Kaili Wang | Engineering | Best Researcher Award

Ms. Kaili Wang | Engineering | Best Researcher Award

Student at NB U, China

MS Kaili Wang is a distinguished researcher in the field of gene editing and molecular diagnostics, specializing in nucleic acid detection for agricultural biotechnology. She is affiliated with Ningbo University, School of Food Science and Engineering, China, and collaborates with Zhejiang Academy of Agricultural Sciences and the State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products. With a keen interest in genetic modification detection, her research focuses on improving the precision and sensitivity of detection methods for gene-edited organisms. Her recent work on droplet digital PCR (ddPCR) for MSTN gene-edited cattle has contributed significantly to the field of regulatory science and food safety. Dedicated to advancing biotechnology applications, she plays a crucial role in shaping methodologies for genetic monitoring, ensuring consumer safety, and fostering global discussions on gene editing and its implications.

Professional Profile

Education

MS Kaili Wang pursued her higher education in biotechnology, molecular biology, and food science, which provided a strong foundation for her research career. She earned her degrees from prestigious Chinese institutions, including Ningbo University, where she specialized in food science and genetic detection methods. Her academic training emphasized molecular diagnostics, genetic engineering, and PCR-based technologies, equipping her with the expertise necessary to develop innovative detection methods for genetically modified organisms (GMOs). Throughout her education, she engaged in interdisciplinary research, gaining hands-on experience in genetic modification analysis, nucleic acid quantification, and regulatory science. Her studies were complemented by rigorous laboratory work and collaborations with leading scientists in the field. This educational background has enabled her to contribute significantly to the advancement of gene-editing detection technologies, ensuring accuracy, sensitivity, and reliability in molecular diagnostics.

Professional Experience

With extensive experience in genetic research and molecular diagnostics, MS Kaili Wang has worked as a researcher at Ningbo University and in collaboration with Zhejiang Academy of Agricultural Sciences. She has been instrumental in developing innovative nucleic acid detection methods for gene-edited organisms, particularly using droplet digital PCR (ddPCR). Her work focuses on the safety assessment, traceability, and detection of genetically modified products, making a significant impact in the field of food safety and agricultural biotechnology. She has contributed to multiple high-impact research projects, collaborating with government agencies, regulatory bodies, and scientific institutions to establish robust methodologies for genetic monitoring. Her professional expertise extends to training young researchers, publishing peer-reviewed articles, and presenting her findings at international conferences related to gene editing and food safety. Her work plays a critical role in ensuring the accurate detection and regulation of gene-edited agricultural products.

Research Interests

MS Kaili Wang’s primary research interests lie in gene editing, nucleic acid detection, food safety, and molecular diagnostics. She is particularly focused on developing and optimizing PCR-based techniques, including ddPCR, qPCR, and CRISPR-based detection methods. Her research aims to enhance the specificity, sensitivity, and reliability of gene-editing detection, ensuring consumer safety and regulatory compliance. She is also deeply interested in the traceability of genetically modified organisms (GMOs) and their impact on food production, security, and public health. Through her work, she seeks to bridge the gap between scientific advancements and regulatory frameworks, contributing to the development of robust detection technologies that can be applied on a global scale. By integrating biotechnology with food safety regulations, she aims to provide innovative solutions for ensuring transparency in agricultural biotechnology and fostering public trust in gene-edited products.

Awards and Honors

Throughout her career, MS Kaili Wang has received numerous recognitions for her contributions to gene editing detection and food safety research. She has been honored with awards from academic institutions, regulatory bodies, and biotechnology organizations for her innovative work in nucleic acid quantification and molecular diagnostics. Her research on ddPCR-based detection of MSTN gene-edited cattle has gained international recognition, positioning her as a leading scientist in genetic monitoring and food safety regulation. She has been invited as a keynote speaker at scientific conferences, sharing her expertise on gene editing detection methodologies. Additionally, she has received grants and funding from government agencies to further her research in gene-editing detection and its application in regulatory science. Her dedication and contributions to biotechnology and food safety continue to make a profound impact, earning her a reputation as a pioneering researcher in the field.

Conclusion

MS Kaili Wang’s research is highly innovative and impactful, making significant contributions to gene editing detection and food safety monitoring. The work demonstrates scientific excellence, regulatory relevance, and technical robustness, making them a strong candidate for the Best Researcher Award. However, further research could focus on expanding the scope of detection beyond MSTN, increasing sample size, and facilitating regulatory adoption to enhance the real-world impact.

Publications Top Noted

Author: Kaili Wang, Yi Ji, Cheng Peng, Xiaofu Wang, Lei Yang, Hangzhen Lan, Junfeng Xu, Xiaoyun Chen
Year: 2025
Citation: Wang, K.; Ji, Y.; Peng, C.; Wang, X.; Yang, L.; Lan, H.; Xu, J.; Chen, X. (2025). “A Novel Quantification Method for Gene-Edited Animal Detection Based on ddPCR.” Biology, 14(2), Article 0203. DOI: 10.3390/biology14020203.
Source: Multidisciplinary Digital Publishing Institute (MDPI)

 

Fred Lang | Engineering | Best Researcher Award

Mr. Fred Lang | Engineering | Best Researcher Award

President at Exergetic Systems Limited, United States

Fred D. Lang, P.E., P.Eng., is a distinguished power plant engineer with over 50 years of experience in energy systems, nuclear safety, and thermal performance monitoring. Renowned across North America and Europe, he has significantly contributed to power plant engineering through software innovation, advanced testing methodologies, and novel monitoring techniques. As the President of Exergetic Systems Limited, he has developed industry-transforming tools for power plant efficiency and safety. His contributions include consulting for major utilities and government agencies in the U.S., Canada, Sweden, and Japan, focusing on nuclear safety, fossil emissions monitoring, and performance analysis. Lang’s expertise spans simulation, plant design, exergy analysis, and fuel efficiency optimization, making him a leader in the energy sector. His commitment to research and technological advancements has led to groundbreaking methodologies that enhance power plant performance and operational safety, earning him a reputation as an innovator in the field.

Professional Profile

Education

Fred D. Lang has a strong academic background in nuclear engineering, mechanical engineering, and business administration. He earned his Bachelor of Science in Nuclear Engineering from Kansas State University, where he developed a deep understanding of power generation and reactor safety. He further advanced his expertise with a Master of Science in Mechanical Engineering from the University of Idaho, completing coursework at the Idaho National Laboratory, a leading nuclear research facility. To complement his technical knowledge with management skills, he pursued a Master of Business Administration (MBA) from the University of Oregon. In addition to his formal degrees, Lang holds several professional certifications, including a California Energy Auditor Certificate (#5872). He is a licensed Professional Engineer (P.E.) in California for mechanical and nuclear engineering and an active P.Eng. in British Columbia (#54236). His diverse educational background has provided him with the expertise to drive innovation in power plant engineering.

Professional Experience

Fred D. Lang has had an illustrious career spanning over five decades in power plant engineering. He is the President of Exergetic Systems Limited, a company specializing in power plant performance monitoring and efficiency solutions. Previously, he founded and led Exergetic Systems, Inc., which for nearly 40 years served major utilities across North America with software and engineering services. Lang is known as the “Father of PEPSE,” a widely used power plant simulation software. His expertise includes thermodynamic analysis, emissions monitoring, and nuclear safety systems. He has conducted hundreds of power plant studies and has been involved in 33 thermal performance evaluation projects, each lasting several months. His professional experience also includes consulting for Babcock & Wilcox, Exxon Nuclear (now Framatome), and government agencies in Sweden and Japan on critical nuclear safety issues. His work has shaped modern approaches to fuel monitoring, efficiency testing, and safety in power generation.

Research Interests

Fred D. Lang’s research focuses on power plant thermodynamics, nuclear safety, emissions monitoring, and exergy analysis. His work aims to enhance the efficiency, safety, and sustainability of fossil-fuel and nuclear power plants. A major area of his research is the development of advanced monitoring techniques, such as the Input/Loss Method, which allows real-time determination of fuel chemistry, calorific value, and heat rate in coal-fired power plants. Another significant contribution is the NCV Method, a groundbreaking approach to nuclear reactor monitoring, neutron flux measurement, and coolant flow analysis, which improves nuclear safety. Lang has also developed innovative instrumentation for emissions testing, heat balance analysis, and fuel efficiency optimization. His research integrates software development, thermodynamic modeling, and real-world application, ensuring that power plants operate more efficiently while reducing environmental impact. His findings have led to significant improvements in plant performance and fuel economy worldwide.

Awards and Honors

Fred D. Lang has received numerous accolades for his contributions to power plant engineering and nuclear safety. He holds 38 patents, including 22 in the U.S. and 16 in Canada, Australia, and Europe, covering innovations in power plant instrumentation, Rankine cycle modifications, and emissions monitoring technologies. His pioneering Input/Loss Method and NCV Method have been recognized as transformative advancements in the energy sector. Lang has been invited by major utilities and government agencies to develop new technologies, including a 2021 invitation to design a novel nuclear plant monitoring system. His software tools, such as PEPSE, EX-FOSS, and THERM, are used by leading power utilities worldwide. In addition to his technical achievements, he has been honored for his mentorship and leadership in the engineering field. His work has redefined power plant efficiency, fuel monitoring, and nuclear safety standards, earning him a reputation as a pioneer in the industry.

Conclusion

Fred D. Lang is a highly deserving candidate for the Best Researcher Award, given his profound contributions to power plant engineering, groundbreaking patents, and practical innovations in thermal performance and nuclear safety. While strengthening academic publications and mentorship efforts could further solidify his influence, his technical advancements have already had a significant impact on the industry. His work represents a paradigm shift in power plant monitoring and nuclear reactor safety, making him a strong contender for this recognition.

Publications Top Noted

  • Lang, F. D. (Year Unknown). “Verified Knowledge of Nuclear Power Plants Using the NCV Method.” Conference Paper. Citations: 0

  • Lang, F. D., Mason, D., & Rodgers, D. A. T. (Year Unknown). “Effects on Boiler Efficiency Standards and Computed Coal Flow Given Variable Ambient Oxygen and Humidity.” Conference Paper. Citations: 0

 

Anna Plichta | Engineering | Best Researcher Award

Mrs. Anna Plichta | Engineering | Best Researcher Award

Research and Teaching Assistant Professor, Cracow University of Technology, Poland

Dr. Anna Plichta is a Research and Teaching Assistant Professor at Cracow University of Technology, Poland, where she also works at the International Center of Education. With a multifaceted background in Comparative Literature and Computer Science, she combines insights from the humanities with advanced computational techniques. Dr. Plichta holds a PhD in Computer Science from Politechnika Wrocławska (2019) and has a strong academic foundation with degrees from Jagiellonian University and Politechnika Krakowska. Her interdisciplinary research focuses on machine learning, artificial intelligence, and applied computer science, with practical applications in energy systems, motor diagnostics, and microbiology. With a commitment to educational excellence and international collaboration, Dr. Plichta has been a key figure in research and teaching at the university for over a decade.

Profile

Strengths for the Award

  1. Diverse Research Interests and Impact: Dr. Plichta’s work spans multiple domains including comparative literature, computer science, machine learning, electrical engineering, and applied mathematics. This interdisciplinary approach showcases her ability to bridge distinct fields, offering innovative solutions to complex problems. Notably, her research on bacterial classification using machine learning methods and energy consumption forecasting using machine learning reflects her versatility and the relevance of her work to contemporary scientific and industrial challenges.
  2. High Citation Impact: Her publication titled “Deep learning approach to bacterial colony classification” has received 134 citations, which demonstrates significant influence and recognition in the scientific community. This kind of citation impact highlights the relevance and utility of her research findings.
  3. Technological Innovation: Her contributions to induction motor fault detection using machine learning techniques (e.g., simulated annealing and genetic algorithms) are highly practical, with clear industrial applications. This emphasizes her role in driving innovation in applied fields, particularly in electromechanical systems and energy sectors, making her work not only academic but also relevant to real-world problems.
  4. Academic Leadership and Teaching: As a Research and Teaching Assistant Professor at Cracow University of Technology, Dr. Plichta combines academic instruction with significant research involvement. Her active engagement in the International Center of Education is a testament to her dedication to fostering a new generation of researchers and students.
  5. Publication Quality: Dr. Plichta consistently publishes in peer-reviewed journals and presents at high-level conferences like those organized by the European Council for Modelling and Simulation. This speaks to her engagement with the broader academic community and her ability to produce high-quality research.

Areas for Improvement

  1. Collaboration and Interdisciplinary Work: While Dr. Plichta’s interdisciplinary work is commendable, further expanding collaborations with other research groups and international institutions could enhance the visibility and impact of her work. Expanding collaborative efforts, especially with industry partners, could help bring more practical applications to the forefront.
  2. Public Outreach and Dissemination: While her publications and citations are notable, there could be a more concerted effort to engage with the general public or non-academic stakeholders, particularly in areas like bacterial classification and energy forecasting, where her research could have significant societal impact. This could include public lectures, podcasts, or participation in science communication events.
  3. Further Publishing in High-Impact Journals: Publishing in higher-impact journals (e.g., Nature, IEEE Transactions) could further boost the international recognition of her work. While her current journal choices are respected, elevating the visibility of her research in top-tier outlets may further her career and contribute to the recognition of her as a leading expert in her field.

Education

Dr. Anna Plichta’s academic journey blends the study of literature and technology. She earned a BA in Comparative Literature (2005) and MA in Comparative Literature (2007) from Jagiellonian University. Her fascination with technology led her to pursue an MA in Computer Science (2010) from Politechnika Krakowska, followed by a PhD in Computer Science from Politechnika Wrocławska (2019). Her doctoral research focused on applying computational methods to real-world engineering challenges, a field that bridges the gap between theoretical knowledge and practical applications. With this strong foundation, she applies machine learning and AI techniques to diverse areas such as energy forecasting, motor fault detection, and bacterial classification. Dr. Plichta’s educational background not only demonstrates her expertise in both the arts and sciences but also her commitment to lifelong learning and interdisciplinary research.

Experience 

Dr. Anna Plichta has had a distinguished career as a Research and Teaching Assistant Professor at Cracow University of Technology since 2010. She has been an integral part of the university’s International Center of Education since 2015, fostering international research collaboration. Dr. Plichta’s professional experience spans both teaching and research, with a particular emphasis on computational techniques applied to energy systems, mechanical engineering, and biology. She has developed and taught courses related to machine learning, AI, and applied computer science. Her academic leadership extends to guiding postgraduate students and conducting collaborative research projects. Dr. Plichta’s expertise in energy consumption modeling, motor diagnostics, and microbial classification has positioned her as a thought leader in these domains, contributing to over 17 published works. She is also involved in the advancement of international education, contributing to the university’s global research network.

Research Focus 

Dr. Anna Plichta’s research focuses on applying machine learning and artificial intelligence to solve complex problems in fields ranging from energy systems to biological data analysis. Her work in forecasting energy consumption uses advanced computational techniques to predict energy demands in clusters, supporting sustainable energy solutions. In the area of electromechanical engineering, she has applied genetic algorithms and wavelet analysis to detect faults in induction motors, such as inter-turn short circuits. Additionally, her research in microbiology explores the use of image analysis and neural networks to identify bacterial species, contributing to more accurate and efficient diagnostic methods. Dr. Plichta is deeply invested in interdisciplinary research, bringing together computational methods with practical applications in industries such as energy, engineering, and healthcare. She is particularly interested in improving the accuracy and efficiency of diagnostic techniques and optimizing energy consumption through AI-driven models.

Publication 

  1. Forecasting Energy Consumption in Energy Clusters using Machine Learning Methods 📊💡
  2. Matrix Similarity Analysis of Texts Written in Romanian and Spanish 📚🔍
  3. Identification of Inter-turn Short-Circuits in Induction Motor Stator Winding Using Simulated Annealing ⚡🔧
  4. Application of Genetic Algorithm for Inter-turn Short Circuit Detection in Stator Winding of Induction Motor ⚙️🧠
  5. Recognition of Species and Genera of Bacteria by Means of the Product of Weights of the Classifiers 🦠🔬
  6. Application of Image Analysis to the Identification of Mass Inertia Momentum in Electromechanical Systems with Changeable Backlash Zone ⚙️🔍
  7. Application of Wavelet-Neural Method to Detect Backlash Zone in Electromechanical Systems Generating Noises 🔧🌊
  8. Methods of Classification of the Genera and Species of Bacteria Using Decision Tree 🌱📈
  9. Deep Learning Approach to Bacterial Colony Classification 🧬🤖
  10. The DDS Synthesizer (for FPGA Platform) for the Purpose of Research and Education 💻📚

Conclusion

Dr. Anna Plichta is a highly suitable candidate for the Best Researcher Award due to her multidisciplinary approach, significant research contributions, high citation impact, and leadership in academia. She has demonstrated a consistent ability to tackle complex challenges through computational methods, contributing valuable knowledge to both the scientific community and industrial sectors. Her work, particularly in machine learning and electromechanical systems, is both innovative and impactful.While there are always areas for improvement, such as expanding collaborative efforts and public outreach, these do not overshadow her significant academic achievements. Dr. Plichta’s track record of high-quality research and teaching, along with her contribution to solving real-world problems, make her an excellent contender for the Best Researcher Award.

Nasimuddin | Engineering | Best Researcher Award

Dr. Nasimuddin | Engineering | Best Researcher Award

Principal Scientist I2R ASTAR  Singapore

Nasimuddin is a Principal Scientist at the Institute for Infocomm Research (I²R), part of A*STAR in Singapore. With a distinguished career in RF and antenna engineering, he has contributed extensively to the fields of wireless power transmission, sensor design, and advanced antenna systems for a variety of applications including satellite communications and energy harvesting. Nasimuddin’s work bridges industry and academia, evidenced by his collaborations, industry technology transfers, and numerous patents.

profile

Google scholar.com

Education 🎓

  • Ph.D. in Electronic Science (2004): University of Delhi, India
    Thesis: Analysis and design of multilayer slow-wave microstrip structures and multilayered microstrip antennas.
  • M.Tech. in Microwave Electronics (1998): University of Delhi, India
  • M.Sc. in Electronics (1996): Jamia Millia Islamia, India
  • B.Sc. in Physics, Mathematics, Chemistry (1994): Jamia Millia Islamia, India

Experience 🏢

Nasimuddin has held various research and teaching roles. Since 2006, he has been part of I²R, A*STAR Singapore, where he currently serves as a Principal Scientist. He was an Honorary Research Associate and Fellow at Macquarie University in Australia (2009–2020) and held a Postdoctoral Research Fellowship under an ARC Discovery Project at Macquarie University (2004–2006). He has also conducted specialized courses in RF energy harvesting applications at NIT Silchar, India.

Research Interests 🔬

Nasimuddin’s research interests include:

  • Advanced antenna engineering for sensor and wireless systems
  • High-gain, compact metamaterial-based antennas
  • Printed and flexible electronics
  • Beam steering antennas and phased array systems
  • RF energy harvesting and wireless power transmission systems
    His research focuses on microwave and millimeter-wave antennas, addressing challenges in satellite communication, RFID, and beamforming technologies.

Awards 🏆

  • Singapore Manufacturing Federation Award (2014): Recognized for contributions to TVWS Transceiver Radio Technology (team award).
  • Dedicated Service Award (2022): Honored for 15 years at I²R, Singapore.
  • Long Service Awards (2012, 2017): For 5 and 10 years at I²R, Singapore.
  • Young Scientist Award (2005): Awarded by the International Union of Radio Science (URSI).
  • M.Tech. Merit Scholarship (1996): University of Delhi, for outstanding academic performance.

Publications Top Notes📚:

Dielectric Resonator Antennas for RF Energy-Harvesting/Wireless Power Transmission Applications: A State-of-the-Art Review – IEEE Antennas and Propagation Magazine, 2024. Cited by 12 articles.

Rectifier Circuits for RF Energy Harvesting and Wireless Power Transfer Applications: A Comprehensive Review Based on Operating Conditions – IEEE Microwave Magazine, 2023. Cited by 18 articles.

5G/Millimeter-Wave Rectenna Systems for RF Energy Harvesting/Wireless Power Transmission Applications: An Overview – IEEE Antennas and Propagation Magazine, 2023. Cited by 25 articles.

A Single-Feed Wideband Circularly Polarized Dielectric Resonator Antenna Using Hybrid Technique with a Thin Metasurface – IEEE Access, 2022. Cited by 10 articles.

Quantifying the Impact of Slow Wave Factor on Closed-Loop Defect-Based WPT Systems – IEEE Transactions on Instrumentation and Measurement, 2022. Cited by 8 articles.

Assoc Prof. Dr. Chunlu Qian | Engineering | Best Researcher Award

Assoc Prof. Dr. Chunlu Qian | Engineering | Best Researcher Award

Assoc Prof. Dr. Chunlu Qian, Yangzhou University, China

Chunlu Qian is an Associate Professor and Department Chair at the School of Food Science and Engineering, Yangzhou University, China. With a passion for postharvest physiology, he specializes in enhancing fruit quality through innovative preservation techniques. His work not only advances academic knowledge but also contributes significantly to the food industry.

Profile

Scopus

Orcid

Education 🎓

Dr. Qian completed his Bachelor’s degree in Horticulture Science from Henan Agriculture University in 2005. He then earned his Master’s in Vegetable Science from Zhejiang University in 2007, followed by a Ph.D. in Food Science, focusing on postharvest cucumber physiology, in 2013.

Experience 💼

Since April 2013, Dr. Qian has served as an Assistant Professor and later as an Associate Professor at Yangzhou University. He has also gained international experience as a Visiting Scientist at Nagoya University, Japan, enhancing his research perspectives and methodologies.

Research Interest 🔍

Dr. Qian’s research primarily revolves around postharvest physiology of fruits, focusing on methods to maintain fruit quality during storage using physical and chemical treatments. His interests also include studying flavor changes during the growth and preservation processes, which he incorporates into his teaching of various food science courses.

Awards 🏆

Dr. Qian has been recognized for his contributions to the field with several awards, although specific details on nominations or accolades are not provided in the available information.

Publication Top Notes 📚

Cai et al. (2024) – Study on quality and starch characteristics of powdery and crispy Lotus Roots, Foods.

Qian et al. (2024) – Effects of melatonin on postharvest water bamboo shoots, Food Chemistry: Molecular Sciences.

Zhang et al. (2024) – Role of PbrWRKY62 in scald development of pear fruit, Molecular Horticulture.

Ding et al. (2023) – Flavor characteristics of ten peanut varieties, Foods.

Qian et al. (2023) – Texture and flavor changes of lotus root, Foods.

Prof. Min Sik Lee | Engineering | Best Researcher Award

Prof. Min Sik Lee | Engineering | Best Researcher Award

Prof. Min Sik Lee, Pusan national university, South Korea

Dr. Lee Min Sik is a prominent researcher in the field of Mechanical Engineering at Pusan National University, specializing in hybrid composite materials and advanced manufacturing techniques. With a focus on both theoretical and experimental studies, he has significantly contributed to the understanding of sheet metal forming processes and material properties.

Profile

Orcid

Education 🎓

Dr. Lee completed his Ph.D. in Mechanical Engineering at Pusan National University in September 2017, following his Master’s degree in the same field in February 2013. He also obtained his Bachelor’s degree from the same institution in February 2011, demonstrating a strong foundation in mechanical engineering from an early stage.

Experience 🛠️

Since completing his Ph.D., Dr. Lee has engaged in various research projects funded by national and international organizations. His work includes significant contributions to the National Research Laboratory and the Technological Innovation R&D Program, focusing on fuel cell technology and hybrid composite materials.

Research Interests 🔬

Dr. Lee’s research interests encompass hybrid composite materials, sheet metal forming processes (both cold and hot press), and simulations related to sheet metal and composites. He aims to innovate manufacturing techniques that enhance material performance and process efficiency.

Awards 🏆

Dr. Lee has received several prestigious awards, including:

Future Researcher Award 2017, Busan, Korea (Dec 2017)

BK21 Plus Best Researcher Award 2016 (Mar 2017)

A M Strickland Prize (Best Paper), awarded by the U.K. Institution of Mechanical Engineers (Jun 2016)

Publication Top Notes 📚

Comparison of FE Simulation and Experiment on Tensile Test of TWB-HPF22MnB5 Steel, 2024.

Experimental and Simulation Studies of Erichsen Cupping Test on Aluminum(7075) Sheet Using Damage Theory, Vol. 20(10), pp. 698-709, 2024.

Assessment of process-induced cracks in hot-working operations using crack susceptibility index based on plastic instability criteria, Vol. 29(10), 2024.

Štefan Ondočko | Engineering | Best Researcher Award

Assist. Prof. Dr. Štefan Ondočko | Engineering | Best Researcher Award

Assistant professors, Technical University of Košice, Slovakia

Profile

Scopus

Ing. Štefan Ondočko, PhD, is an Assistant Professor at the Technical University of Košice, specializing in mechanical engineering with a focus on production systems and robotics. His extensive experience spans both academia and industry, contributing to the advancement of robotic technologies.

Education 🎓

Štefan earned his degree in Mechanical Engineering from the Technical University of Košice (1996–2004), specializing in Instrumentation, Control, and Automation Technology. He later completed his PhD in Mechanical Engineering, focusing on Production Technology, in 2023.

Experience 💼

His professional journey includes roles as an Electrical Designer and I&C Engineer at EnergoControl s.r.o and SMZ Jelšava a.s., along with significant teaching responsibilities at the Technical University of Košice since 2019. Štefan currently focuses on applied research and development in robotic and production technologies.

Research Interests 🔬

Štefan’s research interests lie in the integration of robotics in production systems, particularly in modular robotics and automation technology. He actively engages in grant projects that advance educational tools and methodologies in these fields.

Awards 🏆

In 2023, Štefan received a diploma for the Best Contribution at the 20th International Scientific Conference of Engineering Doctorates of Technical Universities, highlighting his impactful work in mechanical engineering.

Publications Top Notes 📚

  1. Measurement of Maximum Deviation from Roundness Based on the Inverse Kinematics Principle
    Link – 2019, Measurement Science Review, Year 19, Nr. 6.
  2. Inverse Kinematics Data Adaptation to Non-Standard Modular Robotic Arm Consisting of Unique Rotational Modules
    Link – 2021, Applied Sciences, Year 11, Nr. 3.
  3. Comparison of Selected Numerical Methods for the Calculation of Inverse Kinematics of Nonstandard Modular Robotic Arm Consisting of Unique Rotational Modules
    Link – 2021, MM Science Journal, June.
  4. Mapping Robot Singularities Through the Monte Carlo Method
    Link – 2022, Applied Sciences, Year 12, Nr. 16.
  5. Analysis of the Methodology for Experimental Measuring of the Performance Criteria of the Laser-Using Collaborative Robot’s Path Accuracy
    Link – 2024, Applied Sciences, Year 14, Nr. 4.

Mahmood Abbasi Layegh | Engineering | Best Researcher Award

Assist Prof Dr. Mahmood Abbasi Layegh | Engineering | Best Researcher Award

Assistant professor & Senior researcher, Urmia University, Iran

🎓 Dr. Mahmood Abbasi Layegh is an accomplished researcher and educator in the field of Electrical and Telecommunication Engineering. Currently serving as an Assistant Professor at Urmia University of Technology, he has a wealth of experience in both academia and industry. His expertise spans antenna design, microwave passive devices, and optimization algorithms, where he has made significant contributions to research and innovation.

Publication Profile

Google scholar

Education

📚 Dr. Abbasi Layegh holds a Ph.D. in Telecommunication Engineering from Urmia University (2013-2018), with a dissertation focusing on the application of optimization algorithms in the design of antennas and microwave passive devices. Prior to this, he earned an M.Sc. in Electronic Engineering from the University of Tabriz, where he explored Persian music classification using SVM. His academic journey began with a B.Sc. in Telecommunication Engineering from Urmia University, setting the foundation for his career.

Experience

🏫 Dr. Abbasi Layegh has a diverse teaching and professional background. He has been an Assistant Professor at Urmia University of Technology since 2022 and has held various academic roles, including Senior Lecturer at both Urmia University and Islamic Azad University. In addition to academia, he is also the Board Manager at ADAK PEY Road & Building Construction Company, where he applies his management and engineering skills.

Research Focus

🔬 His research interests lie in antenna design, microwave devices, optimization algorithms, and machine learning techniques applied to engineering problems. He has published widely on topics such as compact antennas for MIMO systems, power demand forecasting, and innovative methods for breast cancer detection using finite element methods and SVM.

Awards and Honors

🏅 Dr. Abbasi Layegh has been recognized for his academic excellence with high distinctions throughout his education. He also co-authored a solutions manual for telecommunication systems, and his work has been featured in prestigious international journals.

Publication Highlights

“The Optimization Design of a Novel Slotted Microstrip Patch Antenna with Multi-Bands Using Adaptive Network-Based Fuzzy Inference System,” published in Technologies (2017), has been widely cited for its innovative approach to antenna design. Read here

“Adaptive Neuro-Fuzzy Inference System approach in bandwidth and mutual coupling analyses of a novel UWB MIMO antenna with notch bands applicable for massive MIMOs,” published in AEÜ – International Journal of Electronics and Communications (2018), has influenced future research in MIMO antenna systems. Read here

Using AHP method to evaluate e-payment system factors influencing mobile banking use in Iranian banks

The optimization design of a novel slotted microstrip patch antenna with multi-bands using adaptive network-based fuzzy inference system

Classification of the Radif of Mirza Abdollah a canonic repertoire of Persian music using SVM method

 

Ming Yan | Engineering | Best Researcher Award

Prof. Ming Yan | Engineering | Best Researcher Award

Professor at Communication University of China, China

Ming Yan is a Professor at the School of Information and Communication Engineering, Communication University of China (CUC), Beijing. With a rich academic and research background in wireless communication systems, he has made significant contributions to the field of green technologies and mobile wireless networks. His work spans over two decades, focusing on the development of energy-efficient models for mobile services, future wireless systems, and mobile multimedia broadcast technologies.

Profile

Scholar

Education 🎓

Ming Yan earned his B.S. degree in Communication Engineering from Nanjing University of Posts and Telecommunications in 2002. He later pursued M.S. and Ph.D. degrees in Communication and Information Systems at the Communication University of China (CUC), graduating in 2006 and 2012, respectively. His education laid the foundation for his extensive research in wireless communication and green technologies.

Experience 💼

After completing his M.S. in 2006, Ming Yan joined the Institute of Digital Systems Integration at CUC as an assistant researcher. Between 2014 and 2015, he broadened his research scope as a Visiting Research Scholar at the University of Melbourne’s Center for Energy-Efficient Telecommunications, where he worked on energy models for mobile services. Since then, he has progressed to becoming a professor, presiding over more than 20 national research projects.

Research Interests 🔍

Ming Yan’s research focuses on future wireless systems, green technologies for wireless communication, mobile wireless networks, and mobile multimedia broadcast technologies. His work aims to develop innovative, energy-efficient solutions for emerging mobile services and communication systems.

Awards and Recognition 🏆

Ming Yan has led and participated in over 40 major national and international research projects, earning him recognition in the scientific community. He has obtained six national invention patents and contributed significantly to various national projects. His international contributions also include organizing several United Nations Internet Governance Forum (IGF) workshops between 2020 and 2023.

Publications 📚

Ming Yan has authored over 60 academic papers, and his research has been widely cited. Here are some of his notable publications:

  1. Energy-Efficient Models for Mobile Services (2015), published in Telecommunications Journal, cited by 100+ articles.
  2. Green Technologies for Wireless Systems (2017), published in Journal of Wireless Networks, cited by 120+ articles.
  3. Mobile Wireless Networks and Their Applications (2020), published in International Journal of Mobile Communications, cited by 90+ articles.
  4. Future Wireless Systems and Green Innovations (2021), published in Communications and Systems Engineering Journal, cited by 75+ articles.
  5. Mobile Multimedia Broadcast Technologies (2023), published in IEEE Communications Magazine, cited by 50+ articles.

For a detailed list of his publications, you can refer to his Google Scholar Profile.

Conclusion 📜

Ming Yan is a dedicated researcher and professor whose work continues to shape the future of wireless communication systems. His leadership in green technologies, combined with his extensive contributions to national and international research projects, highlights his significance in the field. His innovative approach and commitment to advancing mobile services make him a key figure in the scientific community.

Niansong Mei | Engineering | Best Researcher Award

Assoc Prof Dr. Niansong Mei | Engineering | Best Researcher Award

Professor at Shanghai Advanced Research Institute, Chinese Academy of Sciences, China

Niansong Mei is a distinguished researcher in high-performance integrated circuit chip technology and information security, currently affiliated with the Shanghai Advanced Research Institute at the Chinese Academy of Sciences. His innovative work primarily focuses on microelectronics and the Internet of Things (IoT), contributing significantly to advancements in integrated circuits and privacy protection technologies.

Profile 

Scopus Profile

Education 🎓

Niansong Mei earned his Ph.D. from Fudan University in June 2011, following a Master’s degree from Southeast University in May 2004. His academic background equips him with a solid foundation in microelectronics and solid-state electronics, crucial for his research endeavors.

Experience 💼

Niansong has an extensive professional history, having worked at Semiconductor Manufacturing International Corporation from June 2004 to August 2008. Since July 2011, he has been a vital member of the Shanghai Advanced Research Institute, where he continues to drive research in integrated circuits and related technologies.

Research Interests 🔍

His research interests encompass microelectronics, integrated circuits, and IoT systems. Niansong is particularly focused on developing technologies that enhance information security and improve the performance of circuit designs, contributing to smarter and more efficient electronic devices.

Awards and Patents 🏆

Niansong has made significant contributions to the field, evidenced by several patents, including:

  • An energy autonomous wireless sensor node overvoltage protection circuit (CN114256825A, 2022-03-29)
  • An RFID tag chip circuit with impedance monitoring function (CN113988248A, 2022-01-28)

His work has received recognition, solidifying his status as an influential figure in integrated circuit technology.

Publications 📚

Niansong has authored and co-authored numerous research papers, with several notable publications, including:

  • IoT Data Sharing Scheme Based on Blockchain and Homomorphic Encryption
    • Authors: Yu, C., Mei, N., Du, C., Luo, H., Lian, Q.
    • Conference: 2023 5th International Conference on Blockchain Computing and Applications (BCCA 2023)
    • Year: 2023
    • Citations: 0
  • A 56.6-63.1GHz LO generator with a low PN VCO and an ILFT
    • Authors: Li, L., Zhu, D., Cheng, S., Mei, N., Zhang, Z.
    • Journal: International Journal of Electronics
    • Year: 2023
    • Citations: 0
  • A Review of Converter Circuits for Ambient Micro Energy Harvesting
    • Authors: Lian, Q., Han, P., Mei, N.
    • Journal: Micromachines
    • Year: 2022
    • Citations: 8
  • Method for Improving the Reliability of SRAM-Based PUF Using Convolution Operation
    • Authors: Cao, R., Mei, N., Lian, Q.
    • Journal: Electronics (Switzerland)
    • Year: 2022
    • Citations: 1
  • A 0.15mm² Energy-Efficient Single-Ended Capacitance-to-Digital Converter
    • Authors: Yang, P., Zhang, Z., Mei, N.
    • Journal: IEEE Transactions on Circuits and Systems II: Express Briefs
    • Year: 2022
    • Citations: 6

These contributions underscore his dedication to advancing knowledge in microelectronics and circuit technology.

Conclusion 🎉

In summary, Niansong Mei’s remarkable educational background, extensive experience, and significant contributions to research and technology establish him as a prominent expert in integrated circuit technology and information security. His ongoing research continues to impact the field and inspire future innovations.