Tatek Wondimu Negash | Irrigation and Drainage Engineering | Best Researcher Award

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Mr. Tatek Wondimu Negash | Irrigation and Drainage Engineering | Best Researcher Award

Agricultural Researcher at Ethiopia Institute Of Agricultural Research, Melkassa Agricultural Research Center, Ethiopia

Tatek Wondimu Negash is a dedicated Water Resource and Irrigation Engineer and Researcher with over eight years of expertise in agricultural water management, hydrological modeling, land use, and climate change. His work focuses on optimizing irrigation systems to enhance productivity and water efficiency in semi-arid regions. He has extensive experience in stakeholder collaboration, working with farmers, government bodies, and research institutions. With multiple publications in high-impact journals, Tatek has significantly contributed to research on evapotranspiration, crop coefficients, and water allocation strategies. His technical proficiency in GIS, hydrological modeling, and irrigation system design, combined with his commitment to research and development, makes him a valuable contributor to sustainable water management.

Professional Profile 

Education

Tatek earned his BSc in Water Resources and Irrigation Engineering from Hawassa University, Ethiopia, in 2015. He further pursued an MPhil in Irrigation and Drainage Engineering at the University for Development Studies, Ghana, under a prestigious World Bank-funded scholarship from the West Africa Center for Water, Irrigation, and Sustainable Agriculture (WACWISA). His thesis investigated the impact of land use and land cover changes on watershed hydrology in Ethiopia. Additionally, he has completed various professional training programs, including data analysis, integrated water resource management, and eco-hydrology. His continuous pursuit of knowledge in irrigation technology and hydrology highlights his commitment to addressing water resource challenges.

Professional Experience

Since 2016, Tatek has been working as a Water Resources and Irrigation Engineer and Researcher at the Ethiopia Institute of Agricultural Research (EIAR), Melkassa Agricultural Research Center. His role involves identifying research gaps, designing and supervising irrigation projects, optimizing crop water requirements, and implementing innovative irrigation technologies. He has expertise in using advanced modeling tools such as ArcGIS, SWAT, DSSAT, and Aquacrop to improve water use efficiency. Tatek actively collaborates with local and international stakeholders to enhance agricultural water management practices. Additionally, he has participated in numerous workshops and training sessions, further expanding his expertise in hydrology and irrigation system design.

Research Interest

Tatek Wondimu Negash’s research focuses on sustainable water resource management, precision irrigation techniques, hydrological modeling, and the impact of climate change on agricultural water availability. His work aims to enhance water-use efficiency through innovative irrigation scheduling and crop water requirement assessments. He is particularly interested in the application of remote sensing and GIS in hydrology, evapotranspiration modeling, and the development of decision-support tools for irrigation planning. Tatek also investigates the effects of land use and land cover changes on watershed hydrology, emphasizing the need for integrated water management strategies. His research contributes to improving agricultural productivity in water-scarce regions, ensuring food security and environmental sustainability.

Awards and Honors

Tatek Wondimu Negash has been recognized for his outstanding contributions to water resource management and irrigation engineering. He received a prestigious World Bank-funded scholarship under the West Africa Center for Water, Irrigation, and Sustainable Agriculture (WACWISA) program for his MPhil studies. His research on watershed hydrology and irrigation efficiency has earned him several acknowledgments from academic and professional institutions. Tatek has also been invited to present his findings at international conferences and workshops, highlighting his expertise in agricultural water management. Additionally, he has received institutional awards for his contributions to applied research and innovative solutions in irrigation systems.

Research Skills

Tatek possesses strong technical expertise in hydrological and crop modeling, remote sensing, and geographic information system (GIS) applications in water resource management. He is proficient in using software such as ArcGIS, SWAT, DSSAT, AquaCrop, and CROPWAT for analyzing water balance, soil moisture, and irrigation efficiency. His skills also extend to statistical data analysis, programming in R and Python, and scientific writing for high-impact journals. With hands-on experience in field data collection, hydrometric station setup, and water quality assessment, he excels in designing and implementing sustainable irrigation strategies. His ability to integrate theoretical knowledge with practical applications makes him a valuable researcher in agricultural water management.

Conclusion

Tatek Wondimu Negash is highly suitable for the Best Researcher Award, given his strong research background, significant contributions to agricultural water management, multiple peer-reviewed publications, and practical impact in irrigation and hydrology. His work has clear relevance to sustainable development and food security, making him a strong candidate. Enhancing his global outreach, innovation, and leadership roles would further solidify his position as a leading researcher in his field.

Publications Top Noted

  • Optimal Irrigation Water Allocation for Enhanced Productivity of Haricot Bean (Phaseolus vulgaris) and Economic Gain: An Experiment Conducted in the Semi-Arid Area of Ethiopia

    • Authors: Tatek Wondimu Negash, Abera Tesfaye Tefera, Gobena Dirirsa Bayisa, Gebeyehu Ashami, Ketema Tezera Bizuneh, Tigist Worku, Aynalem Gurms
    • Year: 2025
    • Citation: Negash, T. W., Tefera, A. T., Bayisa, G. D., Ashami, G., Bizuneh, K. T., Worku, T., & Gurms, A. (2025). Optimal irrigation water allocation for enhanced productivity of haricot bean (Phaseolus vulgaris) and economic gain: An experiment conducted in the semi-arid area of Ethiopia. Journal of Agriculture and Food Research, DOI: 10.1016/j.jafr.2025.101668

  • Optimal Irrigation Water Allocation for Enhanced Productivity of Pepper (Capsicum annuum L.) and Economic Gain: Evidence from the Semi‐Arid Region of Ethiopia

    • Authors: Tatek Wondimu Negash, Abera Tesfaye Tefera, Tigist Worku Awlachew, Aynalem Gurms Denku, Gobena Dirirsa Bayisa, Ketema Tezera Bizuneh, Gebeyehu Ashami Bikila
    • Year: 2025
    • Citation: Negash, T. W., Tefera, A. T., Awlachew, T. W., Denku, A. G., Bayisa, G. D., Bizuneh, K. T., & Bikila, G. A. (2025). Optimal irrigation water allocation for enhanced productivity of pepper (Capsicum annuum L.) and economic gain: Evidence from the semi‐arid region of Ethiopia. Irrigation and Drainage, DOI: 10.1002/ird.3094

  • Irrigation Water Allocation for Enhanced Productivity and Economic Gain of Haricot Bean (Phaseolus vulgaris): A Study in the Semi-Arid Region of Ethiopia

    • Authors: Tatek Wondimu Negash, Abera Tesfaye Tefera, Gebeyehu Ashami Bikila, Aynalem Gurms Dinku, Tigist Worku, Ketema Tezera, Gobena Dirirsa Bayisa
    • Year: 2025
    • Citation: Negash, T. W., Tefera, A. T., Bikila, G. A., Dinku, A. G., Worku, T., Tezera, K., & Bayisa, G. D. (2025). Irrigation water allocation for enhanced productivity and economic gain of haricot bean (Phaseolus vulgaris): A study in the semi-arid region of Ethiopia. Air, Soil and Water Research, DOI: 10.1177/11786221251316538

  • Determination of Evapotranspiration and Crop Coefficient for Tomato by Using Non-Weighing Lysimeter in the Semiarid Region

    • Authors: Tatek Wondimu Negash, Abera Tesfaye Tefera, Gebeyehu Ashemi Bikila, Ketema Tezera Bizuneh, Tigist Worku Awulachew, Aynalem Gurms Dinku
    • Year: 2024
    • Citation: Negash, T. W., Tefera, A. T., Bikila, G. A., Bizuneh, K. T., Awulachew, T. W., & Dinku, A. G. (2024). Determination of evapotranspiration and crop coefficient for tomato by using non-weighing lysimeter in the semiarid region. Air, Soil and Water Research, DOI: 10.1177/11786221241291313

  • Nitrogen and Soil Moisture Optimization for Tomato Crops in Semi-Arid Areas of Ethiopia

    • Authors: Abera Tesfaye, Tatek Wondimu, Ketema Tezera, Gebeyehu Ashemi, Tigist Worku, Aynalem Gurms
    • Year: 2024
    • Citation: Tesfaye, A., Wondimu, T., Tezera, K., Ashemi, G., Worku, T., & Gurms, A. (2024). Nitrogen and soil moisture optimization for tomato crops in semi-arid areas of Ethiopia. Air, Soil and Water Research, DOI: 10.1177/11786221241289641

  • Evapotranspiration and Crop Coefficient of Sorghum (Sorghum bicolor L.) at Melkassa Farmland, Semi-Arid Area of Ethiopia

    • Authors: Tatek Wondimu Negash, Gobena Dirirsa Bayisa, Abera Tesfaye Tefera, Ketema Tezera Bizuneh, Aynalem Gurms Dinku, Tigist Worku Awulachew, Gebeyehu Ashemi Bikela
    • Year: 2023
    • Citation: Negash, T. W., Bayisa, G. D., Tefera, A. T., Bizuneh, K. T., Dinku, A. G., Awulachew, T. W., & Bikela, G. A. (2023). Evapotranspiration and crop coefficient of sorghum (Sorghum bicolor L.) at Melkassa farmland, semi-arid area of Ethiopia. Air, Soil and Water Research, DOI: 10.1177/11786221231184206

Bimal Kumar Dora | Engineering | Best Researcher Award

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Mr. Bimal Kumar Dora | Engineering | Best Researcher Award

PhD at Visvesvaraya National Institute of Technology Nagpur, India

Bimal Kumar Dora is an emerging researcher in electrical engineering with a strong focus on power system optimization and renewable energy integration. Currently pursuing a PhD at Visvesvaraya National Institute of Technology, his research addresses critical challenges in developing a global electricity grid by integrating advanced machine learning and meta-heuristic algorithms. He has contributed significantly to academic literature through multiple publications in reputed international journals and conferences, emphasizing innovative solutions such as hybrid optimization techniques and robust algorithmic frameworks. His work bridges traditional power systems with modern computational methods, demonstrating both theoretical insight and practical application. Alongside his research, he actively participates in workshops and seminars that further enhance his expertise in control, power, and electric drives. His dedication is evidenced by prestigious fellowships and continuous professional development. Dora’s interdisciplinary approach and commitment to solving complex energy problems make him a promising candidate for future advancements in sustainable power systems.

Professional Profile 

Education

Bimal Kumar Dora’s academic journey reflects a dedicated and robust foundation in electrical engineering and research methodologies. He began his studies with a Diploma in Electrical Engineering from Odisha School of Mining Engineering, where he built his fundamental technical skills. Subsequently, he earned a Bachelor’s degree in Electrical Engineering from Gandhi Institute for Technological Advancement, further solidifying his expertise in the field. His academic progression continued with a Master of Technology from the National Institute of Technology Sikkim, where he specialized in Control, Power, and Electric Drives, achieving an outstanding CGPA and engaging in research on power system optimization. Currently, he is pursuing a PhD at Visvesvaraya National Institute of Technology, focusing on the global electricity grid and integrating innovative approaches in machine learning and meta-heuristic algorithms. This comprehensive educational background has equipped him with both theoretical knowledge and practical skills necessary for addressing complex challenges in sustainable energy systems.

Professional Experience

Bimal Kumar Dora’s professional experience exemplifies high-level research and practical applications in the electrical engineering domain. As a dedicated researcher, he has contributed to multiple international journals and conference proceedings, showcasing his work on power system optimization, renewable energy integration, and advanced algorithm development. His work has earned international acclaim. His research projects involve developing innovative hybrid algorithms such as the Exchange Market based Butterfly Optimization Algorithm, tested on standard IEEE systems and real-world power grids. Dora’s experience extends to collaborating with renowned academic institutions and industry experts, enhancing the translational impact of his work. In addition, he has participated in various workshops and seminars focused on control systems, power electronics, and emerging technologies. His technical proficiency in programming tools like Python and MATLAB reinforces his ability to tackle complex engineering challenges. Through professional development and engagement in cutting-edge research, he remains a key asset to the sustainable energy sector.

Research Interest

Mr. Bimal Kumar Dora’s research interests lie at the intersection of power system optimization, renewable energy integration, and advanced computational techniques. His work primarily focuses on developing efficient algorithms to tackle complex challenges in modern electrical grids, including the integration of renewable energy sources into a global electricity grid. He employs machine learning, meta-heuristic, and soft computing methods to design and implement innovative solutions for generation expansion planning and optimal reactive power dispatch. His exploration of hybrid optimization techniques—such as the Exchange Market based Butterfly Optimization Algorithm—demonstrates his commitment to enhancing system reliability and efficiency. By integrating traditional power system engineering with contemporary data-driven methodologies, his research addresses both theoretical and practical aspects of sustainable energy systems. This multidisciplinary approach not only contributes to academic literature but also offers tangible benefits for industry applications, making his work highly relevant in the evolving landscape of energy management and smart grid technologies.

Award and Honor

Throughout his academic and research career, Mr. Dora has received significant recognition for his dedication and innovative contributions. Notably, he qualified in the GATE examination in 2018, which paved the way for prestigious scholarships and fellowships. His academic excellence was further acknowledged through the AICTE GATE Scholarship awarded by MHRD during his M. Tech studies, reinforcing his capability in rigorous research and problem-solving. Currently, his potential is recognized with the MHRD Research Fellowship, an honor that supports his PhD work at Visvesvaraya National Institute of Technology. These awards not only underscore his technical proficiency and research acumen but also reflect his commitment to pushing the boundaries of electrical engineering. Such accolades serve as a testament to his ability to innovate and lead in the field of sustainable energy solutions, earning him respect and admiration among his peers and mentors.

Research Skill

Mr. Bimal Kumar Dora exhibits a robust set of research skills that are fundamental to his success as an emerging scholar in electrical engineering. His technical expertise spans a wide array of programming and simulation tools, including Python, MATLAB, and Octave, which he adeptly applies to model complex power systems and optimize performance. Proficient in using specialized software such as QGIS, MiPower, and Power World, he efficiently conducts simulations and analyses that support his research hypotheses. Additionally, his familiarity with real-time simulators like Typhon HIL and the Real-Time Transmission Line Simulator enhances his ability to test theoretical models under practical conditions. His skills extend to academic writing and presentation, supported by his proficiency in LATEX and MS Office. This comprehensive toolkit not only allows him to conduct innovative experiments and develop hybrid algorithms but also ensures that his findings are communicated effectively through high-impact publications and presentations at international conferences.

Conclusion

Bimal Kumar Dora demonstrates significant promise as a researcher with a strong foundation in innovative and interdisciplinary work. His solid academic record, impactful publications, and technical proficiency make him a compelling candidate for the Best Researcher Award. Addressing areas such as leadership in collaborative projects and extending the societal impact of his research could further elevate his profile. Overall, his achievements and ongoing commitment to advancing power system optimization and renewable energy integration mark him as a deserving contender for this recognition.

Publications Top Noted

Inverse Thresholding to Spectrogram for the Detection of Broken Rotor Bar in Induction Motor
Title: Inverse Thresholding to Spectrogram for the Detection of Broken Rotor Bar in Induction Motor
Authors: S Halder, S Bhat, BK Dora
Year: 2022
Citation Count: 18

An Enhanced Pathfinder Algorithm Based MCSA for Rotor Breakage Detection of Induction Motor
Title: An Enhanced Pathfinder Algorithm Based MCSA for Rotor Breakage Detection of Induction Motor
Authors: S Halder, BK Dora, S Bhat
Year: 2022
Citation Count: 15

Optimal Reactive Power Dispatch Problem Using Exchange Market Based Butterfly Optimization Algorithm
Title: Optimal Reactive Power Dispatch Problem Using Exchange Market Based Butterfly Optimization Algorithm
Authors: BK Dora, A Rajan, S Mallick, S Halder
Year: 2023
Citation Count: 14

Start-up Transient Analysis Using CWT and Ridges for Broken Rotor Bar Fault Diagnosis
Title: Start-up Transient Analysis Using CWT and Ridges for Broken Rotor Bar Fault Diagnosis
Authors: S Halder, S Bhat, B Dora
Year: 2023
Citation Count: 14

Solution of Reactive Power Dispatch Problems Using Enhanced Dwarf Mongoose Optimization Algorithm
Title: Solution of Reactive Power Dispatch Problems Using Enhanced Dwarf Mongoose Optimization Algorithm
Authors: BK Dora, S Bhat, S Halder, M Sahoo
Year: 2023
Citation Count: 13

A Solution to the Techno-Economic Generation Expansion Planning Using Enhanced Dwarf Mongoose Optimization Algorithm
Title: A Solution to the Techno-Economic Generation Expansion Planning Using Enhanced Dwarf Mongoose Optimization Algorithm
Authors: BK Dora, S Bhat, S Halder, I Srivastava
Year: 2022
Citation Count: 8

A Solution to Multi Objective Stochastic Optimal Power Flow Problem Using Mutualism and Elite Strategy Based Pelican Optimization Algorithm
Title: A Solution to Multi Objective Stochastic Optimal Power Flow Problem Using Mutualism and Elite Strategy Based Pelican Optimization Algorithm
Authors: BK Dora, S Bhat, S Halder, I Srivastava
Year: 2024
Citation Count: 6

Optimum Scheduling and Dispatch of Power Systems with Renewable Integration
Title: Optimum Scheduling and Dispatch of Power Systems with Renewable Integration
Authors: A Rajan, BK Dora
Year: 2022
Citation Count: 5

Prediction of Broken Rotor Bar in Induction Motor Using Spectral Entropy Features and TLBO Optimized SVM
Title: Prediction of Broken Rotor Bar in Induction Motor Using Spectral Entropy Features and TLBO Optimized SVM
Authors: S Halder, S Bhat, B Dora
Year: 2022
Citation Count: 3

An Enhanced Path Finder Algorithm for the Estimation of the Stator Current Envelope to Detect Rotor Bar Breakage in an Induction Motor
Title: An Enhanced Path Finder Algorithm for the Estimation of the Stator Current Envelope to Detect Rotor Bar Breakage in an Induction Motor
Authors: S Halder, BK Dora, S Bhat
Year: 2024
Citation Count: 2

Mohammad Mahdi Ochi | Engineering | Best Researcher Award

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Dr. Mohammad Mahdi Ochi | Engineering | Best Researcher Award

School of Life Science Engineering at College of Interdisciplinary Science and Technology, University of Tehran, Iran

Dr. Mohammad Mahdi Ochi is a distinguished researcher whose innovative work bridges the fields of nano-biotechnology, biomimetics, and smart drug delivery systems. With a primary focus on developing novel nano-liposome based herbal drug delivery platforms, his research addresses critical challenges in targeted cancer therapy and sustainable medicinal practices. As an assistant professor at the University of Tehran, Dr. Ochi has established a reputation for academic excellence and pioneering research that integrates interdisciplinary methodologies. His scholarly contributions include multiple patents, high-impact publications, and participation in international conferences, showcasing his ability to translate complex scientific concepts into practical applications. Dr. Ochi’s research portfolio reflects a commitment to advancing both fundamental science and applied technologies, making significant contributions to the fields of nano-biotechnology and plant-based therapeutics. His work is recognized for its potential to improve therapeutic outcomes and foster innovation in drug delivery systems. Dr. Ochi continues inspiring many emerging researchers worldwide.

Professional Profile 

Education

Dr. Mohammad Mahdi Ochi’s academic journey is marked by consistent excellence and a passion for scientific inquiry. He earned his B.Sc. in Plant Protection from the University of Tehran in 2006, achieving a notable average score and establishing a strong foundation in biological sciences. Continuing his academic pursuits at the same institution, he completed an M.Sc. in Phytopathology, and later specialized in Nanobiotechnology, securing high marks that reflected his academic rigor. Recognized as an elite student during his Ph.D. program in Nano-Biotechnology at the University of Tehran’s Faculty of New Science and Technology, he benefited from prestigious scholarships and awards. His rigorous training has been instrumental in shaping his research skills, contributing to his innovative work in nano-biomimetic systems and smart drug delivery. This educational background not only highlights his academic prowess but also underpins his commitment to advancing interdisciplinary research. His outstanding education continues to drive his future achievements.

Professional Experience

Dr. Mohammad Mahdi Ochi’s professional journey reflects a robust blend of academic and research excellence. Currently serving as an assistant professor at the University of Tehran’s School of Life Science Engineering, he has played a pivotal role in advancing interdisciplinary research initiatives. His expertise in nano-biotechnology and smart drug delivery systems has led to the development of innovative nano-liposome platforms for targeted cancer therapy. Dr. Ochi has secured multiple patents, including a U.S. patent for a targeted nano-liposome co-encapsulating anti-cancer drugs, showcasing his ability to translate research into practical solutions. He actively participates in international conferences, disseminating his research findings and fostering collaborations with global experts. Through leadership in various research projects and mentorship of emerging scholars, he continuously contributes to the advancement of nanobiotechnology. His professional experience is a testament to his dedication, innovation, and impactful contributions to both scientific research and academic development. His career continues to flourish.

Research Interest

Dr. Mohammad Mahdi Ochi’s research interests revolve around the innovative integration of nano-biotechnology, nano-biomimetics, smart drug delivery systems, and natural nano-supplements. He passionately explores the development of advanced nano-liposome based herbal drug delivery systems to enhance targeted therapeutic outcomes, with a particular focus on liver cancer treatment. His work bridges the gap between traditional herbal medicine and cutting-edge nanotechnology, fostering systems that improve drug bioavailability while minimizing side effects. By employing the principles of biomimetics, he designs drug carriers that mimic natural biological processes, thereby optimizing therapeutic efficiency. In addition, he investigates the potential of natural nano-supplements to boost the efficacy of medicinal compounds. Dr. Ochi’s interdisciplinary approach not only addresses complex challenges in drug delivery but also paves the way for breakthroughs in personalized medicine. His research aims to revolutionize treatment protocols, offering safer and more effective solutions for patients and contributing substantially to the advancement of healthcare technology.

Award and Honor

Dr. Mohammad Mahdi Ochi’s career is marked by a series of awards and honors that underscore his academic excellence and research innovation. Recognized early on as an elite student during his B.Sc., M.Sc., and Ph.D. studies at the University of Tehran, his consistent high performance has been lauded by peers and mentors alike. His doctoral achievements, including exceptional thesis scores and scholarship awards, reflect his dedication and intellectual rigor. In addition to academic accolades, Dr. Ochi has earned prestigious research awards for his groundbreaking ideas in nano-biotechnology and smart drug delivery systems. His record includes several patents, notably a U.S. patent for a targeted nano-liposome co-encapsulating anti-cancer drugs, which serves as a testament to his inventive contributions. These honors validate his expertise and reinforce his reputation as a leading figure in his field, inspiring confidence in his potential to drive transformative advances in biomedical research.

Research Skill

Dr. Mohammad Mahdi Ochi has demonstrated exceptional research skills through a robust portfolio that combines technical precision, innovative methodologies, and interdisciplinary collaboration. His expertise in nano-biotechnology and smart drug delivery is evident from his extensive work on nano-liposome based systems designed for targeted cancer therapy. He skillfully integrates experimental design, data analysis, and advanced patent development into his research, consistently producing high-impact publications and presenting his findings at international conferences. Dr. Ochi’s ability to synthesize concepts from plant pathology, nanotechnology, and medicinal chemistry underpins his creative approach to solving complex scientific problems. His meticulous attention to detail, coupled with strategic project management and successful acquisition of competitive research funding, further highlights his research prowess. Moreover, his commitment to mentoring emerging scholars and fostering collaborative environments demonstrates a leadership quality that not only enriches his own work but also inspires innovation across the broader scientific community.

Conclusion

Mohammad Mahdi Ochi exhibits a strong and innovative research profile characterized by academic excellence, pioneering work in nano-biomimetic drug delivery systems, and a proven record of interdisciplinary contributions. His patented innovations and diverse publication record highlight his potential to drive significant advances in nanobiotechnology and related fields. With targeted efforts to enhance international exposure and leadership within collaborative projects, Ochi is a highly deserving candidate for the Best Researcher Award.

Publications Top Noted

Title:
Biological and Chemical Assessment of the Liposomes Carrying a Herbal MRI Contrast Agent

Authors:
Ali Yazdani, Mohammad Mahdi Ochi, Nafiseh Hassani, Ahmadreza Okhovat, Hamid Soltanian-Zadeh

Year:
2025

Citations:
0

Jinsheng Liang | Engineering | Best Researcher Award

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Dr. Jinsheng Liang | Engineering | Best Researcher Award

PhD Candidate at Shenyang Institute of Automation, Chinese Academy of Science, China

Dr. Jinsheng Liang is a distinguished researcher specializing in ultra-precision machining and water jet-guided laser technology. He earned his Bachelor of Engineering from Wuhan University of Technology and is currently pursuing a Doctorate in Engineering at the Shenyang Institute of Automation, Chinese Academy of Sciences. His research focuses on fluid flow characteristics, laser transmission mechanisms, and high-efficiency milling techniques, contributing to advancements in precision manufacturing. Dr. Liang has played a key role in national research projects, particularly in enhancing the stability and efficiency of light-guiding liquid beams in laser processing. He has published five high-impact papers in The International Journal of Advanced Manufacturing Technology and Optics & Laser Technology, demonstrating expertise in fluid simulation and mechanical manufacturing. With strong technical skills and a commitment to innovation, Dr. Liang continues to push the boundaries of laser machining technology, aiming to bridge the gap between academic research and industrial applications.

Professional Profile 

Education

Dr. Jinsheng Liang has a strong academic background in mechanical engineering and ultra-precision machining. He is currently pursuing a Doctor of Engineering at the Shenyang Institute of Automation, Chinese Academy of Sciences, specializing in mechanical manufacturing and automation. His doctoral research focuses on water jet-guided laser technology, fluid flow simulation, and high-precision machining. Prior to this, he earned his Bachelor of Engineering in mechanical design, manufacturing, and automation from Wuhan University of Technology in 2019. Throughout his academic journey, Dr. Liang has gained extensive expertise in laser machining techniques, fluid dynamics, and numerical simulations, contributing to cutting-edge research in precision manufacturing. His educational background, combined with hands-on research experience, has positioned him as a promising expert in his field, bridging theoretical knowledge with practical applications to advance high-efficiency laser processing technologies.

Professional Experience

Dr. Jinsheng Liang has extensive research experience in ultra-precision machining and water jet-guided laser technology. Since 2019, he has been pursuing his Doctor of Engineering at the Shenyang Institute of Automation, Chinese Academy of Sciences, where he has been actively involved in national research projects. His key contributions include research on laser electrolysis composite high-efficiency milling technology and the stability of internal light-guiding liquid beams and laser transmission mechanisms. He has utilized Fluent software for fluid simulations, combining theoretical modeling with experimental validation to enhance laser machining precision. Dr. Liang has published five high-impact papers in renowned journals, solidifying his expertise in laser technology, fluid simulation, and mechanical manufacturing. His work significantly contributes to advancements in high-precision manufacturing, and his ability to integrate research findings with industrial applications underscores his potential as a leading researcher in laser machining and automation.

Research Interest

Dr. Jinsheng Liang’s research interests lie in the fields of laser technology, fluid simulation, and mechanical manufacturing, with a particular focus on ultra-precision machining and water jet-guided laser technology. His work explores fluid flow characteristics, laser transmission mechanisms, and high-efficiency milling techniques, aiming to improve the precision and stability of laser processing. He specializes in the numerical simulation of liquid-guided laser beams, using Fluent software to model fluid behavior and enhance machining accuracy. His research also extends to the development of advanced laser processing methods for complex materials, with potential applications in aerospace, electronics, and high-tech manufacturing. Through his studies, Dr. Liang seeks to bridge the gap between theoretical modeling and experimental validation, contributing to the advancement of next-generation laser machining technologies. His expertise in precision engineering and automation positions him as a key contributor to the future of high-precision manufacturing.

Award and Honor

Currently, there are no explicitly listed awards and honors for Dr. Jinsheng Liang. However, his significant contributions to ultra-precision machining and water jet-guided laser technology highlight his growing impact in the field of mechanical manufacturing and automation. As a doctoral researcher at the Shenyang Institute of Automation, Chinese Academy of Sciences, he has been actively involved in national research projects, demonstrating excellence in fluid simulation, laser transmission mechanisms, and high-efficiency milling techniques. His five high-impact publications in prestigious journals, such as The International Journal of Advanced Manufacturing Technology and Optics & Laser Technology, reflect the recognition of his work within the scientific community. Given his expertise and research accomplishments, Dr. Liang is a strong candidate for future academic awards, industry recognitions, and research grants. His contributions to precision laser machining and automation continue to position him as an emerging leader in the field.

Research Skill

Dr. Jinsheng Liang possesses advanced research skills in laser technology, fluid simulation, and mechanical manufacturing, with a strong focus on ultra-precision machining and water jet-guided laser technology. He is proficient in numerical simulation and computational fluid dynamics (CFD), utilizing Fluent software to analyze fluid flow characteristics and laser transmission mechanisms. His expertise extends to experimental validation, where he integrates simulation results with real-world laser machining processes to enhance precision and efficiency. Dr. Liang has a deep understanding of laser-material interactions, milling techniques, and high-efficiency processing methods, allowing him to contribute to cutting-edge manufacturing advancements. His ability to design and execute complex experiments, analyze large datasets, and optimize machining parameters makes him a valuable researcher in the field. With five high-impact journal publications, he demonstrates strong skills in technical writing, data interpretation, and problem-solving, essential for advancing high-precision laser processing technologies.

Conclusion

Jinsheng Liang is a strong candidate for the Best Researcher Award due to his specialized expertise, impactful research, and high-quality publications. His contributions to ultra-precision machining and laser technology are commendable, and his ability to conduct numerical simulations and experimental studies is impressive. Strengthening industry impact and international collaboration would further elevate his profile.

Publications Top Noted

Authors: Jinsheng Liang, Hongchao Qiao, Jibin Zhao, Yuting Zhang, Qing Zhang
Year: 2025
Journal: Optics and Laser Technology
Title: Simulation and experimental study on double staggered-axis air-assisted water jet-guided laser film cooling hole machining

Yi Sun | Engineering | Best Researcher Award

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Dr. Yi Sun | Engineering | Best Researcher Award

Southwest Jiaotong University, China

Dr. Yi Sun is a distinguished researcher specializing in equipment status monitoring, health indicator construction, and deep learning applications. Currently pursuing a Ph.D. in Mechanical and Electronic Engineering at Southwest Jiaotong University, he has an impressive academic track record with 12 published papers, including 7 SCI papers, 4 of which are in top-tier JCR Q1 journals. His research contributions include developing predictive maintenance algorithms, process parameter optimization, and aerodynamic identification models for hypersonic wind tunnels. He has also led industry projects in predictive maintenance systems and multi-source aerodynamic data fusion. Recognized with multiple National Scholarships and industry accolades such as Huawei’s “Rising Star” award, Dr. Sun demonstrates exceptional expertise in both academic research and practical applications. His work bridges the gap between theoretical advancements and industrial innovation, positioning him as a leading figure in mechanical engineering and deep learning-based monitoring systems.

Professional Profile 

Education

Dr. Yi Sun has a strong educational background in mechanical engineering and electronic systems. He earned his Bachelor’s degree in Mechanical Engineering and Automation from Zhengzhou University (2012-2016), where he built a solid foundation in engineering principles. He then pursued a Master’s degree in Mechanical Engineering at Southwest Jiaotong University (2017-2020), where he gained expertise in advanced manufacturing processes, equipment monitoring, and fault diagnosis. Currently, he is undertaking a Ph.D. in Mechanical and Electronic Engineering at Southwest Jiaotong University (2021-2025), focusing on deep learning applications, health indicator construction, and predictive maintenance for industrial systems. Throughout his academic journey, he has been recognized with prestigious honors, including National Scholarships and Outstanding Graduate Student awards. His education has provided him with a unique blend of theoretical knowledge and practical experience, enabling him to contribute significantly to both academia and industry in the fields of mechanical engineering and intelligent monitoring systems.

Professional Experience

Dr. Yi Sun has a diverse professional background spanning both academia and industry. He worked as an R&D Engineer at Huawei Technologies Co., Ltd. (2020-2021), where he contributed to cutting-edge research and development in predictive maintenance and equipment monitoring. His industry experience provided him with hands-on expertise in software and hardware integration, sensor selection, and algorithm development for real-world applications. As a Ph.D. researcher at Southwest Jiaotong University (2021-present), he has led multiple high-impact projects, including the development of predictive maintenance systems for CNC machine tools and multi-source aerodynamic data fusion models for the China Aerodynamics Research and Development Center. His research has resulted in 12 published papers, several in top-tier journals, and numerous awards for academic excellence. Dr. Sun’s professional journey demonstrates his ability to bridge the gap between theoretical research and industrial innovation, making significant contributions to mechanical engineering and deep learning-based monitoring technologies.

Research Interest

Dr. Yi Sun’s research interests lie at the intersection of mechanical engineering, deep learning, and intelligent monitoring systems. His work focuses on equipment status monitoring, health indicator construction, fault diagnosis, and predictive maintenance for industrial applications. He specializes in process parameter optimization, particularly in milling cutter status assessment, utilizing advanced signal analysis, noise reduction, and online monitoring techniques. His expertise extends to deep learning-based fault detection, including the development of aerodynamic force identification models and transfer learning techniques for aerodynamic data analysis in hypersonic wind tunnels. Dr. Sun is also engaged in multi-source data fusion, enhancing accuracy and consistency in industrial systems. His research aims to optimize mechanical performance, reduce downtime, and improve system reliability through AI-driven solutions. By integrating machine learning with mechanical systems, he contributes to advancing intelligent manufacturing, predictive maintenance, and next-generation industrial automation technologies.

Award and Honor

Dr. Yi Sun has received numerous prestigious awards and honors in recognition of his outstanding academic and research achievements. During his master’s and Ph.D. studies, he was awarded the National Scholarship, one of the highest academic honors in China, for his excellence in research and academics. He was also recognized as an Outstanding Graduate Student at both the university and provincial levels. His exceptional contributions to mechanical engineering and intelligent monitoring systems earned him the Mingcheng Award and the Comprehensive Quality A-Level Certificate during his postgraduate studies. In the corporate sector, he was honored as an Excellent Student in Huawei’s New Employee Training Camp and received the Huawei “Rising Star” Award for his innovative contributions. These accolades reflect his dedication, innovation, and leadership in academia and industry. Dr. Sun’s achievements highlight his remarkable research capabilities and his potential to drive advancements in intelligent manufacturing and predictive maintenance systems.

Research Skill

Dr. Yi Sun possesses exceptional research skills in mechanical engineering, deep learning, and intelligent monitoring systems. His expertise includes equipment status monitoring, fault diagnosis, health indicator construction, and predictive maintenance. He is proficient in signal processing, noise reduction, and multi-source data fusion, enabling accurate real-time monitoring and fault prediction for industrial systems. His strong foundation in deep learning and machine learning algorithms allows him to develop advanced models for aerodynamic force identification and process parameter optimization. Dr. Sun is skilled in software and hardware development, including sensor selection, data acquisition, edge computing, and algorithm integration for predictive maintenance systems. He also excels in scientific writing, publishing high-impact research in top-tier journals and presenting at international conferences. His ability to combine theoretical research with practical industrial applications demonstrates his versatility and innovation, making significant contributions to the advancement of intelligent manufacturing and mechanical system optimization.

Conclusion

Sun Yi is highly suitable for the Best Researcher Award due to his exceptional publication record, innovative contributions to equipment status monitoring and deep learning, industry experience, and leadership in research projects. While he could enhance his application with patents, tech commercialization, and broader collaborations, his current achievements make him a strong candidate for the award. 🚀

Publications Top Noted

  • L. Wei, Y. Sun, J. Zeng, S. Qu (2022). “Experimental and numerical investigation of fatigue failure for metro bogie cowcatchers due to modal vibration and stress induced by rail corrugation.” Engineering Failure Analysis, 142, 106810. Citations: 31

  • Y. Sun, L. Wei, C. Liu, H. Dai, S. Qu, W. Zhao (2022). “Dynamic stress analysis of a metro bogie due to wheel out-of-roundness based on multibody dynamics algorithm.” Engineering Failure Analysis, 134, 106051. Citations: 22

  • J. Mu, J. Zeng, C. Huang, Y. Sun, H. Sang (2022). “Experimental and numerical investigation into development mechanism of wheel polygonalization.” Engineering Failure Analysis, 136, 106152. Citations: 21

  • Y. Li, H. Dai, Y. Qi, S. Qu, Y. Sun (2023). “Experimental study of bogie instability monitoring and suppression measures for high-speed EMUs.” Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit. Citations: 6

  • Y. Sun, L. Wei, H. Dai, C. Liu, S. Qu, Y. Qi (2023). “Influence of rail weld irregularity on dynamic stress of bogie frame based on vehicle-track rigid-flexible coupled model.” Journal of Vibration and Control, 29 (17-18), 4172-4185. Citations: 5

  • Y. Sun, L. Wei, S. Qu, H. Dai (2024). “Fatigue stress estimation of metro bogie frame through frequency response functions by using limited sensors.” Structural Health Monitoring, 23 (1), 421-442. Citations: 2

  • Y. Sun, L. Wei, H. Dai (2024). “Indirect Dynamic Stress Measurement of Metro Bogie Using LSTM Network in Frequency Domain.” IEEE Sensors Journal.

Junaid Khan | Engineering | Young Scientist Award

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Dr. Junaid Khan | Engineering | Young Scientist Award

Senior Engineer at Samsung Heavy Industry, South Korea

Dr. Junaid Khan is a distinguished researcher specializing in autonomous navigation systems, intelligent transportation, and deep learning applications. He earned his Ph.D. in Environmental IT Engineering from Chungnam National University, South Korea, focusing on enhancing Alpha-Beta filters with neural networks and fuzzy systems for maritime navigation. Currently, he serves as a Senior Engineer at the Autonomous Ship Research Center, Samsung Heavy Industries. Dr. Khan has made significant contributions to machine learning, maritime traffic analysis, and energy-efficient intelligent systems, reflected in his numerous high-impact journal publications and patents. His research has advanced predictive modeling techniques for vessel trajectory optimization, epileptic seizure detection, and energy consumption reduction. With a strong academic background, international collaborations, and expertise in large language models and digital twins, he continues to drive innovation in intelligent automation and smart mobility. His work bridges theoretical advancements with real-world applications, positioning him as a leading scientist in his field.

Professional Profile 

Education

Dr. Junaid Khan holds a Ph.D. in Environmental IT Engineering from Chungnam National University, South Korea, where his research focused on enhancing Alpha-Beta filters using neural networks and fuzzy systems for improved maritime navigation. He earned his Master’s degree in Electrical Engineering from the University of Engineering and Technology (UET) Peshawar, Pakistan, specializing in machine learning and intelligent transportation systems. His academic journey laid a strong foundation in artificial intelligence, predictive modeling, and deep learning applications. Throughout his education, Dr. Khan actively engaged in interdisciplinary research, contributing to advancements in autonomous navigation, vessel trajectory optimization, and energy-efficient intelligent systems. His studies also involved extensive work in large language models, maritime traffic analysis, and epileptic seizure detection. With a solid educational background and hands-on experience in cutting-edge research, he has established himself as a leader in AI-driven smart mobility and autonomous systems, bridging theoretical knowledge with practical industry applications.

Professional Experience

Dr. Junaid Khan has extensive professional experience in artificial intelligence, autonomous navigation, and intelligent transportation systems. He is currently contributing to cutting-edge research in AI-driven smart mobility, focusing on vessel trajectory optimization, energy-efficient maritime navigation, and predictive modeling. His expertise spans deep learning, neural networks, and fuzzy logic, which he has applied to real-world problems in environmental IT engineering. Dr. Khan has worked on large-scale projects involving maritime traffic analysis, epileptic seizure detection, and autonomous system development. His industry collaborations and academic research have led to innovative solutions in smart transportation and AI-driven decision-making. Throughout his career, he has been actively involved in publishing high-impact research, mentoring students, and presenting at international conferences. With a strong technical background and hands-on experience in AI applications, Dr. Khan continues to push the boundaries of intelligent mobility, making significant contributions to both academia and industry.

Research Interest

Dr. Junaid Khan’s research interests lie at the intersection of artificial intelligence, autonomous navigation, and intelligent transportation systems. His work focuses on developing AI-driven solutions for smart mobility, including vessel trajectory optimization, energy-efficient maritime navigation, and predictive modeling for transportation networks. He is particularly interested in deep learning, neural networks, and fuzzy logic, applying these techniques to real-world challenges such as maritime traffic analysis, epileptic seizure detection, and autonomous system development. Dr. Khan’s research also explores environmental IT engineering, leveraging AI to enhance sustainability in transportation and logistics. His contributions extend to the design of intelligent decision-making systems that improve safety, efficiency, and energy conservation in autonomous vehicles. With a keen interest in interdisciplinary collaboration, he actively engages in projects that bridge AI with healthcare, maritime operations, and smart city development. Through his research, Dr. Khan aims to advance AI applications in real-world, high-impact domains.

Award and Honor

Dr. Junaid Khan has received numerous awards and honors in recognition of his outstanding contributions to artificial intelligence, autonomous navigation, and intelligent transportation systems. He has been honored with prestigious research grants and fellowships for his innovative work in AI-driven solutions for smart mobility. His contributions to vessel trajectory optimization, deep learning applications, and predictive modeling have earned him accolades from leading academic and professional organizations. Dr. Khan has also been recognized for his exceptional scholarly output, receiving awards for best research papers at international conferences. His work in interdisciplinary research, spanning maritime navigation, healthcare AI, and sustainable transportation, has been acknowledged by esteemed institutions and funding agencies. Additionally, he has been invited as a keynote speaker and session chair at various scientific gatherings, further solidifying his reputation as a leader in his field. Through these honors, Dr. Khan continues to be recognized for his pioneering contributions to AI and intelligent systems.

Research Skill

Dr. Junaid Khan’s research interests lie at the intersection of artificial intelligence, machine learning, and intelligent transportation systems, with a strong focus on autonomous navigation, vessel trajectory optimization, and predictive analytics. His work explores deep learning algorithms, reinforcement learning, and data-driven models to enhance decision-making in maritime and land-based transportation networks. He is particularly interested in developing AI-driven solutions for optimizing vessel routing, minimizing fuel consumption, and improving safety in smart mobility systems. Dr. Khan’s research also extends to healthcare applications, where he leverages machine learning techniques for medical diagnostics and predictive modeling. His interdisciplinary approach integrates AI with real-world challenges, aiming to create sustainable and efficient solutions for global transportation and healthcare industries. With a keen interest in the ethical implications of AI, he also investigates fairness, interpretability, and transparency in automated decision-making systems, ensuring that AI advancements align with societal and industrial needs.

Conclusion

Junaid Khan, Ph.D., is a strong candidate for the Young Scientist Award due to his impressive research contributions, patents, and industry experience. His work in machine learning, maritime navigation, and intelligent transportation systems showcases innovation and impact. Strengthening independent recognition and leadership roles in research projects could further enhance his suitability. Overall, he is a competitive nominee for this award.

Publications Top Noted

  1. A higher prediction accuracy–based alpha–beta filter algorithm using the feedforward artificial neural network

    • Authors: J Khan, E Lee, K Kim
    • Year: 2023
    • Citations: 68

  2. A comprehensive review of conventional, machine learning, and deep learning models for groundwater level (GWL) forecasting

    • Authors: J Khan, E Lee, AS Balobaid, K Kim
    • Year: 2023
    • Citations: 48

  3. An improved alpha beta filter using a deep extreme learning machine

    • Authors: J Khan, M Fayaz, A Hussain, S Khalid, WK Mashwani, J Gwak
    • Year: 2021
    • Citations: 25

  4. Secure and fast image encryption algorithm based on modified logistic map

    • Authors: M Riaz, H Dilpazir, S Naseer, H Mahmood, A Anwar, J Khan, IB Benitez, …
    • Year: 2024
    • Citations: 14

  5. An efficient feature augmentation and LSTM-based method to predict maritime traffic conditions

    • Authors: E Lee, J Khan, WJ Son, K Kim
    • Year: 2023
    • Citations: 14

  6. A performance evaluation of the alpha-beta (α-β) filter algorithm with different learning models: DBN, DELM, and SVM

    • Authors: J Khan, K Kim
    • Year: 2022
    • Citations: 14

  7. An efficient methodology for water supply pipeline risk index prediction for avoiding accidental losses

    • Authors: MS Qureshi, A Aljarbouh, M Fayaz, MB Qureshi, WK Mashwani, J Khan
    • Year: 2020
    • Citations: 10

  8. Optimizing the performance of Kalman filter and alpha-beta filter algorithms through neural network

    • Authors: J Khan, E Lee, K Kim
    • Year: 2023
    • Citations: 5

  9. A Performance Evaluation of the AlphaBeta filter Algorithm with different Learning Modules ANN, DELM, CART and SVM

    • Authors: KK Junaid Khan
    • Year: 2022
    • Citations: 5*

  10. Synthetic Maritime Traffic Generation System for Performance Verification of Maritime Autonomous Surface Ships

  • Authors: E Lee, J Khan, U Zaman, J Ku, S Kim, K Kim
  • Year: 2024
  • Citations: 4

Jawad Ali | Engineering | Best Researcher Award

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Mr. Jawad Ali | Engineering | Best Researcher Award

Ph.D. Researcher at High Frequency Systems Laboratory, King Mongkut’s University of Technology North Bangkok, Bangkok 10800, Thailand

Mr. Jawad Ali is a dedicated researcher specializing in electrical engineering, IoT, and antenna design, with a strong academic background and extensive international exposure. He holds a Ph.D. in Electrical and Software Systems Engineering from King Mongkut’s University of Technology North Bangkok, along with a Master’s in Electrical Engineering (CPA 4.00/4.00) from UTHM Malaysia. His research focuses on IoT-based localization, RF and microwave systems, and biomedical applications, with collaborations at Trinity College Dublin, UTHM, and COMSATS University. Recognized with multiple awards, including the IEEE AP-S Fellowship Grant and Malaysia Technology Expo medals, he has contributed to academia through teaching and mentoring roles. His technical expertise spans antenna fabrication, MATLAB, and RF measurements. As an IEEE and Pakistan Engineering Council member, he continues to advance research through international collaborations and industrial projects. With a strong research portfolio and global impact, he is a highly suitable candidate for the Best Researcher Award.

Professional Profile 

Education

Mr. Jawad Ali has a strong academic background in electrical engineering, specializing in RF, microwave, and IoT-based systems. He is currently completing his Ph.D. in Electrical and Software Systems Engineering at King Mongkut’s University of Technology North Bangkok, where he defended his dissertation with a Grade A. His doctoral research focuses on IoT-based localization of people and objects for the MICE industry. He earned his Master’s degree in Electrical Engineering from Universiti Tun Hussein Onn Malaysia (UTHM) with a perfect CPA of 4.00/4.00, researching ultra-wideband antenna arrays for human scanning under debris. His undergraduate studies were completed through a collaborative program between COMSATS University Islamabad and Lancaster University, UK, where he obtained a Bachelor’s degree in Electrical (Telecommunication) Engineering with First-Class Honours. His academic journey is marked by excellence, international exposure, and contributions to cutting-edge research, making him a distinguished scholar in his field.

Professional Experience

Mr. Jawad Ali has a diverse professional background spanning academia, research, and industry. He currently serves as a Visiting Lecturer at Khwaja Fareed University of Engineering and Information Technology, Pakistan. Previously, he was a Ph.D. Researcher at Trinity College Dublin, contributing to IoT-based localization research. As a Teaching Assistant at King Mongkut’s University of Technology North Bangkok, he worked on RF and microwave engineering projects for MuSpace and PTT Thailand. His tenure at COMSATS University Islamabad as a Laboratory Engineer involved research, academic coordination, and industrial collaborations. Additionally, he worked as a Graduate Research Assistant at UTHM Malaysia, assisting with student research and thesis projects. His early career included a role as a Junior System Support Engineer at HB Media (PVT) Capital TV, handling broadcast engineering operations. With expertise in RF measurements, IoT, and antenna design, he has significantly contributed to both academia and industry.

Research Interest

Mr. Jawad Ali’s research interests lie at the intersection of electrical engineering, RF and microwave systems, IoT, and antenna design. His work focuses on developing advanced localization techniques using multi-standard IoT for applications in the Meetings, Incentives, Conventions, and Exhibitions (MICE) industry. He has a strong background in ultra-wideband (UWB) antenna design, biomedical applications, and radar-based human scanning under debris. His research extends to environmentally friendly antenna materials, ground-penetrating radar for soil scanning, and microstrip line designs using cellulose-based substrates. Collaborating with institutions like Trinity College Dublin, UTHM Malaysia, and COMSATS University Islamabad, he actively contributes to cutting-edge innovations in wireless communications and electromagnetic applications. His expertise in RF measurements, simulation tools like CST Studio Suite and HFSS, and his commitment to advancing antenna technology position him as a leading researcher in the field, with significant contributions to both academia and industry-driven projects.

Award and Honor

Mr. Jawad Ali has received numerous awards and honors in recognition of his outstanding research contributions and academic excellence. He was awarded the Bronze Medal at the Malaysia Technology Expo MARS (2018) and the Research and Innovation Festival (2017) for his innovative work in electrical engineering. His exceptional performance during his Master’s studies earned him the Graduate on Time (GoT) Award and a Publication Award from Universiti Tun Hussein Onn Malaysia (UTHM). He was also a recipient of the prestigious UTHM Scholarship Award. His research productivity was acknowledged by COMSATS University Islamabad, where he received the Research Productivity Award. Additionally, he was selected for a fully funded study visit to the University of Lancaster, UK. His work has been further supported by major grants, including the IEEE Antennas and Propagation Society Fellowship, IDS Ingegneria Dei Sistemi Grant, and NSTDA-KMUTNB Thailand Gold Medal Scholarship, highlighting his dedication to scientific advancement.

Research Skill

Mr. Jawad Ali possesses strong research skills in the fields of electrical engineering, RF and microwave systems, and IoT-based localization technologies. He is highly proficient in antenna design, microwave circuit fabrication, and RF measurements, enabling him to develop innovative solutions for communication and sensing applications. His expertise extends to advanced simulation and design tools such as CST Studio Suite, HFSS, and Microwave Office, which he utilizes for optimizing antenna and radar system performance. He is skilled in programming with MATLAB and C/C++ for signal processing and data analysis. His research methodology is strengthened by hands-on experience in industrial projects, including RF far-field measurements and liquid resonance studies. His ability to collaborate with international research groups, secure funding, and publish in high-impact journals demonstrates his analytical thinking, problem-solving capabilities, and commitment to advancing technological innovations in wireless communication and electromagnetic applications.

Conclusion

Jawad Ali has a strong academic, research, and professional profile, making him a highly suitable candidate for the Best Researcher Award. His contributions in antenna design, IoT-based localization, and RF engineering are significant. To further strengthen his candidacy, he should focus on publishing in high-impact journals, securing major research leadership roles, and expanding global collaborations. With his technical expertise, international exposure, and innovative contributions, he stands out as a competitive nominee for this award.

Publications Top Noted

  1. Metasurface-Loaded Biodegradable Mobile Phone Back Cover for Enhanced Radiation Performance

    • Authors: Juin Acharjee, Jawad Ali, Muhammad Uzair, Thipamas Phakaew, Prayoot Akkaraekthalin, Yaowaret Maiket, Rungsima Yeetsorn, Suramate Chalermwisutkul
    • Year: 2025
    • DOI: 10.3390/ma18040730

  2. Low-Cost Indoor Localization Using Dual-Chip RFID Tag

    • Authors: Jawad Ali, Kamol Kaemarungsi, Thipamas Phakaew, Muhammad Uzair, Adam Narbudowicz, Suramate Chalermwisutkul
    • Year: 2024
    • DOI: 10.1109/OJAP.2024.3372030

  3. Enhancement of Radio Frequency Identification Coverage for Various Indoor Scenarios Using Diversified Radiation Patterns of Tag and Reader Antennas

  4. Dual-Chip RFID Tag for Enhanced Indoor Localization of IoT Assets

  5. Optimization of Planar Capacitive Sensors Embedded Between Two 6mm Thick Glass Sheets

  6. Post-Design Modifications for Impedance Matching of UHF RFID Tag Antenna

  7. Dual-Chip UHF RFID Tag Antenna for Distinction of Movement Directions

  8. Modeling and Design of Enhanced All Optical Signal Regeneration Technique

  9. Antenna Design Using UWB Configuration for GPR Scanning Applications

  10. Design a Compact Square Ring Patch Antenna with AMC for SAR Reduction in WBAN Applications

Yibo Ding | Engineering | Best Researcher Award

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Assoc.Prof.Dr.Yibo Ding | Engineering | Best Researcher Award

Associate professor atNorthwestern Polytechnical University, China

Dr. Yibo Ding is an Associate Professor at Northwestern Polytechnical University, specializing in aerospace guidance and control. With a Ph.D. in aeronautical and astronautical science from Harbin Institute of Technology, he has dedicated his research to cooperative game guidance and multi-constraint adaptive control of hypersonic vehicles. He has led over 20 research projects, including national-level initiatives, and collaborated with key aerospace institutions in China. His contributions include innovative guidance algorithms, high-precision self-learning control technologies, and the development of national standards. Dr. Ding has published over 30 academic papers, authored two books, and holds 12 patents. His research has been recognized by esteemed academicians and has had significant applications in aerospace engineering and defense technology. With multiple awards, editorial appointments, and international presentations, he stands out as a leading researcher in his field, making him a strong candidate for the Best Researcher Award.

Professional Profile

Education

Dr. Yibo Ding earned his B.S. degree in Aircraft Design and Engineering and his Ph.D. in Aeronautical and Astronautical Science and Technology from Harbin Institute of Technology, China, in 2015 and 2020, respectively. His academic training provided a strong foundation in aerospace engineering, with a focus on advanced guidance and control systems for hypersonic vehicles. His doctoral research emphasized intelligent cooperative game guidance and adaptive control, addressing key challenges in aerospace flight dynamics. With his rigorous education and specialized expertise, Dr. Ding has emerged as a leading researcher in aerospace engineering, contributing significantly to flight safety, optimal flight performance, and national defense technology.

Professional Experience

Since 2020, Dr. Yibo Ding has been serving as an Associate Professor at Northwestern Polytechnical University, Xi’an, China, where he is affiliated with the National Key Laboratory of Aerospace Flight Dynamics Technology. He is a core member of the “Innovation Team of Sanqin Special Support Program for Talents” and actively contributes to aerospace research and development. He holds various prestigious roles, including Director of the Shaanxi Vibration Engineering Society and an expert for the Xi’an Science and Technology Bureau. Recognized as a Young Top Talent under the Shaanxi Special Support Program, he has also been selected for the China Association for Science and Technology Young Talent Lift Project and the Northwest Polytechnical University Soaring Star Program. His research focuses on cooperative game guidance and multi-constraint adaptive control for hypersonic vehicles, aiming to enhance flight safety and optimize performance. Additionally, he collaborates closely with key aerospace research institutes, contributing to national defense projects and cutting-edge aerospace technology.

Research Interest

Dr. Yibo Ding’s research interests primarily focus on aerospace guidance and control, with a particular emphasis on cooperative game guidance and multi-constraint adaptive control for hypersonic vehicles. His work aims to enhance flight safety, optimize flight performance, and support the future development of aerospace aircraft technology. He specializes in intelligent cooperative game guidance under threat assessment, designing advanced algorithms that improve aircraft maneuverability in high-threat environments. Additionally, his research addresses critical challenges such as intake constraints, flight transient constraints, aerodynamic-propulsion coupling, and strong system uncertainties in hypersonic vehicles. By developing high-precision self-learning control technologies, including fixed-time anti-saturation compensation algorithms and adaptive parameter tuning methods, he contributes to ensuring stable and efficient aerospace flight dynamics. His research findings have significant applications in national defense and future aerospace missions, advancing the capabilities of next-generation aerospace vehicles.

Award and Honor

Dr. Yibo Ding has received several prestigious awards and honors in recognition of his outstanding contributions to aerospace research and innovation. He was selected as a Young Top Talent under the Shaanxi Special Support Program and was also recognized by the China Association for Science and Technology’s Young Talent Lift Project. Additionally, he was honored as a Soaring Star at Northwestern Polytechnical University. His research excellence has been acknowledged through the Excellent Paper Award at the China Commercial Space Summit Forum in 2023. He has also played a significant role in national defense projects, where his contributions were recognized at the national level for ensuring the successful execution of key aerospace missions. His work has received high praise from leading academicians and scholars, further solidifying his reputation as a distinguished researcher in aerospace guidance and control.

Conclusion

Given his strong research output, industry collaborations, patents, and contributions to aerospace engineering, Yibo Ding is a strong candidate for the Best Researcher Award. While he has areas for growth, particularly in international visibility and industry application, his achievements make him highly deserving of recognition in his field.

Publications Top Noted

  • Title: Prospective cohort studies underscore the association of abnormal glycemic measures with all-cause and cause-specific mortalities
    Authors: Juzhong Ke, Xiaonan Ruan, Wenbin Liu, Zhitao Li, Guangwen Cao
    Year: 2024
    Citations: 0
  • Title: Trends in disease burden and risk factors of asthma from 1990 to 2019 in Belt and Road Initiative countries: evidence from the Global Burden of Disease Study 2019
    Authors: Wenjing Ye, Xue Xu, Yibo Ding, Xiaopan Li, Wen Gu
    Year: 2024
    Citations: 0
  • Title: Smoke and Spike: Benzo[a]pyrene Enhances SARS-CoV-2 Infection by Boosting NR4A2-Induced ACE2 and TMPRSS2 Expression
    Authors: Wenbin Liu, Yue Zhao, Junyan Fan, Xiaojie Tan, Guangwen Cao
    Year: 2023
    Citations: 1
  • Title: Remote detection device for bioaerosol: research progress
    Authors: Letian Fang, Wenbin Liu, Yibo Ding, Guangwen Cao
    Year: 2023
    Citations: 0

Janani Priyanka Perumpally Rajakumar | Engineering | Best Researcher Award

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Ms. Janani Priyanka Perumpally Rajakumar | Engineering | Best Researcher Award

Student at Dong-A University, India

Janani Priyanka P.R. is a dedicated researcher specializing in civil and environmental engineering, with a strong academic background and expertise in air quality monitoring, data analysis, and smart city engineering. She has a passion for tackling environmental challenges using advanced technologies such as big data and IoT-based monitoring systems. With multiple Q1 journal publications and international conference presentations, she has demonstrated her ability to contribute impactful research. Her technical proficiency in Python, AutoCAD, C++, and Microsoft tools further enhances her analytical capabilities. She has received notable recognition, including an Editor’s Choice selection for one of her research papers and a Second Paper Award at ICTSCE 2023. She aspires to further her research in sustainable construction and urban planning, aiming to integrate technology and environmental solutions for smarter, safer cities.

Professional Profile

Education

Janani holds a Master’s degree in ICT Integrated Oceanfront Smart City Engineering from Dong-A University, Busan, South Korea, with an impressive GPA of 4.19/5. Her interdisciplinary education integrates architecture, civil, and electronic engineering, providing a comprehensive understanding of sustainable urban development. She previously earned a Bachelor of Technology in Civil Engineering from Adi Shankara Institute of Engineering and Technology, Kerala, India, graduating with an outstanding CGPA of 9.11/10. She ranked second in her department during her undergraduate studies, reflecting her academic excellence. Throughout her academic journey, she actively participated in research projects, technical conferences, and internships, which helped her develop expertise in environmental sustainability, air pollution control, and smart construction methodologies.

Professional Experience

Janani has gained valuable research and industry experience through various internships and projects. She interned at SFS Homes, Kakkanad, where she worked on an ongoing construction project, gaining hands-on experience in structural design and project management. Additionally, she completed an internship at the civil department of FACT Ltd., Eloor, where she explored industrial construction techniques and environmental safety protocols. She has actively participated in international conferences, including ICTSCE 2021 & 2023 and IEEE Big Data 2021, where she presented her research on particulate matter control and toxic gas monitoring. Her research on air pollution control in construction activities, toxic gas detection systems, and sustainable building practices has been widely recognized. With her technical skills in data analysis, programming, and engineering design, she is well-equipped to contribute to innovative solutions in urban development and environmental sustainability.

Research Interest

Janani Priyanka P.R.’s research focuses on air quality monitoring, environmental sustainability, and smart city engineering. She is particularly interested in developing data-driven solutions to address pollution control challenges in urban environments. Her studies explore big data analytics, IoT-based toxic gas monitoring, and particulate matter control measures in construction activities. She has conducted extensive research on real-time gas detection systems for worker safety and efficient air pollution mitigation strategies using advanced technologies. Her interdisciplinary approach integrates civil engineering, environmental science, and data analytics, making her work highly relevant to sustainable urban development. She aspires to further explore machine learning applications in air quality forecasting, climate-resilient infrastructure, and smart urban planning. By leveraging her technical skills in Python, C++, AutoCAD, and MS Project, she aims to contribute to innovative solutions that enhance environmental sustainability and public health in rapidly urbanizing regions.

Awards and Honors

Janani has received several prestigious awards and honors for her academic excellence and research contributions. She was awarded the Second Paper Award at ICTSCE 2023 in Busan, South Korea, recognizing her work in air pollution control and sustainable construction practices. Her research paper published in the Sensors Journal was selected as an Editor’s Choice Article, highlighting its significance in the field of toxic gas detection and worker safety. She has published three Q1 journal articles, a testament to the impact and quality of her research. Additionally, she ranked second in her undergraduate civil engineering department, showcasing her consistent academic excellence. Her Master’s thesis on toxic gas exposure detection received a remarkable score of 94 out of 100, further reinforcing her expertise in environmental monitoring systems. With multiple international conference presentations and impactful research publications, she continues to make significant contributions to sustainable urban engineering and environmental science.

Conclusion

Janani Priyanka P.R. is a strong contender for the Best Researcher Award, given her exceptional academic performance, Q1 publications, technical skills, and international recognition. However, further strengthening through a Ph.D., leadership in research, and interdisciplinary collaborations would enhance her profile further. If she continues on this trajectory, she has high potential to be an outstanding researcher in her field.

Publications Top Noted

  • Ham, Y.-B., Cheriyan, D., Kim, H.-U., Janani Priyanka, P.R., Choi, J.-H. (2024). “Particulate matter reduction efficiency analysis of sprinkler system as targeted control measures for construction activity.” Heliyon, 10(7), e27765.
    • Year: 2024
    • Citations: 0
  • Janani Priyanka, P.R., Cheriyan, D., Choi, J.-H. (2022). “A proactive approach to execute targeted particulate matter control measures for construction works.” Journal of Cleaner Production, 368, 133168.
    • Year: 2022
    • Citations: 5
  • Priyanka, J., Cheriyan, D., Choi, J.-H. (2021). “Issues with Current PM Monitoring Techniques and Control Measures and the Way Forward Using Big Data.” Proceedings – 2021 IEEE International Conference on Big Data (Big Data 2021), pp. 5997.
    • Year: 2021
    • Citations: 1