Ming-Peng Zhuo | Smart Textile | Best Researcher Award

Assoc Prof Dr. Ming-Peng Zhuo | Smart Textile | Best Researcher Award

Associate Professor, Soochow University, China

Ming-Peng Zhuo, born on February 15, 1990, in China, is currently an Associate Professor at Soochow University’s National Engineering Laboratory for Modern Silk and College of Textile and Clothing Engineering. With a solid background in materials science, he specializes in organic semiconductor materials and their optoelectronic applications. He has built a remarkable academic career, contributing significantly to the field through innovative research in nanomaterials and QLED technologies.

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Education 🎓

PhD in Materials Science & Engineering (2016-2019), Soochow University, Suzhou, China. Research focused on organic semiconductor materials and their optoelectronic application under Prof. Liang-Sheng Liao.

Master of Engineering in Materials Engineering (2014-2016), Nanchang University, China. Research centered on inorganic functional nanomaterials for energy and environmental applications under Prof. Wei-Fan Chen.

Bachelor of Science in Materials Physics (2010-2014), Nanchang University, China. Studied synthetic methodology for inorganic functional nanomaterials.

Experience 🏢

Ming-Peng Zhuo is currently an Associate Professor at Soochow University (since June 2022), where he works at the National Engineering Laboratory for Modern Silk and the College of Textile and Clothing Engineering. His role involves integrating cutting-edge research in nanomaterials and photonic applications into textile engineering, bridging traditional materials with modern technological advancements.

Before his current position, Zhuo served as a Postdoctoral Researcher at Soochow University from June 2019 to June 2022, working at the Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices. Under the supervision of renowned scholars Prof. Shuit-Tong Lee and Prof. Liang-Sheng Liao, he focused on the development of organic semiconductor materials. His postdoctoral work primarily centered on improving the performance and stability of organic devices, including OLEDs and QLEDs, contributing to advancements in carbon-based materials for optoelectronics and sustainable energy solutions.

Research Interests 🔬

Ming-Peng Zhuo’s research encompasses a broad range of topics within materials science and nanotechnology, with a particular focus on the precise self-assembly of organic micro-/nanostructures for advanced photonic applications. His work is notable for combining principles of chemistry, physics, and materials engineering to innovate in fields such as quantum dot light-emitting diodes (QLEDs), which hold promise for the next generation of display technologies due to their superior color purity and energy efficiency.

Zhuo is also deeply involved in the rational design of inorganic nanomaterials, where he develops materials with tailored properties for specific functions. His expertise extends into energy applications, where he explores how nanomaterials can be optimized for better energy storage, conversion, and harvesting systems. This includes photocatalysis, solar cells, and other technologies aimed at improving sustainability in energy consumption.

Furthermore, his research is applied to environmental challenges, leveraging nanotechnology to address pollution control and resource management. For example, he investigates the use of nanomaterials for water purification and air filtration, targeting the reduction of hazardous pollutants and enhancing environmental health.

Zhuo’s work often involves a highly interdisciplinary approach, merging concepts from nanophotonics, optoelectronics, and materials chemistry to push the boundaries of what’s possible in display technologies, sustainable energy solutions, and environmental remediation. His research is characterized by both experimental innovation and theoretical insights, contributing to the rapid advancement of nanoscience and its practical applications.

Awards 🏆

Recipient of various academic accolades for outstanding research in the field of materials science and engineering, especially in the development of quantum dot light-emitting diodes (QLEDs) and nanomaterials.

Publications Top Notes 📚

Zhuo, Ming-Peng, et al., Visualizing the interfacial-layer-based epitaxial growth process toward organic core-shell architectures, Nat. Commun., 2024, 15, 1130. Cited by 20. link

Zhuo, Ming-Peng, et al., Cascaded charge-transfer organic alloys for controlled hierarchical self-assembly, Matter, 2024, 7, 1. Cited by 15. link

Zhuo, Ming-Peng, et al., Vertical Phase-Engineering MoS2 Nanosheet Enhanced Textiles, ACS Nano, 2024, 18, 492-505. Cited by 10. link

Zhuo, Ming-Peng, et al., Hydrophilic 1T-WS2 Nanosheet Arrays for Hydroelectric Generation, Small, 2024, 2308527. Cited by 8. link

Zhuo, Ming-Peng, et al., Organic Bilayer Heterostructures with Built-In Exciton Conversion, Adv. Mater., 2023, 2306541. Cited by 25. link

 

 

 

 

Saike Yang | Energy | Best Researcher Award

Dr. Saike Yang | Energy | Best Researcher Award

Postdoctoral researcher, State Grid Hebei Electric Power Research Institute, State Grid Hebei Electric Power Supply Co., Ltd., China

Dr. Saike Yang is a dedicated postdoctoral researcher at the State Grid Hebei Electric Power Research Institute, where his work focuses on enhancing the safety and reliability of power systems. With a strong academic foundation and innovative research in power cable insulation detection, Dr. Yang is making significant contributions to the field of electrical engineering.

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Education 🎓

Dr. Saike Yang was born in Hebei, China, in 1995. He earned his B.Sc. degree from North China Electric Power University in Baoding in 2017. He furthered his education by obtaining a Ph.D. from Xi’an Jiaotong University in 2022, where he specialized in power cable insulation testing and developed novel methodologies for non-destructive testing.

Experience 🛠️

Dr. Yang began his research career at the 54th Research Institute of China Electronic Technology Group Corporation from October 2022 to July 2023. He is currently a postdoctoral researcher at the State Grid Hebei Electric Power Co., Ltd., and Xi’an Jiaotong University. His experience in both academic and industrial research environments equips him with a unique perspective on the practical applications of his work.

Research Interests 🔍

Dr. Yang’s research interests lie in the field of power cable insulation detection. His work primarily focuses on developing advanced non-destructive testing methods to improve the safety and reliability of electrical power systems. His innovations include new voltage generators and fault detection technologies that minimize damage to power cables during testing.

Awards 🏆

Dr. Yang’s contributions to the field have been recognized through various awards and honors. His work on power cable insulation has garnered attention for its practical applications and significant impact on the reliability of electrical systems.

Publications Top Notes 📚

S. Yang, H. Li, P. Xu, et al. (2021). A Novel DAC Generator for PD Testing of MV Cable Insulation. IEEE Transactions on Power Delivery, 36(1), 499-501. Cited by: 50 articles. link

S. Yang, L. Wang, X. Guo, et al. (2021). Implementation of a Novel Very Low Frequency Cosine-Rectangular Voltage Generator for Insulation Testing of Power Cables. IEEE Transactions on Power Electronics, 36(7), 7679-7692. Cited by: 65 articles. link

S. Yang, K. Zhao, L. Wang, et al. (2021). Development of the Accurate Localization of Partial Discharges in Medium-Voltage XLPE Cables Based on Pulse Reconstruction. IET Generation, Transmission & Distribution, 16(2), 193-203. Cited by: 30 articles. link

S. Yang, X. Yue, J. Chen, et al. (2022). A Method to Improve the Efficiency of Onsite Damped AC Test of Medium-Voltage Cables. IEEE Transactions on Power Delivery, 37(4), 3424-3427. Cited by: 40 articles. link

S. Yang, T. Li, X. Pang, et al. (2024). A Nondestructive High-Resistance Fault Diagnosis Method of XLPE Medium Voltage Cables Based on Chirp-TDR. Measurement, 235, 1-10. Cited by: 10 articles. link

 

 

 

 

 

Mohsen Choubani | Nanostructures | Best Researcher Award

Assoc Prof Dr. Mohsen Choubani | Nanostructures | Best Researcher Award

Associate professor, Scientific Faculty of Monastir, Unversity of Monastir, Tunisia

Mohsen Choubani is an Associate Professor of Physics at the Scientific Faculty of Monastir (F.S.M), Tunisia, specializing in Micro-Opto-Electronic and Nanostructures. Born on September 17, 1971, in Mahdia, Tunisia, he has dedicated over 27 years to education and research. Choubani is married with four children and actively contributes to academic and scientific communities.

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Education 🎓  

Mohsen Choubani is an Associate Professor of Physics at F.S.M, Tunisia. He earned his Ph.D. in Physics in April 2011 with the distinction of “Very Honorable” from the Faculty of Sciences of Tunis. Prior to that, he completed a Thorough Studies Diploma (DEA) in Physics in December 1997 with a “Pretty Good” distinction at F.S.M, Tunisia. He also holds a Mastery in Physics, awarded in July 1995 with a “Pretty Good/Quite” distinction from the same institution. Mohsen began his academic journey with a Baccalaureate in Experimental Science, which he received in June 1991 from the High School of Ksour-essef, Mahdia.

Professional Experience 💼

Mohsen Choubani has a diverse and extensive teaching career. Since September 2022, he has been serving as an Associate Professor at the Faculty of Sciences of Monastir (F.S.M), Tunisia. Prior to this role, he was an Assistant Professor at F.S.M from September 2012 to July 2022, following his time as a Higher Education Assistant in September 2010. His career in education began as a Secondary School Teacher, a position he held from September 1997 to 2010. In addition to his full-time roles, Mohsen has experience as a Part-Time Teacher at both the Higher Institute of Computer Science of Mahdia (2006-2007) and F.S.M (1996-1997).

Research Interests 🔬

Modeling and Optimization of Non-linear Optical Properties in Quantum Dots, Quantum Rings, and Nano-Holes

The exploration of non-linear optical properties in quantum systems like quantum dots, quantum rings, and nano-holes (droplets) is pivotal for advancing photonics and optoelectronics. These quantum structures exhibit unique behaviors under varying electromagnetic fields, enabling the manipulation of light at the nanoscale. Modeling these properties involves complex computational techniques to optimize their performance in various applications, such as quantum computing, high-resolution imaging, and ultrafast communication technologies. By understanding and optimizing the interactions within these nanostructures, researchers can develop innovative solutions for next-generation optical devices.

Electromagnetic Modeling of Non-homogeneous Planar Structures, Photonic Crystals, and Electronic Transport through Semiconductor Barriers

In the realm of electromagnetic modeling, non-homogeneous planar structures, photonic crystals, and semiconductor barriers are critical components that shape the behavior of light and electronic transport at the microscopic level. Non-homogeneous planar structures, with their varying material properties, influence wave propagation in ways that can be harnessed for novel optical devices. Photonic crystals, with their periodic structures, allow for the control of light in unprecedented ways, leading to the development of highly efficient waveguides, sensors, and filters. Furthermore, understanding electronic transport through semiconductor barriers is essential for designing advanced electronic and optoelectronic components, including transistors, diodes, and quantum devices. Through meticulous modeling and analysis, these elements contribute to the cutting-edge development of technologies that rely on precise electromagnetic interactions.

Awards 🏆

Numerous acknowledgments for contributions to physics education and research

Publications Top Notes 📚

Benzerroug, N., & Choubani, M. (2024). Effects of hills, morphology, electromagnetic fields, temperature, pressure, and aluminum concentration on the second harmonic generation of GaAs/AlxGa1-xAs elliptical quantum rings. Results in Physics, 63, 107883. (Cited by: 1) link

Choubani, M., & Benzerroug, N. (2024). Design of a frequency multiplier based on laterally coupled quantum dots for optoelectronic device applications in the Tera-Hertz domain: Impact of inhomogeneous indium distribution, strains, pressure, temperature, and electric field. Journal of Electronic Materials, 53(25). (Cited by: 1) link

Benzerroug, N., Makhlouf, D., & Choubani, M. (2023). Pressure, temperature, and electric field effects on linear and nonlinear optical properties in InxGa1-xAs/GaAs strained quantum dots: under indium segregation and In/Ga intermixing phenomena. Physica B, 658, 414819. (Cited by: 3) link

Makhlouf, D., Benzerroug, N., & Choubani, M. (2023). Tailoring of the Nonlinear Optical Rectification in vertically and laterally coupled InxGa1-xAs/GaAs quantum dots for Tera-hertz applications: under In/Ga inter-diffusion, indium segregation, and strains effects. Results in Physics, 48, 106457. (Cited by: 2) link

Choubani, M., Maaref, H., & Saidi, F. (2022). Linear, third-order nonlinear and total absorption coefficients of a coupled InAs/GaAs lens-shaped core/shell quantum dots in terahertz region. European Physical Journal Plus, 137, 265. (Cited by: 5) link

 

 

 

 

 

Xiaochun Li | Biomedical | Best Researcher Award

Prof Dr. Xiaochun Li | Biomedical | Best Researcher Award

Associate Dean, Taiyuan University of Technology, China

Dr. Xiaochun Li is a Professor at the Department of Biomedical Engineering, TaiYuan University of Technology, Shanxi, China. With an extensive background in biomedical sensors and analytical chemistry, Dr. Li has made significant contributions to the field through innovative research and teaching. He has received multiple awards for his work, including the Second Prize of the Shanxi Provincial Natural Science Award and recognition as the “2021 Annual Science and Technology Innovation Person.” His research focuses on developing cutting-edge technologies for disease diagnosis and public health.

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Education 🎓

Dr. Xiaochun Li earned his Ph.D. in Biomedical Engineering, specializing in analytical chemistry and sensor technology. His educational journey laid a strong foundation for his future research and academic career, leading to his current position as a professor at TaiYuan University of Technology.

Experience 🧑‍🏫

Professor, TaiYuan University of Technology, Shanxi, China (2014-present): Leading research in biomedical sensors and analytical chemistry.

Associate Professor, TaiYuan University of Technology, Shanxi, China (2009-2014): Conducted advanced research and taught various courses.

Assistant Professor, TaiYuan University of Technology, Shanxi, China (2007-2009): Initiated his academic career, focusing on innovative research in biomedical engineering.

Research Interests 🔬

Dr. Xiaochun Li’s research interests encompass the development of biomedical sensors, optical fluorescence detection technologies, and AI-enhanced biochemical sensing. His work is particularly focused on creating innovative diagnostic tools for early disease detection and public health applications.

Awards 🏆

Second Prize of Shanxi Provincial Natural Science Award (2022)

Outstanding Science and Technology Worker of China Society of Electronics (2019)

Silver Prize of National Science and Technology Workers’ Innovation and Entrepreneurship Competition (2016)

Young Outstanding Talents of Shanxi Province “Three Jin Talents” (2018)

2021 Annual Science and Technology Innovation Person (2022)

Publications Top Notes 📚

Zhang, L. L., Xu, P. T., Li, X. C., Yang, Z. H., Yu, H.-Z.. (2024). Blu-ray disc technology-enabled portable imaging system for immunoassay quantitation. Sens. Actuat. B-Chem., 419, 136376. Cited by 15 articles. link

Wang, C. X., Deng, R., Li, H. Q., Liu, Z. G., Niu, X. F., Li, X. C.. (2024). An integrated magnetic separation enzyme-linked colorimetric sensing platform for field detection of Escherichia coli O157: H7 in food. Microchimica Acta, 191, 454. Cited by 10 articles. link

Li, H. Q., Xu, H., Li, Y. L., Li, X. C.*. (2024). Application of artificial intelligence (AI)-enhanced biochemical sensing in molecular diagnosis and imaging analysis: Advancing and challenges. Trac-Trend. Anal. Chem., 174, 117700. Cited by 12 articles. link

Gao, X. G., Yuan, L., Xue, C. Z., Zhang, X. L., Meng, X. J., Li, X. C.*. (2024). Bubbles-induced porous structure-based flexible piezoresistive sensors for speech recognition. ACS Appl. Mater. Interfaces, 16(7), 9532-9543. Cited by 8 articles. link

L.Y, Gao, X.G., Kang, R.R., Zhang, X.L., Meng, X.J., Li, X. C., Li, X.J.* (2024). Flexible strain sensors based on an interlayer synergistic effect of nanomaterials for continuous and non-invasive blood pressure monitoring. ACS Appl. Mater. Interfaces, 16(10), 10435-10444. Cited by 6 articles. link

 

 

 

 

 

Selma Ben Ftima | Hydraulics | Best Researcher Award

Dr. Selma Ben Ftima | Hydraulics | Best Researcher Award

Doctor, UCLM, Spain

Dr. Selma Ben Ftima is a distinguished Industrial Electronics Engineer specializing in robotics and control systems. With a robust background in neural-network modeling and fractional-order control, she has made significant contributions to the field of robotics, particularly in the adaptive control of flexible link robots. Her innovative research has been published in several high-impact journals, earning her recognition within the scientific community.

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Education 🎓

Dr. Selma Ben Ftima is a dedicated researcher with a strong academic background in robotics and intelligent systems. She recently completed her Ph.D. in Robotics at the University of Castilla-La Mancha, Spain (Dec 2019 – Feb 2024), where her thesis focused on “Algebraic Identification and Adaptive Fractional-Order Control Applied to Very Lightweight Flexible Link Robots.” This work highlights her expertise in advanced control systems and robotics, particularly in the context of lightweight and flexible robotic structures.

Prior to her doctoral studies, Selma earned a Master of Science in Intelligent and Communicating Systems from the National Engineering School of Sousse, Tunisia (Oct 2017 – Jun 2018), specializing in Embedded Systems. Her academic journey began with a Diploma in Electronic Engineering with Honors from the same institution (Sep 2014 – Oct 2017), also specializing in Embedded Systems. Her educational background reflects a strong foundation in electronics and embedded systems, combined with specialized knowledge in robotics and control systems.

Experience 🛠️

Selma Ben Ftima has also gained valuable professional and teaching experience during her academic journey. She served as a University Teaching Assistant at the University of Sousse, Tunisia (Jan 2020 – Jun 2020), where she conducted laboratory sessions in signal processing and embedded systems. In this role, she focused on setting up experimental platforms and grading, providing hands-on learning experiences for students.

Before her teaching role, Selma worked as an Electrical Engineer at Rovex, Tunisia (Mar 2019 – Dec 2019). In this position, she coordinated electrical upgrades and managed supplier relations, ensuring the smooth operation of showroom equipment. Her ability to oversee technical upgrades and maintain essential equipment demonstrates her practical engineering skills.

During her time at the National Engineering School of Sousse, Tunisia (Sep 2014 – Jan 2017), Selma led various academic projects and internships. These included the development of a line-following robot and biometric facial recognition systems, showcasing her ability to apply theoretical knowledge to real-world challenges.

Research Interests 🔬

Dr. Ftima’s research interests lie in the fields of robotics, control systems, and signal processing. She focuses on the development of robust, optimal, and adaptive control systems for flexible link robots, fractional-order calculus, and neural-network-based modeling. Her work also extends to the practical implementation of these systems using advanced tools like MATLAB, LabVIEW, and NI hardware.

Awards 🏆

Dr. Ftima has consistently demonstrated academic excellence throughout her education and career. While she is still in the early stages of her professional journey, her work has been recognized through publications in peer-reviewed journals, showcasing her potential for future accolades in robotics and industrial electronics.

Publications Top Notes 📝

2024 . Modeling of an Irrigation Main Canal Pool Based on a Narx-Ann System Identification, Communications in Nonlinear Science and Numerical Simulation Cited by: 10 articles. link

2023 . Estimación Algebraica Robusta en Tiempo Real de la Frecuencia Natural y el Retardo de un Robot Flexible Teleoperado, XLIV Jornadas de Automática Cited by: 8 articles. link

2023. Fractional Modeling and Control of Lightweight 1-DOF Flexible Robots Robust to Sensor Disturbances and Payload Changes, Fractal and Fractional Cited by: 15 articles. link

2022. A Fast Online Estimator of the Main Vibration Mode of Mechanisms from a Biased Slightly Damped Signal, IEEE Industrial Electronics Society Cited by: 12 articles. link

2021. Fractional Control of a Lightweight Single Link Flexible Robot Robust to Strain Gauge Sensor Disturbances and Payload Changes, Actuators Cited by: 20 articles. link

 

 

 

 

 

 

 

Shishir Priyadarshi | Space Physics | Best Researcher Award

Dr. Shishir Priyadarshi | Space Physics | Best Researcher Award

Technical Lead-ML-GNSS Engineer, GMV NSL, United Kingdom

Dr. Shishir Priyadarshi is an experienced engineer specializing in Machine Learning (ML) and Global Navigation Satellite Systems (GNSS) at GMV, UK. With over a decade of experience, he has significantly contributed to various ESA projects aimed at enhancing the accuracy and resilience of GNSS through innovative ML algorithms. His work spans multiple international research projects and academic appointments, reflecting a deep commitment to advancing space science and technology.

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Education 🎓

Dr. Shishir Priyadarshi earned his Ph.D. in Space Physics (Geophysics) from the Space Research Centre in Warsaw, Poland, in 2014. His thesis, titled “B-spline model of ionospheric scintillation,” was supervised by Professor Andrzej Wernik. Prior to this, he completed his Master of Science (M.Sc.) in Physics, specializing in Electronics and Radio Physics, at Banaras Hindu University in Varanasi, India, in 2009. His master’s thesis was titled “GPS-Based Measurement of TEC and Its Variability Over Ground Station Varanasi, India.”

Experience 💼

Dr. Shishir Priyadarshi currently serves as an ML-GNSS Engineer and Technical Lead at GMV in Nottingham, UK, since February 2022. In this role, he spearheads the development and validation of machine learning techniques for resilient time provisioning in ESA NAVISP projects, with a particular focus on ionospheric GNSS modeling and the detection of GNSS signal interference. Prior to this, he was a Research Associate at the University of Bath, UK, from February 2021 to January 2022, where he contributed to research on ionospheric modeling and ML applications in GNSS. From November 2019 to January 2021, Dr. Priyadarshi worked as a Postdoctoral Researcher at SUSTech in Shenzhen, China, focusing on ionospheric data assimilation and GNSS signal processing. He also served as an Adjunct at the University of Wroclaw, Poland, from July 2018 to June 2019, concentrating on atmospheric research and ionospheric scintillation. From June 2015 to May 2018, he was a Postdoctoral Research Scientist at the Institute of Space Sciences, Shandong University in Weihai, China, where he investigated the coupling of atmospheric layers and GNSS signal propagation. His earlier role as a Space Physicist (Postdoc) at the Space Research Centre in Warsaw, Poland, from August 2014 to May 2015, involved researching the effects of ionospheric disturbances on GNSS signals. As a Marie-Curie Fellow (Early-Stage Researcher) from August 2011 to July 2014 at the Space Research Centre in Warsaw, he developed models for ionospheric scintillation and its impact on satellite communications. Dr. Priyadarshi began his career as a Junior Research Fellow at the Atmospheric Research Laboratory of Banaras Hindu University in Varanasi, India, from August 2009 to 2011, where he studied ionospheric perturbations using GPS data.

Research Interests 🔬

Dr. Shishir Priyadarshi focuses on Magnetosphere-Ionosphere-Thermosphere (MIT) Coupling, exploring how the interactions between various atmospheric layers influence Global Navigation Satellite System (GNSS) signals. His work in Ionospheric Scintillation involves modeling and predicting the responses of ionospheric scintillation to various space weather phenomena. To enhance the accuracy and integrity of GNSS signals, Dr. Priyadarshi employs advanced machine learning (ML) and artificial intelligence (AI) algorithms in GNSS Signal Processing. Additionally, he leverages ML, recurrent neural networks (RNN), and AI to provide real-time Space Weather Nowcasting/Forecasting. His expertise extends to the development of ML-based algorithms for Jamming and Spoofing Detection, which aim to identify and mitigate interference in GNSS signals.

Awards and Achievements 🏆

URSI Young Scientist Award (2017), Montreal, Canada

Young Scientist Award (2014), Space Research Centre, Poland

Marie-Curie Fellow (2011-2014), European Commission

IAPT Award (2006), Indian Association of Physics Teachers

Sadbhavana Club U.P. Award (2003), Indian Government

Publications Top Notes 📚

Priyadarshi, S. (2023). Machine Learning-based ionospheric modelling performance during high ionospheric activity, Acta-Geophysica, cited by 15 articles. link

Priyadarshi, S. (2023). Fast and reliable forecasting for satellite clock bias correction with transformer deep learning, Radio-Science, Space Weather, cited by 30 articles. link

Priyadarshi, S. (2020). Near-Earth plasma-sheet cumulative magnetic, American Geoscience Union (AGU), cited by 10 articles.

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Mohammad Hemmatinafar | Exercise Physiology | Corporate Research Leadership Award

Assoc Prof Dr. Mohammad Hemmatinafar | Exercise Physiology | Corporate Research Leadership Award

Faculty Member, Shiraz University, Iran

Dr. Mohammad Hemmatinafar is a distinguished expert in Sport Physiology, with a Ph.D. from the University of Tehran. With over 30 published journal articles, he has significantly contributed to understanding the physiological adaptations in athletes, particularly through dietary supplements and exercise intensity. Fluent in English and equipped with extensive research and teaching experience, Dr. Hemmatinafar continues to advance knowledge in sports science, with a particular interest in the impact of nutrition and exercise on cardiac health.

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Education 🎓

Dr. Mohammad Hemmatinafar holds a Doctor of Philosophy in Sport Physiology from the University of Tehran, where he graduated with a GPA of 18.74/20.00 in 2015. His doctoral research focused on “The Impact of Exercise Intensity on Cardiac Regenerative Capacity in Rats with Myocardial Infarction,” under the supervision of Dr. Abbas Ali Gaeini, with Dr. Mohammadreza Kordi as his advisor. Prior to this, he earned his Master of Science in Sport Physiology from the same university in 2012, achieving a GPA of 18.86/20.00. His master’s project, supervised by Dr. Mohammadreza Kordi, examined “The Impact of Six Weeks of High-Intensity Interval Training (HIIT) on Fibrinolytic and Inflammatory Factors in Sedentary Young Men.” Dr. Hemmatinafar completed his Bachelor of Science in Physical Education and Sports Science at the University of Mohaghegh Ardabili in 2010, with a GPA of 18.33/20.00.

Experience 💼

Dr. Hemmatinafar has more than seven years of experience in academic research and teaching, focusing on the physiological aspects of sports and exercise. His work primarily explores the effects of dietary supplements, exercise intensity, and training regimens on athletic performance and cardiac health. His extensive research background is supported by his leadership in multiple studies and his contribution to over 30 peer-reviewed publications.

Research Interests 🔬

Dietary Supplements: Investigating the impact of caffeine, beetroot juice, proteins, and sports drinks on athletic performance and physiological adaptations.

Exercise and Diet: Exploring the effects of various diets, such as ketogenic diets, on athletes’ performance.

Cardiac Adaptations: Studying the molecular, structural, and functional adaptations of the heart in response to exercise.

Awards 🏅

Dr. Hemmatinafar has been recognized for his outstanding academic performance throughout his educational journey, including ranking 1st in his Master’s and Bachelor’s programs. His research contributions have also garnered significant attention in the field of sport physiology.

Publications Top Notes 📚

Niknam, Alireza, et al. (2024) “Low and high doses of espresso coffee improve repeated sprint performance and eye-hand coordination following fatigue status in male basketball players.” Current Developments in Nutrition: 104427. Link

Ahmadpour, Alireza, et al. (2024) “Consuming Beetroot Juice Improves Slalom Performance and Reduces Muscle Soreness in Alpine Skiers Under Hypoxic Conditions.” Current Developments in Nutrition: 104408. Link

Imanian, Babak, et al. (2024) “The effect of probiotics and casein supplementation on aerobic capacity parameters of male soccer players.” Journal of the International Society of Sports Nutrition 21, no. 1: 2382165. Link

Farmani, Azam, et al. (2024) “The effect of repeated coffee mouth rinsing and caffeinated gum consumption on aerobic capacity and explosive power of table tennis players.” Journal of the International Society of Sports Nutrition 21, no. 1: 2340556. Link

Safa, Ghazal, et al. (2024) “Effect of off-season iron supplementation on aerobic capacity of female handball player.” Current Developments in Nutrition: 103767. Link

 

 

 

 

 

 

Birhanu Gizaw | Applied microbiology | Best Researcher Award

Mr. Birhanu Gizaw | Applied microbiology | Best Researcher Award

Researcher, EBI, Ethiopia

🌟 Birhanu Gizaw is a dedicated microbiologist with over two decades of experience in teaching and research. Currently, he serves as a Researcher I at the Ethiopian Biodiversity Institute, specializing in microbial biodiversity. Birhanu is pursuing a Ph.D. in Applied Microbiology at Addis Ababa University, bringing a wealth of knowledge and expertise to the field of microbiology.

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Education 🎓

Birhanu Gizaw is an accomplished scholar in the field of microbiology, currently pursuing his Ph.D. in Applied Microbiology at Addis Ababa University (2019-2023). He has a strong academic foundation with a Master of Science in Applied Microbiology from Addis Ababa University (2008-2010) and a Bachelor of Science in Biology from BirDar University. Birhanu also holds a Diploma in Biology from Kotebe College. His extensive educational background reflects his dedication to advancing his knowledge and expertise in microbiology.

Experience 👨‍🏫

Birhanu Gizaw is a dedicated and experienced microbiologist with a comprehensive educational background and extensive professional experience. He is currently a Ph.D. candidate in Applied Microbiology at Addis Ababa University (2019-2023). He holds a Master of Science in Applied Microbiology (2008-2010) from the same university and a Bachelor of Science in Biology from BirDar University. Additionally, he earned a Diploma in Biology from Kotebe College.

With ten years of teaching experience in various high schools and colleges, Birhanu has honed his pedagogical skills and has positively impacted many students’ academic journeys.

🔬 Research Experience: Birhanu has an impressive eleven-year tenure at the Ethiopian Biodiversity Institute (2004-2016), where he made significant contributions to microbial biodiversity research. His work at the institute highlights his commitment to advancing scientific understanding in this crucial field.

📊 Training: Birhanu is proficient in several essential tools and software, including DIV-GIS, R-Stat, SPSS, and basic computer skills, which enable him to effectively analyze and interpret complex data sets.

Overall, Birhanu Gizaw’s blend of academic achievements, teaching experience, and research expertise make him a valuable asset to the field of microbiology.

Research Interests 🧫

Birhanu’s research interests encompass microbial biodiversity, applied microbiology, and environmental microbiology. He is particularly focused on microbial applications in agriculture, bioremediation, and biofertilizers.

Awards 🏅

Birhanu has been recognized for his contributions to microbiology and biodiversity through various accolades and grants, including a project grant from the Ethiopian Ministry of Innovation and Science.

Publications Top Notes 📚

Isolation and biochemical characterization of Plant Growth Promoting (PGP) bacteria colonizing the rhizosphere of Tef crop during the seedling stage.Birhanu Gizaw, Genene Tefera,Journal of Plant Science and Phytopathology.  link 

Health benefits of probiotics.  Birhanu Gizaw, Zerihun Tsegay, J Bacteriol Infec Dis. link

Phosphate solubilizing fungi isolated and characterized from Teff rhizosphere soil collected from North Showa zone, Ethiopia.Birhanu Gizaw, Zerihun Tsegay, African Journal of Microbiology Research. link

Traditional knowledge on teff (Eragrostis tef) farming practice and role of crop rotation to enrich plant growth promoting microbes for soil fertility in East Showa: Ethiopia.Birhanu Gizaw, Genene Tefera ZerihunTsegay, Agric. Res. Technol. link

Concept, principle and application of biological control and their role in sustainable plant diseases management strategies. B Gizaw, E Abatenh, Int. J. Res. Stud. Biosci. link

 

 

 

 

Yudan Yuan | supercapacitor | Best Researcher Award

Dr. Yudan Yuan | Supercapacitor | Best Researcher Award

Lecturer, Suzhou Vocational Institute of Industrial Technology, China

Dr. Yuan Yudan is a dedicated researcher and lecturer at Suzhou Vocational Institute of Industrial Technology. With a strong academic background and significant contributions to the field of supercapacitors and integrated circuit technology, Dr. Yuan has established a notable presence in the scientific community. His innovative work on biomass-based supercapacitors has garnered widespread recognition, including multiple publications and patents.

Profile

scopus

Education 🎓 

📘 Dr. Yuan Yudan obtained his Master’s degree in Microelectronics and Solid State Electronics from Fudan University in 2011. He later pursued a PhD in Electronic Science and Technology from Xi’an Jiaotong University, which he completed in 2022, focusing on the development of supercapacitors.

Experience 💼 

After completing his PhD, Dr. Yuan joined Suzhou Vocational Institute of Industrial Technology. His career includes leading and participating in various provincial and municipal research projects. In 2023, he was selected for the prestigious Jiangsu Provincial “Science and Technology Deputy Director” Program.

Research Interests 🔬

Dr. Yuan’s research interests lie in the fields of supercapacitors and integrated circuit technology. He focuses on the activation modification of electrode materials for biomass-based supercapacitors, aiming to develop cost-effective and environmentally friendly solutions.

Awards 🏆

Dr. Yuan has received several accolades, including his selection for the Jiangsu Provincial “Science and Technology Deputy Director” Program in 2023. His research has also been highlighted through multiple authorized invention patents.

Publications Top Notes 📚

Yuan Yudan, Sun Yi, Liu Chenguang, Yang Li, Zhao Cezhou, “Hierarchical Porous Activated Carbon Derived from Pleurotus Eryngii and the Influence of Pore Structural Parameters on Capacitance Performance,” Coatings, 2024, 14, 840. DOI: 10.3390/coatings14070840. link

Yuan Yudan, Sun Yi, Liu Chenguang, Yang Li, Zhao Cezhou, “Influence of KHCO3 Activation on Characteristics of Biomass-Derived Carbons for Supercapacitor,” Coatings, 2023, 13, 1236. DOI: 10.3390/coatings13071236. Cited by: Journal of Coatings. link

Yudan Yuan, Yi Sun, Zhichen Feng, et al., “Nitrogen-Doped Hierarchical Porous Activated Carbon Derived from Paddy for High-Performance Supercapacitors,” Materials, 2021, 14(2), 318. DOI: 10.3390/ma14020318. Cited by: Journal of Materials. link

Yudan Yuan, Ruowei Yi, Yi Sun, et al., “Porous Activated Carbons Derived from Pleurotus eryngii for Supercapacitor Applications,” Journal of Nanomaterials, 2018, 7539509. DOI: 10.1155/2018/7539509. Cited by: Journal of Nanomaterials. link

 

 

 

 

Taye Mengistu | Machine learning | Best Researcher Award

Mr. Taye Mengistu | Machine learning | Best Researcher Award

IT engineer, Jigjiga University, Ethiopia

Mr. Taye Mengistu is an innovative researcher and lecturer based at Jigjiga University, Ethiopia. With a strong foundation in computer science and information technology, he is making notable strides in applying machine learning to real-world challenges. His pioneering work includes utilizing ensemble convolutional neural networks (CNNs) for the classification of mango diseases, a significant advancement in agricultural technology aimed at enhancing crop health and productivity.

Profile

Google Scholar

Education 🎓

Mr. Taye Mengistu holds a Master’s degree in Computer Science from Jimma University, Ethiopia, where he graduated in January 2022 with a GPA of 3.58. Prior to this, he completed his Bachelor’s degree in Information Technology at Jigjiga University, Ethiopia, graduating in July 2017 with a GPA of 3.84. His strong academic background underscores his deep understanding and expertise in his field.

Experience 🏢

Mr. Taye Mengistu has been serving as a Lecturer at Jigjiga University, Ethiopia, since October 2017. With over five years of experience, he has played a crucial role in both teaching and research. His responsibilities include delivering lectures, supervising student projects, and conducting research in various domains. His tenure at the university reflects his dedication to academic excellence and his ongoing commitment to advancing knowledge in his field.

Research Interests 🔬

Classification of Mango Disease Using Ensemble Convolutional Neural Network

The classification of mango diseases using ensemble convolutional neural networks (CNNs) represents a cutting-edge research area at the intersection of agriculture and artificial intelligence. This research focuses on leveraging advanced machine learning techniques to accurately identify and categorize diseases affecting mango crops, which is crucial for improving agricultural productivity and sustainability.

Key Aspects of Research Interests:

Ensemble Convolutional Neural Networks (CNNs): Utilizing ensemble methods to combine multiple CNN models to enhance classification accuracy. This approach improves the robustness and reliability of disease detection systems by aggregating predictions from different models.

Disease Classification: Developing algorithms to classify various mango diseases based on visual symptoms captured in images. Accurate classification helps in timely diagnosis and effective management strategies, minimizing crop loss and ensuring better yield.

Image Processing and Analysis: Applying image processing techniques to preprocess and analyze mango leaf and fruit images. This includes noise reduction, feature extraction, and image augmentation to improve model performance.

Machine Learning in Agriculture: Exploring the application of machine learning models to agricultural problems, particularly in disease detection and management. This research aims to bridge the gap between AI technology and practical agricultural needs.

Sustainable Agriculture: Enhancing disease management practices to promote sustainable agriculture. By accurately classifying and managing diseases, farmers can reduce the reliance on chemical treatments, leading to more eco-friendly farming practices.

Awards 🏆

Certification in HDP, Jigjiga University (May 2022) – Recognized for his advanced skills and knowledge in his field.

Publications 📚

Classification of mango disease using ensemble convolutional neural networkJSmart Agricultural Technology 2024. link