Alima Amangeldi | Climate Change | Research Excellence Award

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Ms. Alima Amangeldi | Climate Change | Research Excellence Award

Ms. Alima Amangeldi | Climate Change | Engineer at Institute of Ionosphere | Kazakhstan

Climate Change research forms the foundation of the scholarly and professional journey of Ms. Alima Amangeldi, an emerging Kazakhstani researcher whose contributions reflect a strong commitment to environmental resilience, cryosphere monitoring, and long-term hydro-climatic analysis. Ms. Alima Amangeldi is recognized for her intellectual dedication to understanding glacial dynamics and climate-driven transformations across mountainous regions, with a special focus on the Ile-Alatau Mountains within the Northern Tien Shan. Her academic background is rooted in rigorous scientific training in environmental science, Earth observation, and atmospheric studies, equipping her with a deep understanding of hydrology, remote sensing technologies, and climate processes that shape contemporary environmental challenges. Through her education, Ms. Alima Amangeldi developed expertise in satellite imagery interpretation, GIS-based glacier mapping, and the multi-temporal analysis of glacial and moraine lake changes that are vital for predicting natural hazards and informing adaptation strategies. Professionally, she serves at the Institute of Ionosphere in Almaty, Kazakhstan (2024–present), where she contributes to advanced research on atmospheric interactions, hydro-climatic variability, and geospatial environmental assessments. Her role involves conducting multi-temporal remote sensing studies, applying high-resolution climatic datasets, and collaborating with multidisciplinary experts to deepen insights into mountain cryosphere evolution and its broader regional implications. The professional experience of Ms. Alima Amangeldi is marked by her capacity to integrate field observations, satellite-based analytics, and climate modeling, which positions her as a promising researcher in climate science and natural resource management. Her research interests span climate change impacts on glacier recession, moraine lake expansion, hydro-climatic risk assessments, cryosphere monitoring, atmospheric variation analysis, and remote sensing applications in mountainous environments. In her work, Ms. Alima Amangeldi frequently employs advanced research skills such as geospatial analytics, LiDAR interpretation, multi-decadal climate data synthesis, hydrological modeling, and environmental trend analysis. She is proficient in utilizing tools like ArcGIS, QGIS, Google Earth Engine, ERDAS Imagine, and statistical packages used for climatic trend evaluation. Her analytical skills are further supported by her ability to interpret long-term climate indicators and correlate them with environmental shifts across sensitive alpine ecosystems. Although early in her academic trajectory, Ms. Alima Amangeldi has begun building an impactful scholarly presence, evidenced by her authorship of peer-reviewed scientific work focusing on long-term glacier and lake evolution from 1955–2024, informing early-warning systems, hazard prevention measures, and sustainable water resource planning. Her dedication to scientific rigor and environmental protection has earned her recognition as a promising contributor to Kazakhstan’s climate research community, and she is increasingly acknowledged within international research circles addressing cryosphere change and climate-induced mountain hazards. Awards and honors attributed to her include early-career recognition at institutional and departmental levels for excellence in scientific research and contributions to climate-related geospatial studies. Throughout her career progression, Ms. Alima Amangeldi continues to commit herself to advancing the scientific understanding of climate change impacts, strengthening the data foundations needed for sustainable policymaking, and contributing meaningful insights to global environmental research dialogues. In conclusion, Ms. Alima Amangeldi exemplifies the next generation of climate and environmental scientists whose research promises to support long-term climatic resilience, inform public awareness, and guide actionable strategies for adapting mountain ecosystems to the realities of a rapidly changing climate.

Academic Profile: ORCID

Featured Publications:

  1. Amangeldi, A. A., Iskaliyeva, G., Merekeyev, A., Sydyk, N., Abishev, B., & Baygurin, Z. (2025). Hydro-Climatic and Multi-Temporal Remote Analysis of Glacier and Moraine Lake Changes in the Ile-Alatau Mountains (1955–2024), Northern Tien Shan. Atmosphere.

 

 

Taimoor Ali Khan | Transportation Engineering | Research Excellence Award

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Mr. Taimoor Ali Khan | Transportation Engineering | Research Excellence Award

Mr. Taimoor Ali Khan | Transportation Engineering | Kunming University of Science and Technology | China

Transportation Engineering expert Mr. Taimoor Ali Khan is an emerging civil engineering professional whose academic training, technical expertise, and research contributions span transportation engineering, structural mechanics, infrastructure resilience, Non-Destructive Evaluation (NDE), and intelligent systems. With a Master’s degree in Civil Engineering from Beijing University of Technology and a Bachelor of Engineering in Civil Engineering from Mehran University of Engineering and Technology Mr. Taimoor Ali Khan has established a strong foundation in advanced engineering principles, reliability assessment, and infrastructure performance analysis. Throughout his master’s research, he conducted an in-depth investigation of the size effect on Fiber Reinforced Polymer (FRP)-confined concrete columns using analytical modeling and Finite Element Method (FEM) simulations in Abaqus, which later shaped his broader interest in enhancing infrastructure safety and resilience. Professionally, Mr. Taimoor Ali Khan has served in multiple engineering roles, including Material Engineer at Ghulam Rasool & Co. Pvt. Ltd. Site Engineer at Dico-Tech Qatar and Lecturer at Indus International Institute Pakistan, where he contributed to construction quality control, laboratory material testing, planning operations, and engineering education. These roles allowed him to bridge theoretical knowledge with real-world construction and planning challenges. His research interests now expand across Transportation Engineering, AI-driven mobility analytics, rural traffic management, network traffic prediction, Machine Learning-based safety systems, and NDE methods such as non-contact ultrasonics for structural damage detection. Mr. Taimoor Ali Khan possesses strong research skills in FEM modeling, structural reliability analysis, data-driven modeling, AI algorithm integration, transportation data analysis, and multi-source data fusion. His growing publication record reflects his commitment to developing intelligent, safe, and efficient transportation systems. His professional memberships include registration with the Pakistan Engineering Council and he is also a recipient of the prestigious Chinese Government Scholarship (China Scholarship Council), which supported his graduate studies in Beijing. His honors also include recognition for research contributions in transportation and infrastructure engineering, along with academic distinctions throughout his academic progression. Throughout his career, Mr. Taimoor Ali Khan has demonstrated a forward-thinking approach by integrating Transportation Engineering with Artificial Intelligence, contributing to modern mobility solutions. In conclusion, Mr. Taimoor Ali Khan continues to advance scholarly work and practical engineering innovations aimed at improving infrastructure quality, transportation safety, and data-driven decision-making. His extensive academic background, technical skills, and diverse professional experience position him as a promising researcher in Transportation Engineering, committed to developing sustainable, technologically enhanced engineering solutions for global challenges.

Academic Profile: ORCID

Featured Publications:

  1. Khan, T. A. (2025). Graph-based deep learning and multi-source data to provide safety-actionable insights for rural traffic management.

  2. Khan, T. A. (2025). Artificial intelligence as a tutor: Enhancing self-regulated learning in transportation engineering through AI-driven feedback.

  3. Khan, T. A. (2024). Network traffic prediction: Using AI to predict and manage traffic in high-demand IT networks.

  4. Khan, T. A. (2021). Analytical and numerical analysis of size impact on CFRP restrained cylindrical concrete column.

 

Bilal Jan Haji Muhammad | Geographical | Best Researcher Award

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Dr. Bilal Jan Haji Muhammad | Geographical | Best Researcher Award

Dr. Bilal Jan Haji Muhammad | Geographical | Ministry of Rural Rehabilitation and Development | Afghanistan

Geographical research forms the core of Dr. Bilal Jan Haji Muhammad’s academic identity, and throughout his career, he has established himself as a dynamic researcher devoted to advancing knowledge in Remote Sensing (RS), Geographic Information Systems (GIS), applied geology, land–surface interactions, and environmental change modelling. Dr. Bilal Jan Haji Muhammad completed his higher education at Northeast Normal University, China, where he strengthened his expertise in spatial analysis, geospatial modelling, and petrography, skills that later defined his scientific trajectory. His professional experience includes extensive collaboration with scholars across Afghanistan, Pakistan, and China, contributing significantly to multidisciplinary projects focused on land use/land cover (LULC) dynamics, chromite body characterization, morpho-tectonic interpretation, forest canopy density assessment, and integrated geological–geographical analyses. Through his scholarly work, Dr. Bilal Jan Haji Muhammad has contributed to understanding complex environmental systems using RS/GIS, particularly in regions such as Kunar Province, Logar Ophiolitic Complex, Malakand Division, and the Southern Region of Eritrea. His major research interests span spatial modelling, geochemical characterization, land degradation studies, heat-island assessment, and the interaction between landscape processes and climatic indicators. His specialized research skills include advanced satellite image processing, geospatial data analytics, spectral index computation, petrographic analysis, structural geology interpretation, and environmental change prediction using tools such as land change modeller and GIS-based simulation workflows. These competencies have enabled him to produce impactful cross-disciplinary outputs published in highly regarded journals including the Scottish Geographical Journal, Kuwait Journal of Science, GeoJournal, and Singapore Journal of Tropical Geography. Among his awards and honors, Dr. Bilal Jan Haji Muhammad’s recognition includes international research collaborations, verified academic contributions within his institution, and impactful citations reflecting his growing scholarly presence. His Google Scholar metrics—citations, h-index, and collaborative research networks—demonstrate his commitment to producing quality research in geographical sciences, applied geology, and remote sensing. With continuous contributions to the global academic community, Dr. Bilal Jan Haji Muhammad remains committed to advancing sustainable environmental management, improving geospatial modelling techniques, and strengthening the scientific understanding of geographically sensitive regions. In conclusion, Dr. Bilal Jan Haji Muhammad exemplifies a forward-looking researcher whose contributions in RS, GIS, geology, and Geographical modelling continue to expand the boundaries of environmental and geospatial science, positioning him as a promising scholar dedicated to impactful research and academic excellence.

Academic Profile: ORCID | Google Scholar

Featured Publications:

  1. Muhammad, B. J. H., Ping, W., Mohabbat, M. J., Ahmad, I., & Islam, I. (2025). Modelling and prediction of land use land cover change dynamics based on the land change modeller in Kunar Province, Eastern Afghanistan. Scottish Geographical Journal, 1–24. Citations: 2

  2. Ahmad, I., Ping, W., Razzaq, A., Muhammad, B. J. H., & Ali, W. (2024). Assessing urban thermal field variance and surface urban heat island effects: An ecological study in Malakand Division, Pakistan. Ecological Study. Citations: 2

  3. Muhammad, B. J. H., Rahmani, N. R., Mohabbat, M. J., Islam, I., Ahmad, I., & Ping, W. (2025). Integration of remote sensing and geochemical analysis of chromite bodies in Logar Ophiolitic Complex, Southeast Afghanistan. Kuwait Journal of Science, 100427. Citations: 1

  4. Muhammad, B. J. H., Ping, W., Mohabbat, M. J., Patmal, M. H., & Ahmad, I. (2024). Morpho-tectonic and satellite image interpretation for identifying Gardez fault in Afghanistan. Journal of Geoscience, Engineering, Environment, and Technology, 9(2), 221–226. Citations: 1

  5. Muhammad, B. J. H., Ping, W., Mohabbat, M. J., Islam, I., & Khattak, S. A. (2025). Examining the relationship among land surface temperature (LST), land use/land cover (LULC) and spectral indices in Kunar Province, Afghanistan. GeoJournal, 90(5), 237.

 

Ipek Atik | Health | Research Excellence Award

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Assoc. Prof. Dr. Ipek Atik | Health | Research Excellence Award

Assoc. Prof. Dr. Ipek Atik | Health | Gaziantep Islam Science and Technology University | Turkey

Health plays a central role in the scientific contributions of Assoc. Prof. Dr. Ipek Atik, whose career spans advanced research in deep learning, machine learning, renewable energy forecasting, medical image analysis, and computational modeling. Assoc. Prof. Dr. Ipek Atik has built a strong academic foundation through her formal education, progressing from engineering studies into specialized research areas involving artificial intelligence applications to health systems, environmental sustainability, and complex data-driven prediction models. Her professional experience includes serving as an academic and researcher at Gaziantep Islam Science and Technology University, where she has contributed extensively to AI-driven classification systems, forecasting methodologies, radiation shielding research, and medical imaging solutions, particularly in pneumonia detection and COVID-19 case prediction—fields where health, technology, and engineering effectively converge. Throughout her career, Assoc. Prof. Dr. Ipek Atik has cultivated broad research interests spanning convolutional neural networks, short-term energy forecasting, satellite image classification, landform analysis, LED technologies, renewable energy systems, and advanced material characterization, demonstrating an interdisciplinary approach that strengthens the health and engineering research ecosystem. Her demonstrated research skills include algorithm development, regression learning, deep learning model optimization, transfer learning, optical systems analysis, neural network-based forecasting, materials computation, and the integration of AI with medical and environmental datasets. These skills are strongly supported by her impactful publication record, which has earned awards and honors through high citation counts, international collaborations, and recognition within journals focused on engineering, energy, radiation sciences, and computational technologies. With over 220 citations, an h-index of 8, and an i10-index of 6, Assoc. Prof. Dr. Ipek Atik has established a meaningful global research presence. Her work on CNN-based classification systems, drone detection enhancement, short-term energy load forecasting, and deep learning–supported medical analysis highlights the significant influence of her studies on public health, technological advancement, and industrial applications. The sustained academic output of Assoc. Prof. Dr. Ipek Atik, combined with her dedication to interdisciplinary innovation, positions her as a leading contributor to modern AI-enabled solutions. In conclusion, Assoc. Prof. Dr. Ipek Atik represents a dynamic and forward-focused researcher whose work consistently bridges health, engineering, and artificial intelligence, contributing valuable insights and technologies that support societal progress, scientific advancement, and long-term sustainable development.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

Atik, I. (2022). Classification of electronic components based on convolutional neural network architecture. 39 citations.
Atik, I. (2022). A new CNN-based method for short-term forecasting of electrical energy consumption in the COVID-19 period: The case of Turkey. 32 citations.
Dinçer, F., Atik, İ., Yılmaz, Ş., & Çıngı, A. (2017). Hidrolik enerjisinden yararlanmada ülkemiz ve gelişmiş ülkelerin mevcut durumlarının analizi. 26 citations.
Atik, I. (2023). CB-YOLOv5: Enhancing drone detection with BottleneckCSP and cross convolution for improved performance. 16 citations.
Tuncel, N., Akkurt, I., Atik, I., Malidarre, R. B., & Sayyed, M. I. (2024). Neutron-gamma shielding properties of chalcogenide glasses. 11 citations.
Atik, I. (2022). Performance comparison of regression learning methods: COVID-19 case prediction for Turkey. 10 citations.

 

 

Ze Xiang | Structure optimization | Best Researcher Award

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Dr. Ze Xiang | Structure optimization | Best Researcher Award

Dr. Ze Xiang | Structure optimization | Associate professor at Shaoyang University | China

Dr. Ze Xiang is an accomplished scholar in structural engineering whose work integrates advanced computational modelling, bridge structural behavior, and high-performance composite materials, establishing Him as a significant contributor to modern civil infrastructure research. His academic foundation is strengthened by comprehensive engineering education, culminating in doctoral studies completed at a well-recognized institution where He specialized in structural durability, fatigue mechanisms, and innovative construction materials. Over the course of His professional experience, Dr. Ze Xiang has served in academic and research-focused roles at respected institutions, contributing to teaching, mentoring, and collaborative research while participating in cross-institutional and international engineering initiatives that have further enhanced His technical scope and global perspective. His research interests span fatigue crack propagation, XFEM modelling, steel–UHPC composite deck optimization, long-span bridge performance, computational engineering simulations, and structural material behavior under complex loading conditions. Through these research domains, He has developed strong skills in finite element analysis, multi-objective optimization, numerical computation, structural assessment, and performance-based design, alongside proficiency with advanced engineering software and analytical tools widely used in structural engineering research. His contributions are evidenced by His Scopus-indexed publications, consistent citation performance, and growing research influence in the fields of bridge engineering and composite structural systems, while His works published in reputable international journals highlight His analytical depth and problem-solving abilities. In addition to research productivity, Dr. Ze Xiang has earned recognition through institutional honors, research commendations, and academic achievements that reflect His dedication to advancing structural engineering knowledge and contributing impactful solutions to practical engineering challenges. His professional involvement extends to active participation in engineering conferences, collaborative design projects, and cooperative studies that support the development of improved infrastructure systems, while His ability to bridge theoretical research with real-world engineering needs underscores His leadership potential. Overall, Dr. Ze Xiang continues to advance His research portfolio through high-impact studies, interdisciplinary exploration, and technical innovation, demonstrating a strong commitment to expanding the boundaries of structural engineering and contributing meaningfully to global scientific progress, with His future work expected to further enhance structural reliability, sustainability, and engineering innovation.

Academic Profile: Scopus

Featured Publications:

  1. Xiang, Z. (2024). Research on propagation behaviors of fatigue cracks of arc-cutouts in diaphragms based on XFEM. Citations: 1.

  2. Xiang, Z. (2023). Multi-objective optimization of open-ribbed steel-UHPC composite bridge deck based on NSGA-II. Citations: 2.

Qingbing Chang | Robotics | Research Excellence Award

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Assoc. Prof. Dr. Qingbing Chang | Robotics | Research Excellence Award

Assoc. Prof. Dr. Qingbing Chang | Robotics | Associate Professor at Northeast Forestry University | China

Assoc. Prof. Dr. Qingbing Chang is an accomplished researcher whose academic journey reflects deep expertise in piezoelectric actuation, micro–nano positioning, advanced robotics, and precision mechatronic engineering, supported by a strong record of scholarly excellence and international collaboration. With a solid educational foundation culminating in a doctoral degree in mechanical and mechatronic systems from a leading research-focused university, Assoc. Prof. Dr. Qingbing Chang has built a distinguished career through progressive academic appointments, interdisciplinary laboratory leadership, and contributions to high-impact collaborative research teams working across robotics, optical systems, and cross-scale actuation technologies. His professional experience spans advanced design of multi-degree-of-freedom piezoelectric devices, robotic micromanipulation platforms, micro–nano motion control systems, actuator modeling, and precision instrument calibration, allowing Him to contribute both theoretical advancements and engineering innovations to the global research community. His research interests include cross-scale robotic actuation, stick–slip mechanisms, inertial actuation, multi-DOF piezoelectric structures, biologically assisted puncture robotics, optical alignment systems, and intelligent robotic mechanisms, with a consistent focus on improving stiffness, decoupling performance, load capacity, velocity, and accuracy across micro-to-macro motion manipulation platforms. Assoc. Prof. Dr. Qingbing Chang’s research skills encompass system modeling, structural optimization, experimental validation, optical and mechanical integration, microfabrication concepts, and high-precision measurement techniques, enabling Him to produce impactful results published in internationally indexed journals. He has contributed to widely cited works in IEEE Transactions on Industrial Electronics, IEEE Transactions on Robotics, IEEE/ASME Transactions on Mechatronics, Mechanical Systems and Signal Processing, Smart Materials and Structures, and other leading Scopus-indexed engineering journals. His achievements have earned Him academic honors, recognition for innovative piezoelectric actuator development, and respect within research communities through active participation in scholarly networks and contributions to multi-institutional projects. With more than five hundred citations, consistent publication impact, and ongoing collaborations with esteemed researchers from major robotics laboratories, Assoc. Prof. Dr. Qingbing Chang continues to advance the field through high-quality scholarship and engineering innovation. His future trajectory remains strongly oriented toward developing next-generation micro–nano robotic devices, intelligent sensing-actuation platforms, and cross-disciplinary robotic systems that integrate precision engineering, materials science, and artificial intelligence, positioning Him as an influential contributor to future breakthroughs in advanced mechatronic and robotic technologies.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  1. Piezo robotic hand for motion manipulation from micro to macro. (2023). Citation Count: 118.

  2. Design of a precise linear-rotary positioning stage for optical focusing based on the stick-slip mechanism. (2022). Citation Count: 62.

  3. Development of a novel two-DOF piezo-driven fast steering mirror with high stiffness and good decoupling characteristic. (2021). Citation Count: 60.

  4. A simplified inchworm rotary piezoelectric actuator inspired by finger twist: design, modeling, and experimental evaluation. (2023). Citation Count: 55.

  5. Development of a low capacitance two-axis piezoelectric tilting mirror used for optical assisted micromanipulation. (2021). Citation Count: 49.

 

Maria Giovanna Belcastro | Biological Sciences | Women Researcher Award

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Prof. Maria Giovanna Belcastro | Biological Sciences | Women Researcher  Award

Prof. Maria Giovanna Belcastro | Biological Sciences | Professor at Università di Bologna | Italy

Prof. Maria Giovanna Belcastro is a distinguished scholar in Physical Anthropology and Bioarchaeology whose career reflects sustained academic leadership, rigorous methodological innovation, and internationally recognized research excellence. Prof. Maria Giovanna Belcastro completed her higher education and doctoral training in Physical Anthropology at the Alma Mater Studiorum – Università di Bologna, where she ultimately advanced to the position of Full Professor, contributing significantly to the development of osteological, bioarchaeological, and palaeopathological research. Across her academic trajectory, Prof. Maria Giovanna Belcastro has accumulated extensive professional experience through long-term research collaborations, supervision of archaeological and forensic investigations, and participation in major international projects examining population history, disease evolution, skeletal biomechanics, and lifestyle reconstructions in ancient communities. Her research interests encompass entheseal morphology, ageing estimation techniques, palaeopathology, dental anthropology, human skeletal variation, and the bioarchaeology of past populations, with her contributions consistently informing both theoretical frameworks and applied methodologies used in contemporary anthropological analysis. Prof. Maria Giovanna Belcastro possesses strong research skills in skeletal analysis, forensic identification methods, quantitative morphology, standardized scoring system development, and interdisciplinary integration of anthropological, archaeological, and biomedical data. She has produced a substantial body of peer-reviewed work indexed in Scopus and other leading databases, supported by a citation record exceeding 5000 citations with an H-index of 35 and an i10-index of 79, underscoring her influence in the global research community. Her awards and honors include recognitions for her contributions to anthropological sciences, leadership in collaborative excavation projects, and impact on advancing bioarchaeological methodology. She has also held various academic and scientific service roles, including involvement in editorial activities, conference participation, and international network collaborations that promote innovation within the discipline. Her future research trajectory demonstrates strong potential for leading integrative studies that combine osteobiography, paleogenetics, high-resolution imaging, and computational approaches to further enhance understanding of human adaptation, biological stress markers, and health transitions across historical periods. Overall, Prof. Maria Giovanna Belcastro’s sustained scholarly productivity, international research presence, and commitment to advancing anthropological science firmly establish her as a leading expert in her field and a highly deserving candidate for academic recognition.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  1. Mariotti, V., Facchini, F., & Belcastro, M. G. (2007). The study of entheses: Proposal of a standardised scoring method for twenty-three entheses of the postcranial skeleton. 431 citations.

  2. Mariotti, V., Facchini, F., & Belcastro, M. G. (2004). Enthesopathies: Proposal of a standardized scoring method and applications. 399 citations.

  3. Cameriere, R., Ferrante, L., Belcastro, M. G., Bonfiglioli, B., Rastelli, E., et al. (2007). Age estimation by pulp/tooth ratio in canines by peri-apical X-rays. 348 citations.

  4. Milella, M., Belcastro, M. G., Zollikofer, C. P. E., & Mariotti, V. (2012). The effect of age, sex, and physical activity on entheseal morphology in a contemporary Italian skeletal collection. 236 citations.

  5. Belcastro, G., Rastelli, E., Mariotti, V., Consiglio, C., Facchini, F., et al. (2007). Continuity or discontinuity of lifestyle in central Italy during the Roman Imperial–Early Middle Ages transition: Diet, health, and behavior. 211 citations.

 

 

Gary Wong | Computer Science | Best Researcher Award

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Prof. Dr. Gary Wong | Computer Science | Best Researcher Award

Prof. Dr. Gary Wong | Computer Science | The University of Hong Kong | Hong Kong

Prof. Dr. Gary Wong is a highly accomplished scholar in computer science education whose research contributions have significantly influenced the fields of computational thinking, digital literacy, technology-enhanced learning, and K–12 AI education. With a strong academic foundation supported by advanced degrees from leading institutions, his educational background reflects rigorous training in both pedagogy and computer science, enabling Him to bridge disciplinary boundaries with expertise and innovation. Throughout his professional career, Prof. Dr. Gary Wong has held key academic and leadership roles, contributing to major international research initiatives, collaborating with renowned global scholars, and publishing impactful studies that guide educational technology policies and classroom practices. His research interests encompass computational thinking development, digital literacy assessment, educational data analysis, teacher professional development, AI-in-education integration, and immersive learning design, and he demonstrates strong methodological skills in both qualitative and quantitative research approaches. His scholarly output includes numerous Scopus-indexed and IEEE publications that are extensively cited worldwide, shaping frameworks for digital skills assessment, pedagogical innovation, and technology adoption among educators. His research skills include large-scale data analysis, cross-cultural educational research, experimental design, research instrument development, and systematic reviews with meta-analytic rigor. Prof. Dr. Gary Wong has received multiple recognitions and honors for academic excellence, peer-review contributions, and impactful research, reflecting his prominence in the global education technology community. He has collaborated with leading universities and contributed to funded international research projects focused on curriculum innovation and computational thinking education. Additionally, he is actively involved in academic service, editorial review roles, and professional memberships in major associations such as IEEE and ACM, demonstrating strong engagement with scholarly communities and educational leadership. His substantial citation metrics further reflect the global influence of his work across multiple research domains. In conclusion, Prof. Dr. Gary Wong stands out as a leading expert whose research excellence, innovative contributions, and strong academic leadership continue to advance the global understanding of technology-enhanced learning and computational thinking education, positioning Him as a driving force for future advancements in education research worldwide.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  1. A global framework of reference on digital literacy skills for indicator 4.4.2. (2018). Citation Count: 662

  2. Broadening artificial intelligence education in K-12: Where to start? (2020). Citation Count: 294

  3. Designing unplugged and plugged activities to cultivate computational thinking: An exploratory study in early childhood education. (2020). Citation Count: 260

  4. Exploring children’s perceptions of developing twenty-first century skills through computational thinking and programming. (2020). Citation Count: 153

  5. The behavioral intentions of Hong Kong primary teachers in adopting educational technology. (2016). Citation Count: 149

 

 

Faisal Mehmood | Cybersecurity | Publication Excellence Award

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Dr. Faisal Mehmood | Cybersecurity | Publication Excellence Award

Dr. Faisal Mehmood | Cybersecurity | Research Assistant at Guangxi Minzu University | China

Dr Faisal Mehmood earned his Ph.D. in Mathematics from Beijing Institute of Technology. He currently serves as Lecturer at Guangxi Minzu University (China), after previously working as Assistant Professor at the Institute of Space Technology. His research interests lie in fuzzy algebra, fuzzy vector spaces, fuzzy rings, fuzzy decision-making models, and applications of fuzzy mathematics to computational and security problems. He is experienced in developing novel mathematical frameworks — for example, generalizing classical vector spaces to “M-hazy” vector spaces over “M-hazy” fields — and in applying such theoretical developments to real-world problems like multi-attribute decision making and cybersecurity (e.g., closed-loop time-delay feedback control systems for DDoS mitigation). His research skills include abstract algebra, fuzzy set theory, formal proof construction, fuzzy aggregation operator design, and interdisciplinary application bridging mathematics with computer security. Among his honours, his work has been accepted by peer-reviewed international journals, and some of his papers have attracted citations in the mathematical and computational literature. Through his publications and employment history, Dr Mehmood has demonstrated a balance of rigorous theoretical research and applied problem-solving, contributing to both the foundations of fuzzy algebra and its computational applications. He is also connected to international academic networks, and his ORCID profile ensures traceability of his scholarly record. In conclusion, Dr Mehmood is a promising and productive mathematician whose combination of strong algebraic expertise, research versatility, and commitment to applied interdisciplinary work position him as a valuable candidate for further research funding or awards.

Academic Profile: ORCID | Scopus

Featured Publications:

Mehmood, F., & Shi, F.-G. (2021). M-Hazy Vector Spaces over M-Hazy Field. Mathematics, 9(10), 1118. (Cited by 3)

Mehmood, F., & Liu, H. (2024). Some Complex Picture Fuzzy Aggregation Operators Based on Frank t-norm and t-conorm: An Application to Multi-Attribute Decision-Making (MADM) Process. Computing Open. (Cited by 1)

Mehmood, F., Huang, K., Wang, L., & Liu, J. (2025). Design and Implementation of a Closed Loop Time Delay Feedback Control (CLTD-FC) System for Mitigating DDoS Attacks. Computers & Security.

 

 

Luis Minchala | Disaster Medicine | Outstanding Scientist Award

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Prof. Luis Minchala | Disaster Medicine | Outstanding Scientist Award

Prof. Luis Minchala | Disaster Medicine | Universidad de Cuenca | Ecuador

Prof Luis Ismael Minchala is a highly accomplished researcher whose academic and professional career reflects sustained excellence in advanced control systems, renewable energy integration, and intelligent automation technologies, establishing him as a leading scholar in electrical and electronic engineering. Prof Luis Ismael Minchala completed his higher education with a strong focus on control engineering and digital systems, advancing toward doctoral-level research in intelligent control of microgrids and high-performance embedded platforms, which laid the foundation for his notable contributions to energy management, UAV control, cyber-physical systems, and smart industrial infrastructures. Professionally, Prof Luis Ismael Minchala has served in key academic and research roles, contributing significantly to the development of engineering programs, supervising graduate theses, engaging in multidisciplinary research, and collaborating widely with international partners from Canada, Finland, Mexico, and across Latin America. His research interests span renewable energy systems, microgrid stability, fault-tolerant control, robust optimization, real-time embedded automation, UAV tracking, intelligent SCADA architectures, and IoT-based sensing technologies. Prof Luis Ismael Minchala possesses strong research skills including advanced modeling and simulation, optimal and predictive control design, digital signal processing, algorithm development, system identification, experimental prototyping, and data-driven control strategies supported by state-of-the-art computational tools. His diverse expertise is reflected in numerous high-impact publications indexed in IEEE, Scopus, and top interdisciplinary journals. Prof Luis Ismael Minchala has earned recognition for his scientific impact, evidenced by more than one thousand citations, a strong h-index, and extensive international co-authorship with leading experts including IEEE Fellows. His work has also contributed to major funded research initiatives related to smart energy systems, optimization of microgrid operations, and advanced sensing for industrial automation. Throughout his career, Prof Luis Ismael Minchala has been honored for academic excellence, innovative research output, community engagement in engineering education, and leadership in collaborative scientific projects. His awards and distinctions highlight his dedication to advancing engineering solutions that support sustainable energy systems and modern industrial technologies. In conclusion, Prof Luis Ismael Minchala stands out as a distinguished researcher whose contributions continue to shape the future of renewable energy integration, intelligent control systems, and digital industrial innovation, demonstrating a clear trajectory of high-impact scholarship, strong technical competence, and promising future potential in global research leadership.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  1. Minchala-Avila, L. I., Garza-Castañón, L. E., Vargas-Martínez, A., & Zhang, Y. (2015). A review of optimal control techniques applied to the energy management and control of microgrids. Citations: 177.

  2. Minchala-Avila, L. I., Garza-Castañon, L., Zhang, Y., & Ferrer, H. J. A. (2016). Optimal energy management for stable operation of an islanded microgrid. Citations: 110.

  3. Ortiz, J. P., Minchala, L. I., & Reinoso, M. J. (2016). Nonlinear robust H-infinity PID controller for the multivariable system quadrotor. Citations: 102.

  4. Reinoso, M. J., Minchala, L. I., Ortiz, P., Astudillo, D. F., & Verdugo, D. (2016). Trajectory tracking of a quadrotor using sliding mode control. Citations: 93.

  5. Yu, B., Zhang, Y., Minchala, I., & Qu, Y. (2013). Fault-tolerant control with linear quadratic and model predictive control techniques against actuator faults in a quadrotor UAV. Citations: 75.