Hen Friman | Biotechnology | Best Researcher Award

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Hen Friman | Biotechnology | Best Researcher Award

Dr. Hen Friman, Faculty of Engineering H.I.T – Holon Institute Of Technology, Israel

Dr. Hen Friman ๐ŸŽ“ is a dedicated lecturer at the Holon Institute of Technology (HIT) in Israel, specializing in energy systems and biotechnology. With a Ph.D. in Biology and Life Sciences from Bar-Ilan University ๐Ÿ”ฌ, Dr. Friman has made significant contributions to sustainable energy through bio-fuel cell research. He serves as Head of the Renewable Energy and Smart Grid Excellence Center โšก and actively manages national training programs in collaboration with Israel’s Ministry of Energy. His leadership in academic advising, student retention, and ecological projects reflects his commitment to education, innovation, and public service ๐ŸŒฑ๐Ÿ“˜.

Profile :

๐ŸŽ“Education & Experience :

Dr. Hen Friman ๐ŸŽ“ began his academic journey with a B.Sc. in Chemical Engineering and Biotechnology from Ariel University (with honors) in 2004 ๐Ÿงช. He continued with an M.Sc. in Biology and Life Sciences at Bar-Ilan University in 2007 ๐Ÿงฌ, followed by a Ph.D. in Biology and Life Sciences from the same institution in 2013 ๐Ÿ”‹. His doctoral research focused on energy generation from aromatic-compound-degrading bacteria using bio-fuel cells, under the guidance of Prof. Yeshayahu Nitzan and Dr. Rivka Cahan ๐Ÿ‘จโ€๐Ÿซ. Professionally, Dr. Friman joined the Holon Institute of Technology (HIT) in 2012 as a Junior Lecturer ๐Ÿ“… and has served as a Lecturer in the Faculty of Electrical and Electronics Engineering since 2015 ๐ŸŽ“. He held the role of Acting Head of the Undergraduate Program in 2022โ€“2023 ๐Ÿ‘จโ€๐Ÿซ and is currently the Academic Advisor for Student Drop-out Prevention for the 2023โ€“2024 academic year ๐Ÿ‘จโ€๐ŸŽ“.

๐Ÿ“š Professional Development :

Dr. Friman has been deeply involved in advancing energy education and public outreach initiatives in Israel ๐ŸŒ. He has led national and school-based projects such as โ€œEcological Gardenโ€ ๐ŸŒป and โ€œDecentralized Energyโ€ โšก, promoting sustainability in young minds. As Manager of the โ€œEnergy Supervisorโ€ program at HIT, in collaboration with the Ministry of Energy ๐Ÿ’ผ, he trains professionals in renewable technologies. A frequent speaker and advisory board member at international conferences ๐Ÿ—บ๏ธ, heโ€™s chaired sessions in cities like Amsterdam, Berlin, and Seville, contributing to academic excellence and cross-border collaborations ๐ŸŒ๐Ÿ“Š.

๐Ÿ”ฌ Research Focus :

Dr. Frimanโ€™s research bridges biotechnology and energy science ๐Ÿ”ฌโšก. He focuses on microbial fuel cells, renewable energy, and sustainable power generation using bio-based systems ๐ŸŒฑ๐Ÿ”‹. His doctoral work on using bacteria to degrade aromatic compounds for electricity generation is a pioneering step in bio-electrochemical energy. As Head of HITโ€™s Renewable Energy and Smart Grid Excellence Center, he explores decentralized energy systems, smart grids, and clean energy technologies for practical deployment in educational and community settings ๐Ÿซ๐Ÿ˜๏ธ. His multidisciplinary work positions him at the intersection of life sciences, engineering, and energy innovation ๐Ÿ”ง๐Ÿ’ก.

๐Ÿ† Awards and Honors :

Dr. Hen Friman has received multiple recognitions for his academic and professional contributions ๐Ÿ†. He served as a Member of the International Advisory Board for ICERI conferences in 2016 and 2017, and as a Session Chair at the ICBTS 2017 conferences held in Amsterdam and Berlin ๐Ÿ…. He was also a Member of the Advisory Board for EDULEARN17 ๐Ÿ“š. In 2017, he contributed as a Research Associate in Prof. Dr. Gabi Drochioiu’s laboratory at Alexandru Ioan Cuza University in Romania ๐Ÿ”ฌ. Domestically, he led impactful sustainability initiatives such as the โ€œEcological Gardenโ€ and โ€œDecentralized Energyโ€ school projects ๐ŸŒฟ. Dr. Friman currently heads the Renewable Energy and Smart Grid Center at HIT โšก and manages the โ€œEnergy Supervisorโ€ program, a national training initiative in collaboration with the Ministry of Energy ๐Ÿ› ๏ธ.

Publication Top Notes :

1. Soft Skills Education is Valuableโ€”Perception of Engineering Students

  • Citation:
    Balberg, M., Friman, H., Ragones, H., Baner, I., Shechter, R., & Kurtz, G. (2025). Soft Skills Education is Valuableโ€”Perception of Engineering Students. IEEE Transactions on Education, 68(1), 1โ€“11.

  • Summary:
    This study evaluates the impact of a dedicated soft skills course within an undergraduate electrical engineering program. The course focused on enhancing skills such as teamwork, time management, and communication. Findings indicate that students’ appreciation for soft skills and their confidence in applying them improved significantly post-course, underscoring the importance of integrating soft skills training into engineering curricula.

2. Nurturing Eco-Literate Minds: Unveiling the Pathways to Minimize Ecological Footprint in Early Childhood Education

  • Citation:
    Friman, H., Banner, I., Sitbon, Y., Sahar-Inbar, L., & Shaked, N. (2024). Nurturing Eco-Literate Minds: Unveiling the Pathways to Minimize Ecological Footprint in Early Childhood Education. Social Sciences, 13(4), 187.ย 

  • Summary:
    This article explores the role of early childhood education in promoting sustainability and reducing ecological footprints. It emphasizes the importance of environmental education in developing critical thinking and pro-environmental behaviors among young learners. The study highlights successful programs like โ€œGreen Ambassadors in the Community,โ€ demonstrating the effectiveness of experiential learning in fostering ecological awareness.

3. Shaping the Engineers of Tomorrow: Integrating Renewable Energies and Advanced Technologies in Electrical and Electronics Engineering Education

  • Citation:
    Friman, H. (2024). Shaping the Engineers of Tomorrow: Integrating Renewable Energies and Advanced Technologies in Electrical and Electronics Engineering Education. Energies, 17(16), 4146.

  • Summary:
    This paper discusses the integration of renewable energy technologies and advanced tools into electrical and electronics engineering education. It presents a model for incorporating practical laboratory experiences, such as fuel cell experiments and smart grid simulations, to enhance students’ understanding of sustainable energy systems. The study reports positive feedback from students, indicating increased engagement and comprehension of renewable energy concepts.

4. Experiential Learning for Sustainability: A Catalyst for Global Change

  • Citation:
    Friman, H. (2024). Experiential Learning for Sustainability: A Catalyst for Global Change. Educational Administration: Theory and Practice, 30(2), 45โ€“60.

  • Summary:
    This article examines the impact of experiential learning approaches on promoting sustainability education. It argues that hands-on experiences and real-world problem-solving activities are effective in instilling sustainable values and behaviors in students. The study highlights case studies where experiential learning led to increased environmental awareness and proactive engagement in sustainability initiatives.

5. Reducing Fossil Fuel Consumption by Incorporating Renewable Energy Sources in Wastewater Treatment Processes

  • Citation:
    Friman, H. (2023). Reducing Fossil Fuel Consumption by Incorporating Renewable Energy Sources in Wastewater Treatment Processes. Renewable Energy and Power Quality Journal, 21, 360.ย 

  • Summary:
    This study explores the integration of renewable energy sources, such as solar and wind power, into wastewater treatment processes to reduce reliance on fossil fuels. It presents a case study demonstrating the feasibility and benefits of using renewable energy in wastewater management, including cost savings and decreased greenhouse gas emissions.

๐Ÿ Conclusion:

Dr. Hen Friman exemplifies the qualities of a Best Researcher Award recipientโ€”combining scientific rigor, technological innovation, and public service. His research in bio-fuel cells and leadership in renewable energy initiatives have made a tangible impact in both academia and national energy policy, making him a truly deserving candidate.

 

Georgi Todorov | 3D Design | Best Researcher Award

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Georgi Todorov | 3D Design | Best Researcher Award

Prof. Dr. Georgi Todorov, TU Sofia, Bulgaria

Prof. Dr. Georgi Todorov, DSc, PhD ๐ŸŽ“, is a renowned professor at the Technical University of Sofia ๐Ÿ‡ง๐Ÿ‡ฌ and Head of the Center for Virtual Engineering ๐Ÿง ๐Ÿ’ป. He founded and leads the CAD/CAM/CAE in Industry Lab ๐Ÿ› ๏ธ and the 3DCLab โ€“ Fast Prototyping & 3D Creativity at Sofia Tech Park ๐Ÿงช๐Ÿญ. With vast experience in engineering design, virtual prototyping, and additive technologies ๐Ÿ–จ๏ธ๐Ÿงฌ, he has led over 50 international industrial projects ๐ŸŒ for major global firms. As Dean (2010โ€“2019) of the Faculty of Industrial Technology, he continues to inspire innovation in engineering education and industry collaboration ๐Ÿ”ง๐Ÿ“ˆ.

Profile :

๐ŸŽ“Education & Experience :

Prof. Dr. Georgi Todorov ๐ŸŽ“ holds both a PhD and a DSc in Engineering from the Technical University of Sofia, where he currently serves as a professor ๐Ÿง‘โ€๐Ÿซ. From 2010 to 2019, he was the Dean of the Faculty of Industrial Technology ๐Ÿ›๏ธ. He is the Head of the Center for Virtual Engineering ๐Ÿงช and the Founder and Head of the CAD/CAM/CAE in Industry Laboratory ๐Ÿงฐ. In addition, he leads the 3DCLab โ€“ Fast Prototyping and 3D Creativity Lab at Sofia Tech Park ๐Ÿง . Prof. Todorov has spearheaded over 50 international industrial projects ๐ŸŒ with renowned companies such as Chevron, Renault, VW, and Sensata. His key areas of expertise include 3D technologies, FEM analysis, virtual reality, additive manufacturing, and product/process optimization ๐Ÿ“Š.

๐Ÿ“š Professional Development :

Prof. Todorov has pursued specialized training worldwide to strengthen his expertise ๐ŸŒ๐Ÿ“˜. Between 1986โ€“1987, he trained in robotics and numerical methods ๐Ÿค–โž—. In 1993 and 1994, he specialized in engineering analysis at Staffordshire University, UK ๐Ÿ‡ฌ๐Ÿ‡ง๐Ÿ”. Later, in 2003, he advanced his knowledge in Rapid Prototyping/Tooling at AOTS in Japan ๐Ÿ‡ฏ๐Ÿ‡ตโš™๏ธ. These global experiences helped him build cutting-edge capabilities in digital design, additive manufacturing, and virtual engineering ๐Ÿง‘โ€๐Ÿ’ป๐Ÿ–จ๏ธ. His international exposure and collaboration with industry giants enable him to lead interdisciplinary innovation and applied research across sectors ๐Ÿš€๐Ÿ—๏ธ.

๐Ÿ”ฌ Research Focus :

Prof. Todorovโ€™s research focuses on advanced digital engineering technologies, including 3D modeling, additive manufacturing, and virtual product development ๐Ÿ–จ๏ธ๐Ÿ”. His expertise extends to FEM (Finite Element Method) analysis ๐Ÿงฎ, Virtual and Augmented Reality for engineering visualization ๐Ÿฅฝ, and 3D scanning/metrology ๐Ÿ“. He emphasizes New Product Development (NPD), rapid prototyping/tooling, and smart product/process optimization ๐Ÿ”ง๐Ÿ“ˆ. His work supports both academic excellence and industrial application across automotive, electronics, and mechanical sectors ๐Ÿš—โšก๐Ÿ”ฉ. He is deeply engaged in managing complex R&D projects, ensuring practical impact and innovation in the engineering ecosystem ๐Ÿง‘โ€๐Ÿ”ฌ๐ŸŒ.

๐Ÿ† Awards and Honors :

Prof. Dr. Georgi Todorov has received numerous prestigious awards throughout his distinguished career. In 2019, he was honored with the Dean Emeritus Recognition ๐Ÿ… by the Faculty of Industrial Technology at TU-Sofia. He has earned Global Collaboration Honors ๐ŸŒ from industrial partners across the USA, France, Germany, Taiwan, and the UK, acknowledging his commitment to international cooperation. His outstanding contributions to applied research and prototyping have been recognized through several Innovation Leadership Awards ๐Ÿงช. He also received accolades for Best Industrial Project Execution ๐Ÿ› ๏ธ for successful collaborations with Chevron, VW, and Renault. Additionally, Sofia Tech Park awarded him for his pioneering leadership in 3DCLab and advancing technological innovation ๐ŸŽ–๏ธ.

Publication Top Notes :

1. Evaluation of the Performance of Optimized Horizontal-Axis Hydrokinetic Turbines

  • Citation: Iliev, R., Todorov, G. D., Kamberov, K., & Zlatev, B. (2025). Evaluation of the Performance of Optimized Horizontal-Axis Hydrokinetic Turbines. Water, 17(10), 1532.ย 

  • Summary: This study focuses on the performance assessment of optimized horizontal-axis hydrokinetic turbines. The authors analyze various design parameters and their impact on turbine efficiency, providing insights into the optimization of turbine performance in hydrokinetic energy applications.

2. Failure Modes and Effect Analysis of Turbine Units of Pumped Hydro-Energy Storage Systems

  • Citation: Todorov, G. D., Kralov, I., Kamberov, K., Sofronov, Y., Zlatev, B., & Zahariev, E. (2025). Failure Modes and Effect Analysis of Turbine Units of Pumped Hydro-Energy Storage Systems. Energies, 18(8), 1885.ย 

  • Summary: The paper presents a comprehensive failure modes and effects analysis (FMEA) of turbine units in pumped hydro-energy storage systems. It identifies potential failure points, assesses their impact, and suggests mitigation strategies to enhance system reliability and performance.

3. Dynamics of a Self-Excited Vibrating Thermal Energy Harvester with Shape Memory Alloys and PVDF Cantilevers

  • Citation: Yotov, I., Todorov, G. D., Gieva, E., & Todorov, T. (2025). Dynamics of a Self-Excited Vibrating Thermal Energy Harvester with Shape Memory Alloys and PVDF Cantilevers. Actuators, 14(1), 8.ย 

  • Summary: This research introduces a novel thermal energy harvester that converts heat into mechanical vibrations using shape memory alloys (SMA) and polyvinylidene fluoride (PVDF) cantilevers. The device leverages the thermomechanical properties of SMA to induce vibrations, which are then converted into electrical energy by PVDF elements. Experimental results demonstrate the harvester’s potential for low-power applications.

4. Virtual Prototyping-Based Development of Stepper Motor Design

  • Citation: Kamberov, K., Todorov, G. D., & Zlatev, B. (2024). Virtual Prototyping-Based Development of Stepper Motor Design. Actuators, 13(12), 512.ย 

  • Summary: The authors present a methodology combining virtual and physical prototyping for the development of stepper motors. By integrating simulations at various design stages, the approach enhances design accuracy and reduces development time. The study showcases the methodology’s application in designing a stepper motor for hydraulic valve systems.MDPI

5. Investigation and Identification of the Causes of the Unprecedented Accident at the โ€œChairaโ€ Pumped Hydroelectric Energy Storage

  • Citation: Todorov, G. D., Kralov, I., Kamberov, K., Sofronov, Y., Zlatev, B., & Zahariev, E. (2024). Investigation and Identification of the Causes of the Unprecedented Accident at the โ€œChairaโ€ Pumped Hydroelectric Energy Storage. Water, 16(23), 3393.ย 

  • Summary: This paper analyzes a significant failure in the “Chaira” pumped hydroelectric energy storage facility, focusing on the destruction of stay vanes in Hydraulic Unit No. 4. Through virtual prototyping and finite element analysis, the study identifies low-cycle fatigue as the primary cause and recommends measures for rehabilitation and future prevention.

Conclusion:

Prof. Dr. Georgi Todorov stands out as a visionary researcher whose work has significantly influenced both academic scholarship and industrial advancement. His unique ability to translate theoretical research into impactful industrial applications makes him a highly deserving candidate for the Best Researcher Award. His sustained contributions to engineering science, technological innovation, and research leadership embody the spirit of excellence that this award seeks to recognize.

 

Gholamreza Hesamian | Fuzzy Statistical Analysis | Best Researcher Award

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Gholamreza Hesamian | Fuzzy Statistical Analysis | Best Researcher Award

Prof. Gholamreza Hesamian, Payame Noor University, Iran

Dr. Gholamreza Hesamian ๐ŸŽ“ is an accomplished Iranian statistician specializing in fuzzy statistical modeling and imprecise data analysis. Born on March 21, 1979, in Isfahan ๐Ÿ‡ฎ๐Ÿ‡ท, he currently serves at the Department of Statistics, Payame Noor University, Tehran ๐Ÿ“. With a Ph.D. in Statistics from Isfahan University of Technology, his work focuses on integrating fuzzy mathematics ๐Ÿค– into statistical inference. His research offers robust solutions in uncertain environments, making valuable contributions to modern statistical science ๐Ÿ“Š. Dr. Hesamian is dedicated to teaching, research, and academic development, helping shape the next generation of data scientists and statisticians ๐Ÿ‘จโ€๐Ÿซโœจ.

Profile :

๐ŸŽ“Education & Experience :

Dr. Gholamreza Hesamian ๐ŸŽ“ began his academic journey with a B.S. in Statistics from Isfahan University in 2000. He continued his studies at Isfahan University of Technology, earning an M.A. in Statistics ๐Ÿ“˜ in 2004, followed by a Ph.D. in Statistics ๐Ÿ“š in 2012. His doctoral research focused on Non-Parametric Statistical Inference based on Imprecise Information ๐Ÿ“, under the supervision of Dr. S.M. Taheri ๐Ÿ‘จโ€๐Ÿซ. Currently, he serves as a faculty member at the Department of Statistics, Payame Noor University in Tehran ๐Ÿข, where he teaches and conducts research in advanced statistical modeling and fuzzy mathematics.

๐Ÿ“š Professional Development :

Dr. Hesamian has consistently advanced his academic and professional development ๐Ÿ“ˆ through dedicated research, publication, and active engagement in statistical education. He has participated in academic conferences ๐ŸŽค, contributed to scientific journals ๐Ÿ“‘, and collaborated on interdisciplinary projects involving fuzzy logic and probability ๐Ÿค. His commitment to knowledge-sharing and curriculum innovation enhances statistical learning outcomes ๐Ÿ’ผ๐Ÿ“˜. Through workshops, seminars, and mentorship, he inspires students and young researchers to pursue excellence in data science, especially under conditions of uncertainty ๐ŸŽฏ๐Ÿง . Dr. Hesamian remains a proactive contributor to Iranโ€™s academic and research community in statistics ๐Ÿ‡ฎ๐Ÿ‡ท.

๐Ÿ”ฌ Research Focus :

Dr. Hesamianโ€™s research focuses on fuzzy statistics ๐Ÿค–๐Ÿ“Šโ€”a field that combines traditional statistical techniques with fuzzy logic to model uncertainty and imprecise information. His work enhances data analysis when classical probabilistic models fall short, particularly in decision-making environments marked by vagueness and ambiguity ๐ŸŒซ๏ธ๐Ÿ”. Key areas include fuzzy probability, fuzzy mathematical models, and non-parametric inference under uncertainty ๐Ÿ“ˆ. His research has wide applications in engineering, economics, and social sciences where exact data is difficult to obtain ๐Ÿงฎ๐Ÿ’ก. By bridging mathematics and real-world complexity, Dr. Hesamian contributes significantly to the development of intelligent and adaptive data systems ๐Ÿค“โš™๏ธ.

๐Ÿ† Awards and Honors :

Dr. Gholamreza Hesamian ๐Ÿ… has been recognized for his outstanding Ph.D. research in Non-Parametric Inference with Imprecise Data. He has received honors ๐ŸŽ–๏ธ from Payame Noor University for Excellence in Research and has been commended ๐Ÿ“œ for his significant academic contributions to Fuzzy Statistical Modeling. Additionally, he has actively participated ๐Ÿ† in national conferences focused on Advanced Statistics and Fuzzy Systems, showcasing his dedication to advancing the field.

๐Ÿ”นPublication Top Notes :

1. A Fuzzy Multiple Regression Model Adopted with Locally Weighted and Interval-Valued Techniques

  • Authors: Gholamreza Hesamian, Arne Johannssen, Nataliya Chukhrova

  • Journal: Journal of Computational and Applied Mathematics

  • Year: 2026

  • Type: Open Access

  • Summary:
    This study introduces a fuzzy multiple regression model that integrates locally weighted regression with interval-valued fuzzy techniques. The proposed method addresses uncertainties in predictor-response relationships and improves interpretability in fuzzy environments. Local weighting enables the model to adapt flexibly to localized data patterns, while interval-valued fuzzy numbers help handle imprecise or vague data.

2. A Two-way Crossed Effects Fuzzy Panel Linear Regression Model

  • Authors: Gholamreza Hesamian, Arne Johannssen

  • Journal: International Journal of Computational Intelligence Systems

  • Year: 2025

  • Volume: 18, Issue 1, Article 13

  • Type: Open Access

  • Summary:
    This article proposes a fuzzy panel data regression model that incorporates two-way crossed random effects, capturing both individual and time-related variability. The fuzzy framework accommodates vagueness in longitudinal data, improving forecasting and inference in applications where uncertainty is prominent, such as economics and social sciences.

3. A Fuzzy Multivariate Regression Model to Control Outliers and Multicollinearity Based on Exact Predictors and Fuzzy Responses

  • Authors: Gholamreza Hesamian, Mohammad Ghasem H. Akbari, Mehdi Shams

  • Journal: Iranian Journal of Mathematical Sciences and Informatics

  • Year: 2025

  • Summary:
    This model introduces a fuzzy multivariate regression approach designed to handle outliers and multicollinearity in regression analysis. It uses exact numerical predictors and fuzzy-valued responses to provide robust estimation and reduce the effect of anomalies or correlated variables, especially useful in uncertain data settings like finance or environmental studies.

4. A Flexible Soft Nonlinear Quantile-Based Regression Model

  • Authors: Gholamreza Hesamian, Arne Johannssen, Nataliya Chukhrova

  • Journal: Fuzzy Optimization and Decision Making

  • Year: 2025

  • Type: Open Access

  • Summary:
    This article introduces a nonlinear soft regression model based on quantile estimation techniques in fuzzy environments. It allows modeling asymmetric distributions and tail behaviors under uncertainty. This is particularly useful in decision-making and risk assessment where traditional mean-based models fail to capture distributional extremes.

5. A Neural Network-Based ARMA Model for Fuzzy Time Series Data

  • Authors: Gholamreza Hesamian, Arne Johannssen, Nataliya Chukhrova

  • Journal: Computational and Applied Mathematics

  • Year: 2024

  • Summary:
    Combines ARMA (AutoRegressive Moving Average) models with neural networks for modeling fuzzy time series. This hybrid model handles both temporal dependencies and fuzzy uncertainty, offering improved accuracy in forecasting complex real-world systems such as energy demand or economic indicators.

๐Ÿ”นConclusion:

Given his trailblazing contributions to fuzzy statistical inference, commitment to academic excellence, and influence on the next generation of researchers, Dr. Gholamreza Hesamian embodies the values and vision of the Best Researcher Award. His work not only enhances statistical science but also provides vital tools for real-world decision-making under uncertainty. He is a deserving recipient of this recognition.

Jurgita Malaiลกkienฤ— | Innovation | Women Researcher Award

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Dr. Jurgita Malaiลกkienฤ—| Innovation | Women Researcher Award

Chief researcher, Vilnius Gediminas technical university, Lithuania

Dr. Jurgita Malaiลกkienฤ— (๐ŸŽ‚ 1979-05-02) is the Chief Researcher at the Laboratory of Composite Materials, Vilnius Gediminas Technical University ๐Ÿ›๏ธ. With a strong academic background in Civil Engineering ๐Ÿ‘ทโ€โ™€๏ธ, she holds a Ph.D. in Technological Sciences (2008) ๐ŸŽ“. Her expertise centers on ceramic and cementitious materials, sustainable construction, and the application of nano-additives ๐Ÿงช. Jurgita has held various academic and research positions since 2008, actively contributing to innovation in material science and engineering ๐Ÿ”ฌ. She is also involved in project evaluation and education development across Lithuania ๐Ÿ“˜๐Ÿ‡ฑ๐Ÿ‡น, reflecting her dedication to academic excellence and applied research ๐Ÿš€.

Profile:

๐ŸŽ“ Education & ๐Ÿ‘ฉโ€๐Ÿ”ฌ Professional Experience:

Dr. Jurgita Malaiลกkienฤ— earned her B.Sc. ๐Ÿ“˜ (2001) and M.Sc. ๐Ÿ“— (2003) degrees in Civil Engineering from Vilnius Gediminas Technical University (VILNIUS TECH), followed by a Ph.D. ๐Ÿ“• in Technological Sciences (Civil Engineering) in 2008. Her professional journey began as a Researcher ๐Ÿ”ฌ at the Department of Building Materials, VILNIUS TECH (2008โ€“2014). She also served as an Associate Professor ๐Ÿ‘ฉโ€๐Ÿซ from 2009โ€“2011 and again in 2013โ€“2014. After a period of maternity and parental leave ๐Ÿ‘ถ (2014โ€“2016), she resumed work as a Senior Researcher ๐Ÿงช at the Research Institute of Building Materials (2016โ€“2017) and later as a Professor ๐Ÿงฏ (2018โ€“2019). In parallel, she contributed as an LVPA Assessor โœ… (2017โ€“2018, 2023โ€“2024). From 2017โ€“2023, she worked as a Senior Researcher ๐Ÿงฌ at the Laboratory of Composite Materials and has been serving as the Chief Researcher ๐Ÿ‘ฉโ€๐Ÿ”ฌ since 2023.

๐Ÿ”นProfessional Development :

Dr. Malaiลกkienฤ— has consistently enhanced her professional skills through specialized courses and seminars ๐ŸŽ“๐Ÿ’ผ. From 2005โ€“2008, she participated in human resource improvement seminars for civil engineering ๐Ÿง‘โ€๐Ÿซ. She deepened her expertise in thermal analysis and calorimetry in 2008 ๐ŸŒก๏ธ. Over the years, she has embraced new technologies and innovations, attending seminars like โ€œSmart Buildingโ€ (2013) ๐Ÿข๐Ÿ’ก and courses on product development, R&D commercialization, and innovative teaching strategies ๐Ÿ“Š๐Ÿง . Her pedagogical knowledge was reinforced through dedicated courses in 2015, shaping her holistic approach to research, teaching, and industry collaboration ๐Ÿ‘ฉโ€๐Ÿซ๐Ÿ”ฌ.

๐Ÿ”น Research Focus :

Dr. Malaiลกkienฤ—โ€™s research revolves around ceramic and cementitious building materials ๐Ÿงฑ๐Ÿงช, with a strong emphasis on sustainability and innovation ๐ŸŒ. She explores the utilization of industrial waste โ™ป๏ธ, enhancing the eco-efficiency of construction materials. Her studies also investigate the impact of chemical admixtures and nano additives on structural and performance properties of cement-based composites ๐Ÿงฌ๐Ÿ—๏ธ. She applies mathematical modeling to predict material behavior and optimize compositions based on key parameters ๐Ÿ“ˆ๐Ÿ“. Her interdisciplinary work bridges material science and environmental engineering, driving advances in next-generation, high-performance construction materials ๐Ÿ˜๏ธ๐Ÿš€.

๐Ÿ”นPublication Top Notes :

1. Effect of Pozzolanic Additive on Properties and Surface Finish Assessment of Concrete

  • Citation:
    Girskas, G., Kriptaviฤius, D., Kizinieviฤ, O., & Malaiลกkienฤ—, J. (2025). Effect of Pozzolanic Additive on Properties and Surface Finish Assessment of Concrete. Buildings, 15(10), 1617.ย 

  • Summary:
    This study investigates the impact of a pozzolanic additive on concrete’s properties and surface finish. The additive reduced flowability, density, and ultrasonic pulse velocity while increasing entrained air content and reducing porosity. These changes suggest potential benefits for durability and surface quality in concrete applications.

2. Influence of Different Binders on the Municipal Solid Waste Incineration Fly Ash Granulation-Based Stabilization Process

  • Citation:
    Shevtsova, M., Malaiลกkienฤ—, J., ล kamat, J., & Antonoviฤ, V. (2025). Influence of Different Binders on the Municipal Solid Waste Incineration Fly Ash Granulation-Based Stabilization Process. Sustainability, 17(10), 4573.

  • Summary:
    The research evaluates how various binders affect the stabilization of municipal solid waste incineration fly ash (MSWI FA). Findings indicate that while cement-based solidification/stabilization techniques can immobilize heavy metals, they are less effective in reducing the mobility of chlorides and sulfates. Pre-treatment washing is recommended to enhance ash stability for potential reuse in construction materials.

3. Utilisation of Different Types of Glass Waste as Pozzolanic Additive or Aggregate in Construction Materials

  • Citation:
    Bekerฤ—, K., & Malaiลกkienฤ—, J. (2025). Utilisation of Different Types of Glass Waste as Pozzolanic Additive or Aggregate in Construction Materials. Processes, 13(5), 1613.

  • Summary:
    This article explores the potential of using glass waste as a fine or coarse aggregate in concrete or mortar mixtures, replacing traditional materials like sand and gravel. The study highlights the environmental benefits, including reduced COโ‚‚ emissions during clinker manufacturing, by incorporating dispersed glass into blended cements.

4. An Analysis of a Cement Hydration Process Using Glass Waste from Household Appliances as a Supplementary Material

  • Citation:
    Bekerฤ—, K., Malaiลกkienฤ—, J., & ล kamat, J. (2025). An Analysis of a Cement Hydration Process Using Glass Waste from Household Appliances as a Supplementary Material. Processes, 13(3), 840.

  • Summary:
    The study examines the feasibility of using glass waste from household appliances as a supplementary material in cement-based products. It analyzes the chemical and mineral compositions, particle morphology, and size distribution of the glass waste, assessing its suitability as a replacement additive in cement hydration processes.

5. Influence of Pozzolanic Additives on the Structure and Properties of Ultra-High-Performance Concrete

  • Citation:
    Malaiลกkienฤ—, J., & Jakubovskis, R. (2025). Influence of Pozzolanic Additives on the Structure and Properties of Ultra-High-Performance Concrete. Materials, 18(6), 1304.

  • Summary:
    This paper explores the structural changes and performance improvements in ultra-high-performance concrete (UHPC) when pozzolanic additives are incorporated. The study confirms enhancements in strength, density, and durability due to the pozzolanic reaction and refined microstructure, suggesting viable applications in high-demand structural elements.

๐Ÿ”นConclusion:

Dr. Jurgita Malaiลกkienฤ—โ€™s distinguished career, scientific rigor, and meaningful contributions to sustainable material science make her a highly deserving nominee for the Best Researcher Award. Her work not only advances engineering knowledge but also delivers tangible benefits to society and the environmentโ€”embodying the spirit of this prestigious recognition.

Shayesteh Tabatabaei | Wireless Sensor Networks | Best Researcher Award

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Assoc. Prof. Dr. Shayesteh Tabatabaei | Wireless Sensor Networks | Best Researcher Award

Phd, University of Saravan, Iran

Dr. Shayesteh Tabatabei is an accomplished Iranian Associate Professor in Computer Engineering at the Higher Education Complex of Saravan. Born in Tabriz, she has been recognized among the top 2% of scientists worldwide in 2024 ๐ŸŒ. With a Ph.D. from Tehran Science and Research University, her expertise spans wireless sensor networks, mobile ad-hoc networks, IoT, and intelligent algorithms ๐Ÿค–๐Ÿ“ก. She is a passionate educator and researcher who actively contributes to advancing intelligent routing protocols and optimization algorithms. Shayesteh also organizes workshops to foster knowledge in wireless networks and ISI article writing, supporting academic growth in her community ๐Ÿ“š๐ŸŽ“.

Profile:

๐ŸŽ“Education & Experience :

Dr. Shayesteh Tabatabei earned her Ph.D. in Computer Engineering from Tehran Science and Research University between 2010 and 2015, where she focused on intelligent routing protocols for mobile ad-hoc networks ๐ŸŽ“. Prior to that, she completed her M.Sc. at Islamic Azad University of Shabestar from 2007 to 2009, researching improvements to the AODV routing protocol using reinforcement learning ๐ŸŽ“. She also holds a B.Sc. in Computer Engineering from the same university, earned between 2002 and 2006 ๐ŸŽ“. Currently, she serves as an Associate Professor at the Department of Computer Engineering, Higher Education Complex of Saravan ๐Ÿ’ผ. Shayesteh has extensive teaching experience in advanced computer engineering courses across several universities ๐Ÿ“ฑ and is proficient in simulation tools and programming languages such as Matlab, R, Opnet, GloMoSim, C/C++, Python, HTML, SQL, and Oracle ๐Ÿ’ป.

๐Ÿ”นProfessional Development :

Dr. Tabatabei actively pursues professional growth through leading and organizing numerous workshops, including Wireless Networks, IoT, and ISI Article Writing workshops, held between 2014 and 2022 ๐Ÿ› ๏ธ๐Ÿ“…. Her commitment to advancing scientific knowledge is reflected in her top researcher awards at multiple universities ๐Ÿ†. She continually updates her skills in simulation tools and programming languages, strengthening her research and teaching capabilities ๐Ÿ’ป. Her dedication to academic excellence and community support drives her efforts in mentoring students and colleagues, facilitating better understanding and application of cutting-edge technologies in wireless communication and intelligent systems ๐Ÿค๐ŸŒ.

๐Ÿ”น Research Focus :

Dr. Tabatabeiโ€™s research centers on wireless sensor networks, mobile ad-hoc networks, and Internet of Things (IoT), focusing on designing and optimizing intelligent routing protocols for efficient communication in dynamic networks ๐Ÿ“ก๐Ÿ“ถ. She explores intelligent and optimization algorithms to enhance network performance and reliability, integrating reinforcement learning techniques for adaptive routing ๐Ÿ“Š๐Ÿค–. Her work addresses challenges in distributed systems and intelligent systems to support scalable, energy-efficient, and secure data transmission. This research is crucial for advancing next-generation smart networks and IoT applications, contributing to improved connectivity and smart infrastructure development ๐ŸŒโš™๏ธ.

๐Ÿ†Awards and Honors :

Dr. Shayesteh Tabatabei has been recognized multiple times for her outstanding research contributions. She was honored as the Top Researcher at the Islamic Azad University of Malekan Branch in 2011, 2016, and 2017 ๐Ÿ†. More recently, she received the Top Researcher award at the Higher Education Complex of Saravan in 2019, 2021, and 2022 ๐Ÿ…. These accolades highlight her consistent dedication to advancing research and excellence in her academic field.

๐Ÿ”นPublication Top Notes :

  • Title: New energy efficient management approach for wireless sensor networks in target tracking using Vortex Search Algorithm

Citation:
Tabatabaei, S. (2025). New energy efficient management approach for wireless sensor networks in target tracking using Vortex Search Algorithm. Heliyon, 2025-Mar. https://doi.org/10.1016/j.heliyon.2025.e42867

Summary:
This paper proposes a novel energy-efficient management protocol for wireless sensor networks (WSNs) focused on improving target tracking accuracy and prolonging network lifetime. It employs the Vortex Search Algorithm, a nature-inspired metaheuristic optimization technique, to optimize cluster formation and routing paths, reducing energy consumption. Simulation results demonstrate enhanced performance compared to existing methods, showing increased network longevity and tracking reliability.

  • Title: WITHDRAWN: A Novel method of routing in multi-channel multi-radio wireless mesh networks

Citation:
Tabatabaei, S., & Mehbodniya, A. (2025). WITHDRAWN: A Novel method of routing in multi-channel multi-radio wireless mesh networks. Preprint, 2025-Mar-05. https://doi.org/10.21203/rs.3.rs-3069796/v2

Summary:
This preprint, now withdrawn, originally introduced a new routing method for multi-channel, multi-radio wireless mesh networks aimed at enhancing throughput and minimizing interference. The approach integrated channel assignment and route optimization strategies. As the paper was withdrawn, details on methodology or results are unavailable.

  • Title: An energy-aware protocol in wireless sensor networks using the scattered search algorithm and fuzzy logic

Citation:
Tabatabaei, S., & Shaheen, Q. (2024). An energy-aware protocol in wireless sensor networks using the scattered search algorithm and fuzzy logic. PLOS ONE, 2024-Nov-04. https://doi.org/10.1371/journal.pone.0297728

Summary:
This article presents an energy-aware routing protocol that combines the Scattered Search Algorithm, a global optimization technique, with fuzzy logic to improve decision-making in WSNs. The protocol focuses on efficient energy usage by dynamically adapting routing paths according to network conditions and sensor node energy levels, significantly extending network lifespan while maintaining reliable data transmission.

  • Title: A Fault-Tolerant Clustering Approach for Target Tracking in Wireless Sensor Networks

Citation:
Tabatabaei, S. (2024). A Fault-Tolerant Clustering Approach for Target Tracking in Wireless Sensor Networks. Wireless Personal Communications, 2024-Aug. https://doi.org/10.1007/s11277-024-11495-4

Summary:
This paper introduces a fault-tolerant clustering protocol designed for target tracking applications in WSNs. The method enhances network robustness by incorporating mechanisms to detect and recover from node failures during target tracking, ensuring continuous monitoring and reducing data loss. Results show improved reliability and accuracy in tracking moving targets under adverse network conditions.

  • Title: A new model for evaluating the impact of organizational culture variables on the success of knowledge management in organizations using the TOPSIS multi-criteria algorithm: Case study

Citation:
Tabatabaei, S. (2024). A new model for evaluating the impact of organizational culture variables on the success of knowledge management in organizations using the TOPSIS multi-criteria algorithm: Case study. Computers in Human Behavior Reports, 2024-May. https://doi.org/10.1016/j.chbr.2024.100417

Summary:
This interdisciplinary paper applies the TOPSIS multi-criteria decision-making algorithm to evaluate how various organizational culture factors affect the success of knowledge management initiatives. The case study reveals key cultural drivers that significantly influence knowledge sharing and management, providing actionable insights for organizational development and strategy planning.

๐Ÿ”นConclusion:

Dr. Shayesteh Tabatabei exemplifies the qualities that the Best Researcher Award seeks to honor: impactful research, global recognition, leadership in knowledge dissemination, and a clear dedication to advancing her field. Her combination of technical innovation and educational mentorship makes her an ideal candidate for this award, reflecting both academic excellence and meaningful community impact.

Kang Tian | Drone modeling | Best Researcher Award

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Mr. Kang Tian | Drone modeling | Best Researcher Award

Student, Yantai University, China

Tian Kang ๐ŸŽ“ is a dedicated graduate student currently pursuing a Master’s degree in Control Engineering at the School of Computer and Control Engineering, Yantai University ๐Ÿ‡จ๐Ÿ‡ณ. He earned his Bachelor’s degree in Automation from the same university in 2022. His research passion ๐Ÿš lies in drone modeling and control design, contributing to projects such as intelligent sustainable aerial-ground IoT networks and multi-UAV time collaborative guidance algorithm software ๐ŸŒ. With a focus on innovation and precision, Tian Kang is actively shaping the future of autonomous systems and intelligent aerial networks. ๐Ÿ“ง

Profile

๐Ÿ”น Education and Experience :

Tian Kang ๐ŸŽ“ earned his Bachelor’s degree in Automation from Yantai University in 2022. He is currently pursuing a Master’s degree ๐Ÿ“š in Control Engineering at the School of Computer and Control Engineering, Yantai University. During his academic journey, he has actively participated in research projects ๐Ÿ’ผ focused on intelligent sustainable aerial-ground IoT networks, showcasing his ability to apply theoretical knowledge to real-world challenges. Additionally, Tian has been involved in the development of software ๐Ÿค– for multi-UAV time collaborative guidance algorithms, gaining valuable experience in autonomous systems and control technologies.

๐Ÿ”นProfessional Development :

Tian Kang is continuously advancing his expertise through academic research and technical innovation ๐Ÿ“˜๐Ÿ› ๏ธ. He has actively participated in cutting-edge projects, particularly in developing guidance algorithms for UAVs and intelligent IoT networks ๐Ÿš€๐Ÿ“ก. His commitment to academic growth is matched by his hands-on experience in system modeling and control design. Through collaborations and project work, he is building a strong foundation in autonomous system control, contributing to the evolving field of intelligent aerial-ground integration systems ๐ŸŒ๐Ÿ›ธ. Tian is keen on exploring interdisciplinary solutions that combine control theory, AI, and robotics to address complex engineering challenges ๐Ÿค๐Ÿ’ก.

๐Ÿ”น Research Focus Category :

Tian Kangโ€™s research focus lies primarily in the Aerospace Control and Intelligent Systems category ๐Ÿš€๐Ÿค–. His interests span drone modeling, flight control systems, and multi-agent collaboration using real-time algorithms. He actively explores solutions in UAV navigation, cooperative control, and IoT integration ๐ŸŒ๐Ÿ›ฐ๏ธ. His work addresses sustainability and efficiency in aerial-ground communications and control networks, making key contributions to the development of smart and eco-friendly UAV applications ๐ŸŒฑ๐Ÿ’ก. Tianโ€™s interdisciplinary approach merges control engineering, automation, and intelligent networking to advance research in autonomous aerial vehicle technologies ๐Ÿ“ˆ๐Ÿ”ฌ.

๐Ÿ”น Awards and Honors :

While Tian Kang ๐Ÿ… has not yet received publicly listed individual awards, he has made significant contributions as an active member ๐Ÿ’ผ๐ŸŽ“ of funded university-level research projects. His dedication and performance have earned him recognition ๐Ÿ“˜โœจ for academic excellence in project-based learning environments. Through his involvement in innovative and technically demanding projects, Tian has demonstrated a strong commitment to research, teamwork, and continuous professional development.

๐Ÿ”นPublication Top Notes :

  • Title: A Dynamic Inverse Decoupling Control Method for Reducing Energy Consumption in Quadcopter UAV

  • Authors: Guoxin Ma, Kang Tian, Hongbo Sun, Yongyan Wang, Haitao Li

Summary

This study introduces a dynamic inverse decoupling control strategy aimed at reducing energy consumption in quadcopter unmanned aerial vehicles (UAVs). The proposed method focuses on decoupling the complex dynamics of quadcopters to enhance control efficiency and minimize energy usage during flight operations. By implementing this control approach, the authors aim to improve the overall performance and energy efficiency of quadcopter UAVs.

๐Ÿ”นConclusion:

Tian Kang stands out as a promising young researcher whose work in autonomous systems and drone control is shaping the next generation of intelligent aerial networks. His combination of academic excellence, technical contribution, and forward-thinking application makes him an excellent candidate for the Best Researcher Award.

Weidong Li | Toxicology | Best Researcher Award

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Weidong Li | Toxicology | Best Researcher Award

Dr Weidong Li, Beijing Institute of Pharmacology and Toxicology, China

Dr. Weidong Li ๐Ÿง‘โ€๐Ÿ”ฌ is a leading toxicology researcher at the Beijing Institute of Pharmacology and Toxicology ๐Ÿ‡จ๐Ÿ‡ณ. Holding a Ph.D. in Pharmacy ๐ŸŽ“, he specializes in transcriptomics and investigates the molecular mechanisms of lung injury caused by toxic gases ๐Ÿงช. His work applies high-throughput and single-cell RNA sequencing ๐Ÿ”ฌ to identify novel biomarkers and therapeutic targets for respiratory diseases ๐ŸŒฌ๏ธ. Dr. Li has published in top journals including Cellular and Molecular Life Sciences ๐Ÿ“š and is a member of the Chinese Society of Toxicology ๐Ÿงซ. He is deeply committed to advancing respiratory health through cutting-edge toxicological research ๐Ÿš€.

Profile :

๐ŸŽ“Education & Experience :

Dr. Weidong Li earned his Ph.D. in Pharmacy from the Beijing Institute of Pharmacology and Toxicology, where he specialized in transcriptomics and lung injury mechanisms ๐Ÿ”ฌ. Currently serving as a Doctor at the same institute ๐Ÿง‘โ€๐Ÿ”ฌ, he leads pioneering research focused on toxic gas-induced pulmonary damage ๐Ÿงช. Dr. Li is an expert in leveraging high-throughput and single-cell RNA sequencing technologies ๐Ÿงฌ to uncover molecular and cellular changes in lung tissue. He remains an active member of the Chinese Society of Toxicology ๐Ÿงซ, contributing to national and international advancements in the field of respiratory toxicology.

๐Ÿ“š Professional Development :

Dr. Li continually expands his professional competencies through active research, publication, and collaboration ๐Ÿ“š๐Ÿค. He integrates cutting-edge bioinformatics ๐Ÿง  and transcriptomics technologies ๐Ÿ” to drive innovations in respiratory toxicology. His multidisciplinary approach merges in vivo and in vitro studies ๐Ÿงซ๐Ÿงฌ, enabling discoveries of novel molecular targets and cell subtypes in lung injury. His contributions appear in respected journals such as Ecotoxicology and Environmental Safety and Journal of Translational Medicine ๐Ÿ“. By participating in scientific societies and submitting patents ๐Ÿ’ก๐Ÿ“„, Dr. Li remains at the forefront of toxicological innovation and therapeutic discovery ๐Ÿ”ฌ.

๐Ÿ”ฌ Research Focus :

Dr. Li’s research centers on toxicology, with a specific focus on pulmonary injury caused by toxic gas exposure ๐ŸŒซ๏ธ๐Ÿงช. Utilizing transcriptomic techniques, including single-cell RNA sequencing ๐Ÿ”ฌ, he uncovers gene expression changes and cellular dynamics in lung tissues after exposure. His integrated use of in vivo and in vitro models helps identify critical biomarkers and therapeutic targets ๐ŸŽฏ for respiratory disorders. This translational approach bridges basic science and clinical application ๐Ÿง ๐Ÿ’‰, offering new avenues for prevention and treatment strategies in respiratory medicine ๐ŸŒฌ๏ธ. His work significantly contributes to advancing environmental health and safety ๐Ÿ›ก๏ธ๐ŸŒฑ.

๐Ÿ† Awards and Honors :

Dr. Weidong Li was nominated for the prestigious Best Researcher Award in 2025 ๐Ÿ…, recognizing his impactful contributions to toxicological science. He is a published author ๐Ÿ“„ in high-impact journals such as Ecotoxicology and Environmental Safety, Cellular and Molecular Life Sciences, and the Journal of Translational Medicine. His innovative research has led to the development of a patent ๐Ÿ“Š focused on biomarkers for lung injury, which is currently published or under process. As a dedicated member of the Chinese Society of Toxicology ๐ŸŽ–๏ธ, Dr. Li actively contributes to the advancement of the toxicology community.

Publication Top Notes :

1. Single-cell RNA sequencing identifies cellular heterogeneity in endothelial and epithelial cells associated with nitrogen dioxide-induced acute lung injury

Journal: Ecotoxicology and Environmental Safety
Publication Date: July 2025
DOI: 10.1016/j.ecoenv.2025.118385
ISSN: 0147-6513
Authors: Weidong Li, Zhenghao Bao, Hongpeng Huang, Yingkai Ma, Yangyang Sun, Xueyang Lin, Weiqiang Sun, Shengran Wang, Ziqi Cui, Chen Yang, et al.

Summary:
This study utilized single-cell RNA sequencing to analyze lung tissue affected by nitrogen dioxide (NOโ‚‚)-induced acute lung injury (ALI). The research revealed pronounced cellular heterogeneity in endothelial and epithelial populations, highlighting specific gene expression changes that underlie tissue damage and repair. The findings contribute to understanding the pathophysiological mechanisms of NOโ‚‚-induced lung injury and may inform targeted therapeutic strategies.

2. Role of transient receptor potential ankyrin 1 in idiopathic pulmonary fibrosis: modulation of M2 macrophage polarization

Journal: Cellular and Molecular Life Sciences
Publication Date: December 2024
DOI: 10.1007/s00018-024-05219-x
ISSN: 1420-682X / 1420-9071
Authors: Yi Yang, Zhenyu Xiao, Weijie Yang, Yangyang Sun, Xin Sui, Xueyang Lin, Xinyi Yang, Zhenghao Bao, Ziqi Cui, Yingkai Ma, Weidong Li, et al.

Summary:
This article explores the involvement of TRPA1 (transient receptor potential ankyrin 1) in the progression of idiopathic pulmonary fibrosis (IPF), focusing on its role in regulating M2 macrophage polarization. The study demonstrates that TRPA1 activation contributes to fibrotic processes by enhancing M2 macrophage responses, suggesting it as a potential therapeutic target in IPF management.

3. Meldonium, as a potential neuroprotective agent, promotes neuronal survival by protecting mitochondria in cerebral ischemiaโ€“reperfusion injury

Journal: Journal of Translational Medicine
Publication Date: August 15, 2024
DOI: 10.1186/s12967-024-05222-7
ISSN: 1479-5876
Authors: Weijie Yang, Xiuxing Lei, Fengying Liu, Xin Sui, Yi Yang, Zhenyu Xiao, Ziqi Cui, Yangyang Sun, Jun Yang, Xinyi Yang, Weidong Li, et al.

Summary:
The study investigates meldonium as a neuroprotective agent in cerebral ischemiaโ€“reperfusion injury. Results show that meldonium enhances neuronal survival by preserving mitochondrial function, reducing oxidative stress, and stabilizing energy metabolism. These findings suggest that meldonium could be a promising candidate for stroke therapy.

4. Antioxidant Activity and Probiotic Proliferation and Acidifying Activity of Intracellular Polysaccharides from the Shaggy Ink Cap Medicinal Mushroom, Coprinus comatus (Agaricomycetes), under Optimal Polysaccharide Synthase Activity

Journal: International Journal of Medicinal Mushrooms
Publication Year: 2021
DOI: 10.1615/intjmedmushrooms.2021039970
ISSN: 1521-9437
Authors: Yongxia Wang, Min Sun, Weidong Li, Yongqing Zhang, Hua Zhang, Chun-Chao Han

Summary:
This paper evaluates the antioxidant and probiotic-stimulating properties of intracellular polysaccharides extracted from Coprinus comatus cultivated under optimal enzymatic conditions. Results demonstrate significant antioxidant activity and the ability to enhance probiotic proliferation and acidification, indicating potential for functional food and nutraceutical applications.

5. The Shaggy Ink Cap Medicinal Mushroom, Coprinus comatus (Agaricomycetes), Protein Attenuates Acute Alcoholic Liver Injury in Association with Changes in the Gut Microbiota of Mice

Journal: International Journal of Medicinal Mushrooms
Publication Year: 2021
DOI: 10.1615/intjmedmushrooms.2021038229
ISSN: 1521-9437
Authors: Weidong Li, Yongxia Wang, Min Sun, Yuting Liang, Xianlei Wang, Dongmei Qi, Chunchao Han

Summary:
This study demonstrates the hepatoprotective effects of protein derived from Coprinus comatus against acute alcoholic liver injury in mice. The protective effect is associated with beneficial modulation of gut microbiota, pointing toward a promising natural remedy for alcohol-induced liver damage.

Conclusion:

Dr. Weidong Liโ€™s innovative use of modern transcriptomic technologies to explore and mitigate the health impacts of toxic gases represents a significant advancement in environmental and respiratory toxicology. His research not only enhances scientific understanding but also holds direct clinical and public health implications. Therefore, he is highly deserving of the Best Researcher Award for his pioneering work, scientific excellence, and unwavering commitment to improving respiratory health through toxicological innovation.

 

Jiqiang Chen | Optimal Transport | Best Researcher Award

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Prof. Jiqiang Chen | Optimal Transport | Best Researcher Awardย 

Dean of the School of Mathematics and Physics, Hebei University of Engineering, China

Dr. Jiqiang Chen ย is a prominent Professor and the Dean ย of the School of Mathematics and Physics at Hebei University of Engineering, Handan, China . He earned his M.Sc. from Hebei University in 2008 and completed his Ph.D. from the Harbin Institute of Technology in 2018 . With a strong foundation in mathematics and artificial intelligence ๐Ÿค–, Dr. Chen serves on the Youth Editorial Board for Fuzzy Information and Engineeringย  His research spans dynamic neural networks, AI, fuzzy optimization, and optimal transport ๐Ÿš€. He is widely recognized for his contributions to computational intelligence and engineering applications

Profile

ย  Scopus

๐ŸŽ“ Education

Dr. Jiqiang Chen ๐ŸŽ“ obtained his M.Sc. in Mathematics from Hebei University, Baoding, China, in 2008, and later earned his Ph.D. in Applied Mathematics from the Harbin Institute of Technology, Harbin, China, in 2018 ๐ŸŽ“. He currently serves as a Professor ๐Ÿ‘จโ€๐Ÿซ and the Deanย  of the School of Mathematics and Physics at Hebei University of Engineering. In addition to his academic leadership, Dr. Chen holds an editorial position as a Member of the Youth Editorial Boardย  for the Fuzzy Information and Engineering (SCI) journal, actively contributing to the advancement of research in computational intelligence and fuzzy systems.

๐Ÿ“š Professional Development

Dr. Chen has continually advanced his academic and leadership journey ๐Ÿ“ˆthrough years of rigorous research, interdisciplinary collaboration , and academic stewardship. His role as Dean involves curriculum innovation, fostering international cooperation , and mentoring young researchers ๐Ÿ‘จโ€๐Ÿ”ฌ. As a Youth Editorial Board Member for Fuzzy Information and Engineering ๐Ÿ“–, he contributes to the scientific community by reviewing and promoting cutting-edge research. Dr. Chen actively participates in conferences, workshops, and scientific forums , where he shares his insights on neural networks and fuzzy systems. His commitment to academic excellence and scientific innovation makes him a distinguished figure in his field .

๐Ÿ”ฌ Research Focus

Dr. Chen’s research focuses on the theoretical and practical aspects of dynamic neural networks , artificial intelligence ๐Ÿค–, fuzzy optimization โš™๏ธ, and optimal transport ๐Ÿš›. He explores how dynamic systems interact under uncertainty using fuzzy logic ๐ŸŒซ๏ธ, and applies optimal transport theory to solve real-world problems efficiently . His work aims to enhance machine learning frameworks and intelligent systems, with applications ranging from data science to engineering . He also contributes to developing novel algorithms for complex systems where deterministic approaches fall short. His multidisciplinary approach strengthens the bridge between mathematical theory and AI-based applications .

Publication Top Notesย 

ย The Prediction Model of Water Level in Front of the Check Gate of the LSTM Neural Network Based on AIW-CLPSO

  • Authors: Linqing Gao, Dengzhe Ha, Litao Ma, Jiqiang Chen

  • Journal: Journal of Combinatorial Optimization, Volume 47, Issue 2, 2024

  • Citations: 0 (as per latest available data)

Summary:

This study addresses the challenge of accurately predicting water levels in front of check gates, which is crucial for water resource management. The authors propose a hybrid model combining Long Short-Term Memory (LSTM) neural networks with an Adaptive Inertia Weight Comprehensive Learning Particle Swarm Optimization (AIW-CLPSO) algorithm. This integration aims to enhance the global optimization capability and convergence speed of the prediction model. The model was applied to the Chaohu Lake check gate, demonstrating superior performance with a Nashโ€“Sutcliffe efficiency coefficient of 0.9851 and a root mean square error of 0.0273 meters. The results indicate that the proposed AIW-CLPSO-LSTM model effectively captures the nonlinear and stochastic characteristics of water level fluctuations, offering a valuable tool for intelligent gate control and water resource scheduling in long-distance water transfer projects.

Discrete Optimal Transport for Class-Imbalanced Classifications

  • Authors: Jiqiang Chen, Jie Wan, Litao Ma

  • Journal: Mathematics, Volume 12, Issue 4, Article 524, 2024

  • Citations: 1 (as per latest available data)

Summary:

This paper introduces a novel approach to address the challenge of class imbalance in classification tasks using Regularized Discrete Optimal Transport (RDOT). The authors develop a framework that incorporates regularization into the discrete optimal transport problem, aiming to improve the performance of classifiers on imbalanced datasets. By formulating the classification problem as a transport problem between empirical distributions of different classes, the method seeks to find an optimal mapping that minimizes the cost while considering regularization terms to prevent overfitting. Experimental results on various benchmark datasets demonstrate that the proposed RDOT approach outperforms traditional methods in terms of accuracy and robustness, particularly in scenarios with significant class imbalance. This work contributes to the field by providing a mathematically grounded and effective solution for imbalanced classification problems.

Conclusion

Dr. Jiqiang Chenย  stands out as a dedicated scholar, innovative researcher, and visionary academic leader . His contributions to dynamic neural networks, artificial intelligence, and fuzzy optimization continue to drive progress in applied mathematics and intelligent systemsย  Through his leadership as Dean ๐Ÿซand involvement in editorial activities ๐Ÿง‘โ€๐Ÿ”ฌ, he fosters academic excellence and collaborative research. Dr. Chen’s work not only enhances theoretical understanding but also supports real-world applications, solidifying his reputation as a key figure in modern computational science .

Xia Renbo | Robotic Vision | Best Researcher Award

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Mr.Xia Renbo | Robotic Vision | Best Researcher Award

Researcher, Shenyang Institute of Automation and Chinese Academy of Sciences, China

Dr. Xia Renbo is a distinguished researcher and doctoral supervisor at the Shenyang Institute of Automation, Chinese Academy of Sciences (CAS) ๐Ÿง ๐Ÿค–. With a Ph.D. in Engineering from CAS and degrees from Harbin Institute of Technology ๐ŸŽ“, Dr. Xia specializes in industrial optical measurement, robotic vision, and intelligent manufacturing ๐Ÿ”ฌ๐Ÿ“ธ. He has led innovative projects in 3D reconstruction, machine learning, and pattern recognition ๐Ÿ› ๏ธ๐Ÿ’ก. A key contributor to smart industry technologies, he earned recognition with the Liaoning Provincial Science and Technology Progress Award ๐Ÿ…. His work bridges advanced computer vision and real-world automation challenges .

ย Profile

๐Ÿ”น Education & Experience :

Dr. Xia Renbo earned his ๐ŸŽ“ Ph.D. in Engineering in 2006 from the Shenyang Institute of Automation, Chinese Academy of Sciences (CAS), where he specialized in 3D reconstruction for industrial applications. He also holds an ๐ŸŽ“ M.S. (2002) and ๐ŸŽ“ B.S. (2000) in Mechanical Engineering and Automation from Harbin Institute of Technology. His professional journey began as an ๐Ÿ‘จโ€๐Ÿ”ฌ Assistant Researcher (2006โ€“2008) at SIA, CAS, where he developed algorithms for photogrammetry and surface reconstruction. He then served as an ๐Ÿ‘จโ€๐Ÿ”ฌ Associate Researcher (2009โ€“2018), focusing on 3D vision, defect detection, and camera calibration. Since 2019, he has been a leading ๐Ÿ‘จโ€๐Ÿ”ฌ Researcher at SIA, driving projects in intelligent optical measurement and robotic vision systems.

๐Ÿ“š Professional Development :

Dr. Xia Renbo has steadily advanced his career in industrial automation and intelligent systems ๐Ÿ”ง๐Ÿค–. Beginning as an Assistant Researcher, he contributed to early developments in 3D surface reconstruction and photogrammetry ๐Ÿ“๐Ÿ“ท. As an Associate Researcher, he expanded into multi-camera calibration and defect detection, contributing to industry-grade systems for quality assurance and control ๐Ÿ› ๏ธ๐Ÿงช. Now a lead Researcher, he spearheads high-impact projects in intelligent measurement and robotic vision, applying computer vision and AI to automation tasks ๐Ÿค–๐Ÿ”. His leadership reflects a commitment to integrating smart technologies into real-world industrial environments โš™๏ธ๐ŸŒ.

๐Ÿ”ฌ Research Focus :

Dr. Xiaโ€™s research spans several interconnected domains at the intersection of automation and intelligence ๐Ÿง โš™๏ธ. He focuses on industrial optical measurement, advancing precision in manufacturing with 3D reconstruction and dynamic tracking technologies ๐Ÿ“๐Ÿ”ฌ. His work in robotic vision and intelligent manufacturing leverages machine learning, computer vision, and pattern recognition to improve industrial adaptability and efficiency ๐Ÿค–๐Ÿ“ธ. By merging hardware integration with software intelligence, he contributes to the evolution of Industry 4.0 applications ๐Ÿš€๐Ÿญ. His research enhances robotic equipment with real-time perception and adaptability, fostering smarter production lines and inspection systems ๐Ÿ› ๏ธ๐Ÿ“Š.

๐Ÿ† Awards and Honors :

Dr. Xia Renbo was honored with the ๐Ÿฅ‰ Third Prize of the Liaoning Provincial Science and Technology Progress Award in 2011. This recognition was awarded for his outstanding contribution to the development of a 3D Photogrammetric System designed for accurate railway tanker volume measurement ๐Ÿ”๐Ÿš†. The project showcased his expertise in applying advanced optical measurement techniques to solve complex industrial challenges, further establishing his reputation in the field of intelligent manufacturing and robotic vision ๐Ÿค–๐Ÿ“

Publication Top Notes :

A Spectral-Domain Low-Coherence Method for Measuring Composite Windshield Thickness

Citation:
Tao Zhang, Renbo Xia, Jibin Zhao, Yanyi Sun, Jiajun Wu, ShengPeng Fu, Yueling Chen.
โ€œA Spectral-Domain Low-Coherence Method for Measuring Composite Windshield Thickness.โ€ IEEE Transactions on Instrumentation and Measurement, 2024.
DOI: 10.1109/TIM.2024.3353865

Summary:
This paper presents a spectral-domain low-coherence interferometry method tailored for non-destructive and high-precision thickness measurement of composite windshields. The proposed technique compensates for multi-layer reflections and surface curvatures, enabling accurate measurements across curved, layered glass structures commonly used in automotive windshields. The method demonstrates enhanced reliability and resolution compared to traditional time-domain approaches, making it suitable for quality control in automotive manufacturing.

Robust Correspondences with Saliency for Point Cloud Registration

Citation:
Yinghao Li, Renbo Xia, Jibin Zhao, Junlan Yi, Taiwen Qiu.
โ€œRobust Correspondences with Saliency for Point Cloud Registration.โ€ Proceedings of the 2024 ACM International Conference on Graphics and Interaction, April 26, 2024.
DOI: 10.1145/3671151.3671191

Summary:
The authors propose a saliency-guided framework for robust point cloud registration. By integrating geometric saliency and feature consistency, the approach significantly improves correspondence accuracy, especially in scenes with partial overlap or heavy noise. Experimental results confirm superior performance compared to traditional methods like ICP and FGR, particularly in challenging real-world 3D environments such as indoor mapping and robotic navigation.

Low-Coherence Measurement Methods for Industrial Parts With Large Surface Reflectance Variations

Citation:
Tao Zhang, Renbo Xia, Jibin Zhao, Jiajun Wu, Shengpeng Fu, Yueling Chen, Yanyi Sun.
โ€œLow-Coherence Measurement Methods for Industrial Parts With Large Surface Reflectance Variations.โ€ IEEE Transactions on Instrumentation and Measurement, 2023.
DOI: 10.1109/TIM.2023.3301894

Summary:
This study develops a low-coherence interferometric system optimized for measuring the thickness of industrial parts with complex surfaces and high reflectance variability. The methodology integrates reflectance compensation and real-time spectral analysis, enabling high-resolution and repeatable measurements on metal, glass, and composite surfaces. The approach is validated across various industrial use cases including machined parts and reflective coatings.

Research on Optimization of Multi-Camera Placement Based on Environment Model

Citation:
Liming Tao, Renbo Xia, Jibin Zhao, Fangyuan Wang, Shengpeng Fu.
โ€œResearch on Optimization of Multi-Camera Placement Based on Environment Model.โ€ Proceedings of the 2023 ACM International Conference on Intelligent Systems and Smart Environments, September 15, 2023.
DOI: 10.1145/3629264.3629288

Summary:
This paper introduces an optimization strategy for multi-camera placement in intelligent monitoring environments. Using a 3D environmental model, the proposed system maximizes surveillance coverage and minimizes blind spots by leveraging visibility analysis and coverage redundancy metrics. The algorithm proves effective in simulation and real-world testing, demonstrating practical value in smart buildings and industrial automation setups.

A High-Accuracy Circular Hole Measurement Method Based on Multi-Camera System

Citation:
Liming Tao, Renbo Xia, Jibin Zhao, Tao Zhang, Yinghao Li, Yueling Chen, Shengpeng Fu.
โ€œA High-Accuracy Circular Hole Measurement Method Based on Multi-Camera System.โ€ Measurement, Volume 205, February 2023, Article 112361.
DOI: 10.1016/j.measurement.2022.112361

Summary:
This work presents a multi-camera 3D reconstruction system for precise circular hole measurements in industrial components. The method employs stereo calibration, edge detection, and ellipse fitting techniques to extract geometric parameters with high accuracy. The system’s performance is validated against traditional single-camera and manual measurement approaches, achieving sub-millimeter precision and improved automation suitability.

Conclusion:

Dr. Xia Renbo exemplifies the qualities of a leading researcherโ€”technical depth, cross-disciplinary innovation, real-world impact, and academic mentorship. His groundbreaking work continues to shape the future of intelligent manufacturing and robotic automation. In light of his achievements and contributions, he is a compelling and deserving recipient of the Best Researcher Award.

Jiayue Guo | Starch Digestibility | Best Researcher Award

Posted on by ScienceFather

Assoc. Prof. Dr. Jiayue Guo | Starch Digestibility | Best Researcher Award

Associate professor, China Agricultural University. China

Dr. Jiayue Guo is an Associate Professor in the Department of Nutrition and Health at China Agricultural University, Beijing ๐Ÿ‡จ๐Ÿ‡ณ. She earned her Ph.D. in Human Nutrition from The University of Alabama (USA) and has rich international research experience, including postdoctoral work at UC Berkeley ๐Ÿ‡บ๐Ÿ‡ธ. Her research focuses on food biomacromolecules, starch digestibility, and molecular nutrition mechanisms ๐ŸŽ๐Ÿ”ฌ. Jiayue has contributed extensively to understanding resistant starch, bioactive compounds, and molecular aging in nutritional science. Passionate about bridging food science and health, she combines advanced lab techniques with applied nutritional studies to promote better health outcomes worldwide ๐ŸŒฑ๐Ÿ“š.

ย Profile

๐ŸŽ“ Education :

Dr. Jiayue Guo earned her Ph.D. in Human Nutrition from The University of Alabama (๐ŸŽ“2018โ€“2022) after completing her B.S. in Food Science and Technology at Hong Kong Baptist University-United International College (๐ŸŽ“2014โ€“2018). She then advanced her expertise as a Postdoctoral Scholar in Nutritional Science and Toxicology at UC Berkeley (๐Ÿง‘โ€๐Ÿ”ฌ2022โ€“2023). Currently, she serves as an Associate Professor in the Department of Nutrition and Health at China Agricultural University (๐Ÿ‘ฉโ€๐Ÿซ2023โ€“Present). Earlier in her career, Jiayue worked as a Research Assistant in the Food Biomacromolecules Lab at the University of Alabama (๐Ÿงช2018โ€“2022) and gained practical lab experience as a Lab Assistant at Mengniu Dairy Company and the Chinese Academy of Agricultural Sciences (๐Ÿง‘โ€๐Ÿญ2016โ€“2017).

๐Ÿ“š Professional Development :

Dr. Guo has developed a strong professional background through diverse educational and research programs ๐ŸŽ“๐ŸŒŽ. She participated in the Cornell-China Undergraduate Summer Program and a summer session on American History and Culture, enhancing her global perspective ๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ. Her teaching experience includes leading lab and online courses on food preparation and cellular nutrition ๐Ÿง‘โ€๐Ÿซ๐Ÿงฌ. Throughout her career, she has engaged in multidisciplinary projects involving food science, nutritional biochemistry, and molecular biology ๐Ÿ”ฌ๐Ÿฝ๏ธ. Her postdoctoral work at UC Berkeley further honed her expertise in metabolic biology and aging research, establishing her as a well-rounded scientist dedicated to improving human nutrition and health ๐ŸŒฑ๐Ÿ’ก.

๐Ÿ”ฌ Research Focus :

Dr. Jiayue Guoโ€™s research is centered on Human Nutrition and Food Science with a focus on starch digestibility, bioactive compound interactions, and molecular nutrition mechanisms ๐Ÿš๐Ÿ”ฌ. She investigates the structure-function relationships of resistant starch and its impact on digestion and health ๐Ÿฝ๏ธ๐Ÿงฌ. Her work includes studying starch inclusion complexes, encapsulation of bioactive molecules, and calorie restriction effects on stem cell aging ๐Ÿงช๐Ÿงฌ. This interdisciplinary focus blends food chemistry, biochemistry, and metabolic biology to uncover how dietary components influence human health and disease prevention ๐ŸŒฑโค๏ธ. Her innovative approach advances nutritional science and functional food development for better public health outcomes ๐ŸŒ๐Ÿ“ˆ.

๐Ÿ† Awards and Honors :

Dr. Jiayue Guo has been recognized for her outstanding achievements throughout her career. She was a recipient of competitive research funding during her postdoctoral training at UC Berkeley (๐Ÿ…) and earned recognition for excellence in her teaching assistantship at The University of Alabama (๐Ÿ“œ). Jiayue has also presented multiple research projects and published extensively in nutrition and food science journals (๐Ÿ”ฌ). Early in her academic journey, she was selected as a participant in the prestigious Cornell-China Undergraduate Summer Program (๐ŸŒŸ) and has been acknowledged for her valuable contributions to food biomacromolecules and starch research.

Publication Top Notes :

  • Structural changes of type 3 resistant starch during in vivo digestion using a duodenum and ileal cannulated miniature pig model
    J Shi, K Zeng, X An, J Guo, Y Hu, P Wang, F Ren, S Liu
    Carbohydrate Polymers, 360, 123608 (2025)

  • Inhibitory effects of water-soluble hemicelluloses from corn bran with varying molecular weights on wheat starch digestibility
    Z Ma, Y Sheng, X Liu, J Guo, P Wang, F Ren, L Wu, Y Liang, B Xu, S Liu
    Food Chemistry, 478, 143649 (2025)

  • Modification of waxy rice starch using a combination of ฮฒ-amylase and branching enzyme to delay retrogradation
    M Xu, D Guo, J Guo, Y Hu, P Wang, F Ren, S Liu
    International Journal of Biological Macromolecules, 144256 (2025)

  • Inhibition mechanism of ฮฑ-amylase and amyloglucosidase by spherical nanocrystalline cellulose with varying particle sizes
    D Long, Q Ma, D Guo, Y Hu, J Guo, R Wang, P Wang, F Ren, S Liu
    International Journal of Biological Macromolecules, 144041 (2025)

  • The effect of high-amylose maize starch on the digestibility of wheat starch after high-temperature cooking
    D Liang, W Luo, M Xu, D Guo, J Guo, Y Hu, P Wang, F Ren, S Liu
    International Journal of Biological Macromolecules, 310, 143258 (2025)

Conclusion :

Dr. Jiayue Guoโ€™s comprehensive expertise in nutrition science, international research background, and impactful contributions to understanding food biomacromolecules and molecular nutrition make her a highly deserving candidate for the Best Researcher Award. Her work not only advances scientific knowledge but also has meaningful implications for improving health worldwide, embodying the spirit of this award.