun, Yongnan; Li, Shuohao; Liu, Xu; Zhu, Yan; Yang, Yanhui
    Journal: The Journal of Chemical Physics
    

    16. 

  16. 

    A survey of recent progress on novel catalytic materials with precise crystalline structures for oxidation/hydrogenation of key biomass platform chemicals
    Authors: Not listed
    Journal: EcoMat
    

    17. 

  17. 

    Selective CO2 conversion tuned by periodicities in Au8n+4(TBBT)4n+8 nanoclusters
    Authors: Not listed
    Journal: Nano Research
    

    18. 

  18. 

    Evolution of catalytic activity driven by structural fusion of icosahedral gold cluster cores
    Authors: Not listed
    Journal: Chinese Journal of Catalysis
    

    19. 

  19. 

    Ligand-protected Au4Ru2 and Au5Ru2 nanoclusters: distinct structures and implications for site-cooperation catalysis
    Authors: Not listed
    Journal: Chemical Communications
    

    20. 

  20. 

    Structural Relaxation Enabled by Internal Vacancy Available in a 24-Atom Gold Cluster Reinforces Catalytic Reactivity
    Authors: Not listed
    Journal: Journal of the American Chemical Society
    

    21. 

  21. 

    Controllable Conversion of CO2 on Non‐Metallic Gold Clusters
    Authors: Not listed
    Journal: Angewandte Chemie International Edition
    

    22. 

  22. 

    Sequence isomerism-dependent self-assembly of glycopeptide mimetics with switchable antibiofilm properties
    Authors: Chen, Limin; Feng, Jie; Yang, Dan; Tian, Falin; Ye, Xiaomin; Qian, Qiuping; Wei, Shuai; Zhou, Yunlong
    Journal: Chemical Science
    

    23. 

  23. 

    Switchable modulation of bacterial growth and biofilm formation based on supramolecular tripeptide amphiphiles
    Authors: Chen, Limin; Yang, Dan; Feng, Jie; Zhang, Min; Qian, Qiuping; Zhou, Yunlong
    Journal: Journal of Materials Chemistry B
    

    24. 

  24. 

    The Evolution in Catalytic Activity Driven by Periodic Transformation in the Inner Sites of Gold Clusters
    Authors: Sun, Yongnan; Wang, Endong; Ren, Yujing; Xiao, Kang; Liu, Xu; Yang, Dan; Gao, Yi; Ding, Weiping; Zhu, Yan
    Journal: Advanced Functional Materials
    

    25. 


	


	

	






	
	

		


Abrham Kassie | Engineering | Best Researcher Award
			

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Mr. Abrham Kassie | Engineering | Best Researcher Award


Lecturer at Bahir Dar Institute of Technology, Bahir Dar University, Ethiopia










Abrham Tadesse Kassie is a dedicated researcher and academic specializing in electrical and computer engineering, particularly in industrial control and instrumentation. With a strong background in control systems, renewable energy, and artificial intelligence-based control strategies, he has contributed significantly to the field through research and teaching. He has served as a lecturer at Bahir Dar University and Debre Tabor University, mentoring students and conducting advanced research. His expertise spans control system design for robotics, electric vehicles, renewable energy systems, and smart grids. Through numerous publications and ongoing research, he continues to advance the field of intelligent control systems.


Professional Profile



Education


Abrham Tadesse Kassie obtained a Bachelor of Science degree in Electrical and Computer Engineering (Industrial Control Engineering) from Hawassa University in 2015, graduating with distinction. He then pursued a Master of Science in Electrical and Computer Engineering (Control and Instrumentation Engineering) at Addis Ababa Science and Technology University, earning his degree in 2019 with honors. His coursework included advanced studies in optimal control, nonlinear and adaptive control, digital signal processing, embedded systems, and artificial intelligence-based control. His strong academic performance reflects his commitment to excellence in engineering and research.


Professional Experience


Mr. Kassie has extensive teaching and research experience. He began his academic career as an Assistant Lecturer at Debre Tabor University in 2015 before being promoted to Lecturer in 2019. In 2021, he joined Bahir Dar Institute of Technology, Bahir Dar University, where he continues to serve as a Lecturer. Additionally, from November 2022 to January 2025, he held the position of Chairholder of Industrial Control Engineering (ABET Accredited) at Bahir Dar University. His role involves curriculum development, research supervision, and leading innovative projects in control engineering.


Research Interest


His research interests are centered around control system design for robotics, electric vehicles, renewable energy, airborne wind energy, and smart grids/microgrids. He is particularly focused on developing intelligent control strategies using machine learning and optimization techniques. His work includes designing adaptive and robust controllers for renewable energy applications, trajectory tracking for robotic systems, and enhancing the efficiency of industrial control processes. His research aims to bridge the gap between theoretical advancements and real-world engineering applications.


Research Skills


Mr. Kassie possesses strong technical skills in programming languages, modeling, and simulation software. He is proficient in Python, C++, C, Java, MATLAB, and TIA Portal for PLC programming. Additionally, he has expertise in using simulation tools like Multisim, Proteus, Circuit Maker, and LabVIEW for system modeling and testing. His expertise extends to machine learning applications in control systems, optimization techniques, and intelligent control algorithms. His ability to integrate theoretical models with practical implementations makes him a valuable contributor to advanced engineering research.


Awards and Honors


Throughout his academic journey, Mr. Kassie has received recognition for his outstanding performance. He graduated with distinction during his undergraduate studies and earned his Master’s degree with honors. His role as Chairholder of Industrial Control Engineering at Bahir Dar University is a testament to his leadership and contributions to academia. Additionally, his research publications have gained citations and recognition, demonstrating the impact of his work in the field of electrical and control engineering.


Conclusion


Abrham Tadesse Kassie is a highly skilled researcher with a strong academic and professional background in electrical and control engineering. His contributions to intelligent control systems, renewable energy, and robotics highlight his commitment to advancing technology. While his research is impactful, expanding international collaborations and increasing publication impact can further strengthen his recognition in the field. His expertise, dedication, and innovative mindset make him a strong candidate for the Best Researcher Award.


Publications Top Notes


    

  1. 

    Title: Design of Neuro Fuzzy Sliding Mode Controller for Active Magnetic Bearing Control System
    

      

    • Authors: HF Asres, AT Kassie
      • 

    • Year: 2023
      • 

    • Citations: 5
      • 

    

    2. 

  2. 

    Title: Evaluation of intelligent PPI controller for the performance enhancement of speed control of induction motor
    

      

    • Authors: TG Workineh, YB Jember, AT Kassie
      • 

    • Year: 2023
      • 

    • Citations: 3
      • 

    

    3. 

  3. 

    Title: Direct Adaptive Fuzzy PI Strategy for a Smooth MPPT of Variable Speed Wind Turbines
    

      

    • Authors: A Tadesse, E Ayenew, V LNK
      • 

    • Year: 2021
      • 

    • Citations: 2
      • 

    

    4. 

  4. 

    Title: Dynamic programming strategy in optimal controller design for a wind turbine system
    

      

    • Authors: A Abate Mitaw, A Tadesse Kassie, D Shiferaw Negash
      • 

    • Year: 2024
      • 

    

    5. 

  5. 

    Title: Fuzzy Model Based Model Predictive Control for Biomass Boiler
    

      

    • Authors: GA Nibiret, AT Kassie
      • 

    • Year: 2024
      • 

    

    6. 

  6. 

    Title: Wind Energy Resource Potential Evaluation based on Statistical Distribution Models at Four Selected Locations in Amhara Region, Ethiopia
    

      

    • Authors: YB Jember, GL Hailu, AT Kassie, DA Bimrew
      • 

    • Year: 2023
      • 

    

    7. 

  7. 

    Title: Direct Adaptive Fuzzy Proportional Integral Strategy for a Combined Maximum Power Point Tracking-Pitch Angle Control of Variable Speed Wind Turbine
    

      

    • Authors: AT Kassie
      • 

    • Year: 2019
      • 

    

    8. 



 











	


	

	






	
	

		


Ali Nawaz Sanjrani | Engineering | Best Researcher Award
			

				Posted on  by ScienceFather			

		
	


	

		
Assist. Prof. Dr Ali Nawaz Sanjrani | Engineering | Best Researcher Award


Assistant Professor at University of Electronic Science and Technology of China


Dr. Ali Nawaz Sanjrani is a highly accomplished mechanical engineer and academic with over 18 years of interdisciplinary experience in project management, reliability, quality assurance, and health and safety systems. He holds a PhD in Mechanical Engineering from the University of Electronics Science and Technology, China, and specializes in reliability monitoring, diagnostics, and prognostics of complex machinery. Dr. Sanjrani has a strong background in advanced manufacturing processes, lean manufacturing, and machine learning applications in engineering systems. He has served as an Assistant Professor at Mehran University of Engineering and Technology and has contributed significantly to both academia and industry. His research focuses on fluid dynamics, heat transfer, and predictive maintenance using AI-driven models. Dr. Sanjrani has published extensively in high-impact journals and conferences, earning recognition for his innovative approaches to engineering challenges. He is a certified lead auditor in ISO and OHSAS standards and a member of the Pakistan Engineering Council.


Professional Profile



Education


Dr. Ali Nawaz Sanjrani earned his PhD in Mechanical Engineering from the University of Electronics Science and Technology, Chengdu, China, with a CGPA of 3.89/4. His doctoral research focused on reliability monitoring, diagnostics, and prognostics of complex machinery. He completed his M.Engg. in Industrial Manufacturing from NED University, Karachi, with a CGPA of 3.04/4, specializing in lean manufacturing. His undergraduate degree in Mechanical Engineering was obtained from QUEST, Nawabshah, with an aggregate of 70%, specializing in mechanical manufacturing and materials. Throughout his academic journey, Dr. Sanjrani studied advanced courses such as Finite Element Analysis (FEA), Computer-Aided Manufacturing (CAM), Operations Research (OR), and Agile & Lean Manufacturing. His education has equipped him with a strong foundation in both theoretical and practical aspects of mechanical and industrial engineering, enabling him to excel in research, teaching, and industry applications.


Professional Experience 


Dr. Ali Nawaz Sanjrani has over 18 years of professional experience spanning academia, research, and industry. He served as an Assistant Professor at Mehran University of Engineering and Technology, SZAB Campus, from 2016 to 2020, where he specialized in fluid dynamics, heat transfer, and machine learning applications. Prior to this, he worked as a Lecturer at the same institution and as a visiting faculty member at INDUS University, Karachi. In the industry, Dr. Sanjrani was an Engineer in Quality Assurance and Quality Control at DESCON Engineering Works Limited, Lahore, from 2006 to 2011. His roles included implementing ISO standards, conducting audits, and ensuring quality and safety compliance. Dr. Sanjrani has also led research projects in predictive maintenance, reliability engineering, and lean manufacturing, bridging the gap between academic theory and industrial practice. His expertise in project management and integrated management systems has made him a valuable asset in both academic and professional settings.


Awards and Honors


Dr. Ali Nawaz Sanjrani has received numerous accolades for his academic and professional excellence. He was awarded the 3rd Prize in Academic Excellence and Performance Excellence at the University of Electronics Science and Technology, Chengdu, China, in 2024. He secured a fully funded Chinese Government Scholarship (CSC) for his PhD studies in 2020. Dr. Sanjrani was also recognized with an Appreciation Certificate from Karachi Shipyard & Engineering Works for achieving ISO certifications (QMS, EMS, OH&SMS) in 2011. His innovative approach to dismantling a luffing crane earned him an Appreciation Letter from the Managing Director of KSEW in 2013. Additionally, Dr. Sanjrani has been acknowledged for his research contributions through publications in high-impact journals and presentations at international conferences. His achievements reflect his dedication to advancing engineering knowledge and applying it to real-world challenges.


Research Interests


Dr. Ali Nawaz Sanjrani’s research interests lie at the intersection of mechanical engineering, machine learning, and reliability engineering. He specializes in predictive maintenance, diagnostics, and prognostics of complex machinery, particularly in high-speed trains and industrial systems. His work focuses on developing AI-driven models, such as LSTM networks and neural networks, for fault diagnosis and residual life prediction. Dr. Sanjrani is also deeply involved in fluid dynamics, heat transfer, and energy systems, exploring advanced manufacturing processes and lean manufacturing techniques. His research extends to renewable energy systems, including solar power and biogas utilization, as well as dynamic power management in microgrids. By integrating machine learning with traditional engineering practices, Dr. Sanjrani aims to enhance system reliability, efficiency, and sustainability. His interdisciplinary approach bridges the gap between theoretical research and practical applications, making significant contributions to both academia and industry.


Research Skills


    

  • Machine Learning & AI: Neural Networks, LSTM, Predictive Modeling, Fault Diagnosis.
    • 

  • Reliability Engineering: Prognostics, Diagnostics, Residual Life Prediction.
    • 

  • Fluid Dynamics & Heat Transfer: Modeling, Simulation, and Analysis.
    • 

  • Advanced Manufacturing: Lean Manufacturing, FEA, CAM, Agile Processes.
    • 

  • Renewable Energy Systems: Solar Power, Biogas, Microgrids.
    • 

  • Software Proficiency: Python, MATLAB, SolidWorks, Auto CAD, FEA Tools.
    • 

  • Certifications: ISO 9001, ISO 14001, OHSAS 18001 Lead Auditor.
    • 



Conclusion


Dr. Ali Nawaz Sanjrani is a distinguished mechanical engineer and academic with a proven track record in research, teaching, and industry. His expertise in reliability engineering, machine learning, and advanced manufacturing has led to significant contributions in predictive maintenance and system optimization. With numerous publications, awards, and certifications, Dr. Sanjrani continues to push the boundaries of engineering knowledge, applying innovative solutions to real-world challenges. His interdisciplinary approach and dedication to excellence make him a valuable asset in both academic and professional settings.


Publication Top Notes


    

  1. Ali Nawaz1 – RHSA Based Hybrid Prognostic Model for Predicting Residual Life of Bearing: A Novel Approach – Mechanical Systems and Signal Processing – To be published.
    2. 

  2. Ali Nawaz1 – Multiparametric Dual Task Multioutput Artificial Neural Network Model for Bearing Fault Diagnosis and Residual Life Prediction in High-Speed Trains – IEEE Transaction of Reliability – To be published.
    3. 

  3. Ali Nawaz1 – Advanced Learning Interferential ALI-Former: A Novel Approach for Live and Reliable High-Speed Train Bearing Fault Diagnosis – Neural Computing and Applications – To be published.
    4. 

  4. Ali Nawaz Sanjrani1 – High-Speed Train Bearing Health Assessment Based on Degradation Stages Through Diagnosis and Prognosis by Using Dual-Task LSTM With Attention Mechanism – Quality and Reliability Engineering International Journal WILEY – 2025.
    5. 

  5. Ali Nawaz Sanjrani3 – Dynamic Temporal LSTM-Seqtrans for Long Sequence: An Approach for Credit Card and Banking Accounts Fraud Detection in Banking System – 2024 21st International Computer Conference on Wavelet Active Media Technology and Information Processing – 2025.
    6. 

  6. Ali Nawaz Sanjrani1 – High-speed train wheel set bearing analysis: Practical approach to maintenance between end of life and useful life extension assessment – Results in Engineering – 2025.
    7. 

  7. Ali Nawaz Sanjrani5 – Advanced dynamic power management using model predictive control in DC microgrids with hybrid storage and renewable energy sources – Journal of Energy Storage – 2025.
    8. 

  8. Ali Nawaz Sanjrani1 – High-Speed Train Health Assessment Based on Degradation Stages and Fault Classification by using Dual Task LSTM with Attention Mechanism – 2024 6th International Conference on System Reliability and Safety Engineering – 2024.
    9. 

  9. A.N. Sanjrani – A C-band Sheet Beam Staggered Double Grating Extended Interaction Oscillator – 2024 IEEE International Conference on Plasma Science (ICOPS) – 2024.
    10. 

  10. Ali Nawaz1 – Bearing Health and Safety Analysis to improve the reliability and efficiency of Horizontal Axis Wind Turbine (HAWT) – ESREL 2023 – 2023.
    11. 

  11. Ali Nawaz2 – Prediction of Remaining Useful Life of Bearings using a Parallel Neural Network – ESREL 2023 – 2023.
    12. 

  12. Ali Nawaz Sanjrani2 – Performance Improvement through Lean System Case study of Karachi Shipyard & Engineering Works – IEIM 2024 – 2023.
    13. 

  13. Ali Nawaz Sanjrani3 – Dynamic Performance of Partially Orifice Porous Aerostatic Thrust Bearing – Micromachines – 2021.
    14. 

  14. Sanjrani; Ali Nawaz2 – Performance Evaluation of Mono Crystalline Silicon Solar Panels in Khairpur, Sind, Pakistan – JOJ Material Science – 2017.
    15. 

  15. A. N. Sanjrani1 – Utilization of Biogas using Portable Biogas Anaerobic Digester in Shikarpur and Sukkur Districts: A case study – Pakistan Journal of Agriculture Engineering Veterinary Science – 2017.
    16. 

  16. A. N. Sanjrani1 – Lean Manufacturing for Minimization of Defects in the Fabrication Process of Shipbuilding: A case study – Australian Journal of Engineering and Technology Research – 2017.
    17.