Hisham AbouGrad | Artificial intelligence | Best Academic Researcher Award

Dr. Hisham AbouGrad | Artificial intelligence | Best Academic Researcher Award

Dr. Hisham AbouGrad , Senior Lecturer , University of East London – UEL , United Kingdom.

Dr. Hisham AbouGrad is a dynamic academic and industry expert in computer science and digital technologies. Currently a Senior Lecturer at the University of East London, he brings over two decades of experience in higher education and IT. Known for bridging theory with practice, he has supervised innovative projects in AI, FinTech, and mobile app development. Dr. AbouGrad also leads international academic collaborations and contributes to top-tier journals. He is a Fellow of the Higher Education Academy and an active member of the British Computer Society, with a passion for enhancing digital learning, scientific problem-solving, and sustainable technology.

Publication Profile

Scopus

ORCID

Google scholar

🎓 Education Background

Dr. Hisham AbouGrad earned his Doctorate in Professional Studies (DProf) from London South Bank University, focusing on Workflow Information Systems Performance using BPM methodologies. He also holds a Master of Science (MSc) in Software Engineering from the University of Bradford and a Master of Business Administration (MBA) in Management from the University of Lincoln. Additionally, he completed a Postgraduate Certificate in Higher Education Practice (PGCHEP) from the University of Plymouth. His academic credentials are enhanced by certifications in project management and IT, including CITP from BCS and PMP qualifications, reinforcing his foundation in both pedagogy and technical leadership.

💼 Professional Experience

Dr. AbouGrad’s career spans prestigious academic institutions and industry roles. Since 2021, he has served as a Senior Lecturer at the University of East London, where he also fosters international collaborations. Previously, he held teaching and leadership roles at ICON College, QA Higher Education, GSM London, and the University of Plymouth. From 2011 to 2019, he was a doctoral researcher at London South Bank University. With vast teaching experience in computing, business management, and information systems, Dr. AbouGrad has mentored numerous PhD and DProf students while shaping curricula aligned with technological advancements and practical industry applications.

🏆 Awards and Honors

Dr. Hisham AbouGrad has been recognized for his commitment to academic excellence and professional contribution. He is a Fellow of the UK Higher Education Academy (FHEA), a Certified IT Professional (CITP) with the British Computer Society (BCS), and has received qualifications in IT Quality Management (ITQM). He is a founding member of UEL’s FinTech Centre and contributes actively to academic committees and journal editorial boards. As a reviewer for reputed journals like IEEE TCE, SAGE, Elsevier, and Emerald, he consistently upholds research quality, earning professional credibility and trust in the global academic and scientific communities.

🔬 Research Focus

Dr. AbouGrad’s research integrates Artificial Intelligence, FinTech, Machine Learning, Information Security, and Multi-Criteria Decision Making (MCDM) with Business Process Management (BPM) and Workflow Systems. His work aims to create scalable, secure, and intelligent digital solutions. Projects under his supervision include AI-based financial prediction systems, eCommerce fraud detection using neural networks, and mobile payment technologies. His recent studies explore AI-driven stock prediction, sentiment analysis, and fake review detection—highlighting his goal to solve real-world problems through data science, machine learning, and performance analysis. He also researches Decision Support Systems (DSS), ECM, GIS, and user-centered eCommerce design.

🔚 Conclusion

Dr. Hisham AbouGrad is a passionate educator, strategic researcher, and technology advocate whose career is marked by innovation, collaboration, and impact. His multifaceted expertise across academia and industry supports students, institutions, and global communities in adapting to digital transformation. Through research, mentorship, and leadership, he contributes to solving complex challenges in AI, FinTech, and Information Systems. With a forward-thinking mindset, he continues to influence academic practices, elevate IT performance, and foster global academic relationships. His legacy reflects both the rigor of scholarly inquiry and the relevance of applied science in the 21st century.

📚 Top Publications with Details

  1. AI-Framework to Detect eCommerce Fake Reviews: A Hybrid Neural Network Machine Learning Model
    Published: 2024, Book: Artificial Intelligence and Computational Technologies
    Cited by: 1

  2. Financial Decision-Making AI-Framework to Predict Stock Price Using LSTM Algorithm and NLP-Driven Sentiment Analysis Model
    Published: 2025, Conference: Annual International Congress on Computer Science
    Cited by: 1

  3. Decision Making by Applying Machine Learning Techniques to Mitigate Spam SMS Attacks
    Published: 2023, Conference: International Conference on Deep Learning, Artificial Intelligence and Robotics
    Cited by: 5

  4. Developing the Business Process Management Performance of an Information System Using the Delphi Study Technique
    Published: 2019, Conference: EAI International Conference on Technology, Innovation, Entrepreneurship and Education
    Cited by: 5

  5. Applying the Delphi Method to Measure Enterprise Content Management Workflow System Performance
    Published: 2022, Journal: Lecture Notes in Networks and Systems (Springer)
    Cited by: 1

  6. The Impact of Business Process Management Values on Enterprise Content Management Workflow Systems Performance
    Published: 2020, Thesis: London South Bank University
    Cited by: 1

  7. Intelligent Computing, Proceedings of the 2022 Computing Conference
    Published: 2022, Publisher: Springer International Publishing
    Cited by: 23

  8. Key Digital Trends in Artificial Intelligence and Robotics: Proceedings of ICDLAIR 2022
    Published: 2023, Publisher: Springer International Publishing
    Cited by: 1

 

Ms. Elahe Rahmani Samani | Artificial Intelligence | Young Researcher Award

Ms. Elahe Rahmani Samani | Artificial Intelligence | Young Researcher Award

Ms. Elahe Rahmani Samani, Undergraduate Researcher, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.

Ms. Elahe Rahmani Samani is a dedicated undergraduate researcher in Healthcare Management at Shahid Sadoughi University of Medical Sciences, Yazd, Iran. With a strong commitment to advancing health systems through innovative technologies, she has emerged as a promising young voice in the intersection of healthcare and artificial intelligence. As the corresponding author of a high-impact study published in the International Journal of Medical Informatics, she has already gained visibility on an international platform. Elahe is also an editorial board member of a university-affiliated journal and actively engages in research collaboration, demonstrating leadership and academic excellence early in her career.

Publication Profile

ORCID

🎓 Education Background

Ms. Elahe Rahmani Samani is currently pursuing her undergraduate degree in Healthcare Management at Shahid Sadoughi University of Medical Sciences in Yazd, Iran. Her academic journey has been marked by an early passion for healthcare innovation and policy development. As a student member of the Health Policy and Management Research Center, she has access to extensive research mentorship and academic resources, which support her pursuits in AI integration in health systems. Her education equips her with both practical management knowledge and technical understanding essential for modern health leadership. She continues to excel academically, contributing meaningfully to her institution’s research mission.

💼 Professional Experience

Although still an undergraduate student, Ms. Rahmani Samani has demonstrated remarkable initiative by leading and collaborating on several research projects. Her standout experience includes serving as the primary researcher and corresponding author for a study on AI adoption in hospital settings, presented at the International Congress on Artificial Intelligence in Health. She also serves on the editorial board of a university-affiliated journal, where she helps shape academic content for peer learning. Elahe’s active involvement in health systems projects, poster sessions, and ongoing collaborations reflect her deep engagement with practical and theoretical aspects of healthcare management.

🏆 Awards and Honors

While formal awards are yet to be recorded due to her early stage in academia, Ms. Elahe Rahmani Samani has achieved significant recognition by publishing in a Scopus-indexed journal and presenting at an international congress. She earned certificates of participation from the International Congress on Artificial Intelligence in Health and is continuously contributing to scholarly work in health systems. Her selection for the editorial board role and involvement in a university-level book project highlight the academic community’s acknowledgment of her talents. Her publication is already accessible through global platforms and is poised to gain academic citations in the near future.

🔬 Research Focus

Elahe Rahmani Samani’s research interests revolve around hospital and healthcare management, particularly in leveraging artificial intelligence to optimize health systems for both patients and staff. She has successfully completed one major research project that analyzes hospital managers’ perspectives on AI integration—an innovative topic reflecting current global trends. Her work aims to influence strategic decision-making within health institutions by promoting the adoption of intelligent systems. She is also contributing to an ongoing book project in healthcare management and continues to work on four other health-related research studies, exploring themes of efficiency, technology adoption, and patient-centered care in health policy.

🧭 Conclusion

Ms. Elahe Rahmani Samani exemplifies the drive and intellect of a next-generation healthcare researcher. Her early publication in a high-impact journal and involvement in both local and international academic platforms underscore her potential to become a leader in the field. With a unique blend of management insight and technological perspective, she aims to transform how healthcare institutions approach innovation. Her commitment to research excellence, combined with her growing professional network and academic contributions, positions her as a strong contender for the Young Researcher Award. Her journey is only beginning, and she is already contributing to global discussions in health innovation.

📚 Top Publication Note

Title: Managers’ perceptions and attitudes toward the use of artificial intelligence technology in selected hospital settings
Authors: Mousavi SM, RahmaniSamani E, Raadabadi M, DehghaniTafti A
Journal: International Journal of Medical Informatics
Year: 2025

Lirong Wang | Artifical Intelligence | Best Researcher Award

Ms. Lirong Wang | Artifical Intelligence | Best Researcher Award

professor at Suzhou University, China

Professor Lirong Wang is a distinguished researcher at Soochow University, specializing in intelligent wearable devices and information processing. She earned her B.S. and Ph.D. from Jilin University and has been serving as a professor since 2014. Her research integrates microelectronics, machine learning, and biomedical engineering, with a strong focus on signal acquisition and analysis. Professor Wang leads several interdisciplinary projects and supervises graduate students, fostering innovation and academic growth. As the Principal Investigator of a National Key R&D Program, she demonstrates outstanding leadership in advancing cutting-edge technologies. She has authored over 40 peer-reviewed publications in prestigious journals such as IEEE Transactions on Biomedical Engineering and holds more than 20 invention patents, highlighting her contributions to both academic research and practical innovation. In addition to her research work, she actively participates in the global scientific community as a journal reviewer and organizer of international conference sessions in wearable technology and computer science.

Publication Profile

Education🎓

Professor Lirong Wang received her formal education at Jilin University, one of China’s premier institutions, where she earned both her Bachelor of Science (B.S.) and Doctor of Philosophy (Ph.D.) degrees. Her academic training focused on electronic engineering and information processing, laying a strong foundation for her specialization in intelligent wearable devices. Throughout her educational journey, she developed expertise in signal acquisition technologies, microelectronics, and data analysis, which later became the core pillars of her research. During her Ph.D. studies, Professor Wang engaged in interdisciplinary work that bridged engineering, computer science, and biomedical applications, positioning her at the forefront of next-generation health monitoring technologies. Her rigorous academic background and commitment to research excellence have equipped her with the analytical skills and innovative mindset needed to lead complex scientific projects. This strong educational grounding has played a pivotal role in shaping her successful academic and research career at Soochow University.

Professional Experience 💼

Professor Lirong Wang has built a robust professional career centered on interdisciplinary research and academic leadership. Since 2014, she has served as a professor at Soochow University, where she specializes in intelligent wearable devices, signal acquisition, and biomedical information processing. Her professional experience spans leading national-level R&D programs and supervising numerous graduate students, fostering innovation in both academia and applied technology. As the Principal Investigator of a National Key Research and Development Program, she has demonstrated exceptional capability in managing large-scale, collaborative research projects. Professor Wang has authored over 40 peer-reviewed publications and holds more than 20 invention patents, reflecting a strong commitment to both theoretical advancement and technological innovation. Beyond her university role, she contributes to the global research community as a reviewer for prestigious journals and an organizer of international conference sessions, particularly in wearable technology and computer science. Her experience reflects a deep integration of research, mentorship, and scientific engagement.

Research Interest 🔬

Professor Lirong Wang has a diverse and forward-thinking research portfolio centered on the development and application of intelligent wearable devices and biomedical information processing. Her primary interests lie in signal acquisition technology, physiological data analysis, and the integration of machine learning with microelectronic systems for real-time health monitoring and diagnostics. She is particularly focused on designing wearable platforms capable of accurately capturing and interpreting complex biological signals, such as ECG and EMG, to support early disease detection and personalized healthcare. Her interdisciplinary approach merges principles from biomedical engineering, computer science, and electrical engineering, creating practical solutions for next-generation health technologies. Additionally, she explores low-power sensor systems, data fusion algorithms, and human-computer interaction interfaces within wearable technologies. Professor Wang’s research aims to bridge the gap between theoretical modeling and real-world applications, ultimately enhancing the reliability and usability of wearable systems in clinical, athletic, and daily life settings.

Research Skill🔎

Professor Lirong Wang possesses a comprehensive set of research skills that reflect her expertise in intelligent wearable technology, biomedical engineering, and data-driven signal processing. She is highly skilled in designing and developing advanced wearable systems, with a strong command of microelectronic circuit design, sensor integration, and embedded system programming. Her proficiency in signal acquisition and processing allows her to extract meaningful insights from complex physiological data such as ECG, EMG, and PPG. She is also adept at applying machine learning algorithms for pattern recognition, anomaly detection, and predictive modeling in healthcare applications. In addition, she demonstrates expertise in managing interdisciplinary research teams, coordinating large-scale projects, and supervising graduate-level research. Professor Wang is experienced in securing research funding, particularly as a Principal Investigator on national R&D initiatives. Her ability to bridge theoretical knowledge with practical innovation highlights her strong analytical, experimental, and collaborative research capabilities across multiple scientific domains.

Award and Honor🏆

Professor Lirong Wang has received several prestigious awards and honors in recognition of her outstanding contributions to research and innovation in the fields of intelligent wearable devices and biomedical engineering. As the Principal Investigator of a National Key R&D Program, she has been recognized at the national level for her leadership and scientific excellence. Her pioneering work has earned accolades from academic institutions and government agencies, including awards for Technological Innovation and Excellence in Research. She has also been honored for her contributions to patent development, with over 20 invention patents credited to her name, many of which have led to real-world applications. Professor Wang’s high-impact publications in leading journals such as IEEE Transactions on Biomedical Engineering have further contributed to her reputation as a top researcher. Additionally, she has received invitations to serve as a reviewer and session chair at international conferences, reflecting her respected status in the global scientific community.

Conclusion📝

Professor Lirong Wang is highly suitable for the Best Researcher Award. His sustained contributions to interdisciplinary research, innovation through patents, and leadership in national research programs mark him as a leading figure in the field of intelligent wearable devices and biomedical engineering. With some enhancement in international collaboration and outreach, his profile stands as exemplary in both academic and practical domains.

Publications Top Noted📚

  • End-to-End ECG Signal Compression Based on Temporal Information and Residual Compensation

    • Year: 2025

    • Journal: Circuits, Systems, and Signal Processing

  • QRS Wave Detection Algorithm of Dynamic ECG Signal Based on Improved U-Net Network

    • Year: 2025

    • Journal: ICIC Express Letters, Part B: Applications

  • TrCL-AGS: A Universal Sequential Triple-Stage Contrastive Learning Framework for Bacterial Detection With Across-Growth-Stage Information

    • Year: 2025

    • Journal: IEEE Internet of Things Journal

  • Multi-label Few-Shot Classification of Abnormal ECG Signals Using Metric Learning

    • Year: 2025

    • Journal: Circuits, Systems, and Signal Processing

  • Automated Deep Learning Model for Sperm Head Segmentation, Pose Correction, and Classification (Open Access)

    • Year: 2024

    • Journal: Applied Sciences (Switzerland)

  • Instance Segmentation of Mouse Brain Scanning Electron Microscopy Images Based on Fine-Tuning Nature Image Model

    • Year: 2024

    • Journal: Guangxue Jingmi Gongcheng / Optics and Precision Engineering

    • Citations: 1

  • Multi-label Classification of Arrhythmia Using Dynamic Graph Convolutional Network Based on Encoder-Decoder Framework

    • Year: 2024

    • Journal: Biomedical Signal Processing and Control

    • Citations: 4

  • Two-Stage Error Detection to Improve Electron Microscopy Image Mosaicking

    • Year: 2024

    • Journal: Computers in Biology and Medicine

    • Citations: 2

Dr. Keyong Hu | artificial intelligence | Best Researcher Award

Dr. Keyong Hu | artificial intelligence | Best Researcher Award

Teacher, Hangzhou Normal University, China

Dr. KeYong Hu is an accomplished academic and researcher specializing in artificial intelligence and new energy technology. He earned his Ph.D. from the Zhejiang University of Technology in 2016 and is currently serving as an Associate Professor at Hangzhou Normal University, within the School of Information Science and Technology. Dr. Hu has contributed significantly to the intersection of AI and energy systems, with numerous publications in international journals, showcasing his expertise in predictive modeling and intelligent optimization.

Publication Profile

ORCID

🎓 Education Background

Dr. KeYong Hu completed his doctoral studies at the Zhejiang University of Technology, Hangzhou, China, where he received his Ph.D. in 2016. His academic training laid a strong foundation in computational intelligence and energy-related engineering applications.

💼 Professional Experience

Dr. Hu holds the position of Associate Professor at Hangzhou Normal University, Hangzhou, Zhejiang, China, affiliated with the School of Information Science and Technology. He has been actively involved in teaching, mentoring, and high-impact research since earning his doctorate.

🏆 Awards and Honors

While specific awards are not listed, Dr. Hu’s prolific publishing record in top-tier peer-reviewed journals like Mathematics, Heliyon, Sustainability, and Computers and Electrical Engineering underscores his recognition and influence in the fields of AI and energy optimization.

🔬 Research Focus

Dr. Hu’s research centers on the integration of artificial intelligence with new energy technologies, particularly photovoltaic power forecasting, energy system optimization, and cross-modal data analysis. His innovative use of algorithms such as Copula functions, Transformers, and Dung Beetle Optimization showcases his depth in AI-driven energy analytics.

✅ Conclusion

Dr. KeYong Hu stands out as a forward-thinking researcher contributing impactful work at the intersection of artificial intelligence and sustainable energy. Through his academic leadership and research contributions, he continues to shape the future of intelligent energy systems in China and beyond. 🌍📈

📚 Top Publications 

🔗 Two-Stage Distributionally Robust Optimal Scheduling for Integrated Energy Systems Considering Uncertainties in Renewable Generation and Loads
Journal: Mathematics | Year: 2025
Cited by: Check on Google Scholar

🔗 Short-term Photovoltaic Forecasting Model with Parallel Multi-Channel Optimization Based on Improved Dung Beetle Algorithm
Journal: Heliyon | Year: 2024
Cited by: Check on Google Scholar

🔗 Distributed Regional Photovoltaic Power Prediction Based on Stack Integration Algorithm
Journal: Mathematics | Year: 2024
Cited by: Check on Google Scholar

🔗 Automatic Depression Prediction via Cross-Modal Attention-Based Multi-Modal Fusion in Social Networks
Journal: Computers and Electrical Engineering | Year: 2024
Cited by: Check on Google Scholar

🔗 Short-Term Photovoltaic Power Generation Prediction Based on Copula Function and CNN-CosAttention-Transformer
Journal: Sustainability | Year: 2024
Cited by: Check on Google Scholar

Dr. Saikat Gochhait | Artificial Intelligence | Best Researcher Award

Dr. Saikat Gochhait | Artificial Intelligence | Best Researcher Award

Assistant Professor, Symbiosis International (Deemed to be University), India

Dr. Saikat Gochhait is an accomplished Indian academic, researcher, and innovator, currently serving as an Assistant Professor at Symbiosis International Deemed University, Pune. With a strong background in management, information technology, and behavioral sciences, he also contributes as a Research Team Member at the Symbiosis Centre for Behavioral Sciences and Adjunct Faculty at the Neuroscience Research Institute, Samara State Medical University, Russia. He is a prolific inventor with several published patents and has been recognized for his contributions to interdisciplinary research in artificial intelligence, neuroscience, and optimization algorithms.

Publication Profile

🎓 Education Background

Dr. Gochhait earned his Doctor of Philosophy (Ph.D.) in Management from Sambalpur University in 2014 🧠, a Master’s in Business Management from the same university in 2009 📊, and a Master’s in Information Technology from Sikkim Manipal University in 2017 💻. His diverse academic training has laid a multidisciplinary foundation that supports his cross-functional research across business, IT, and neuroscience domains.

💼 Professional Experience

With over two decades of experience spanning academia and industry, Dr. Gochhait has held key roles such as Assistant Professor at ASBM University, Khalikote University, and HOD at Sambhram Institute of Technology. His industry experience includes strategic roles at IFGL Refractories Ltd. and Tata Krosaki Refractories Ltd. Currently, at Symbiosis International University, he mentors postgraduate and doctoral students, manages AI-centric research projects, and continues collaborative ventures with prestigious institutions including IIT Roorkee and international universities 🌏.

🏆 Awards and Honors

Dr. Gochhait has been honored as a Senior Member of IEEE in 2019 and recognized by the Alpha Network of the Federation of European Neuroscience Societies in 2024 🌟. His academic excellence has earned him international research fellowships from leading institutions, including the Natural Sciences and Engineering Research Council of Canada, Samara State Medical University (Russia), National Dong Hwa University (Taiwan), and the University of Deusto (Spain), with total grants exceeding USD 20,000 💰.

🔬 Research Focus

Dr. Gochhait’s research is rooted in artificial intelligence, behavioral science, energy prediction, bio-inspired optimization algorithms, and neuroscience-enhanced technology applications 🧬. He is a principal investigator of high-impact government-funded projects such as AI-based load forecasting for dispatch centers and BCI-integrated neurofeedback games. His innovations also extend to smart agriculture and transport systems, reflecting his dedication to societal improvement through technology 🤖🌱.

✅ Conclusion

Blending visionary academic pursuit with innovative problem-solving, Dr. Saikat Gochhait continues to drive global research collaborations, mentor emerging scholars, and contribute meaningful technological solutions to real-world challenges 📚🌍. His evolving body of work bridges disciplines, industries, and nations, making him a respected figure in AI, management, and neuroscience research.

📚 Top Publications

Pufferfish Optimization Algorithm: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems
Biomimetics, 2024Indexed in Scopus/WoS
Cited by: 12 articles

Dollmaker Optimization Algorithm: A Novel Human-Inspired Optimizer for Solving Optimization Problems
International Journal of Intelligent Engineering and Systems, 2024Indexed in Scopus
Cited by: 9 articles

Addax Optimization Algorithm: A Novel Nature-Inspired Optimizer for Solving Engineering Applications
International Journal of Intelligent Engineering and Systems, 2024Indexed in Scopus
Cited by: 7 articles

Enhancing Household Energy Consumption Predictions Through Explainable AI Frameworks
IEEE Access, 2024 – Indexed in Scopus/WoS
Cited by: 15 articles

URL Shortener for Web Consumption: An Extensive and Impressive Security Algorithm
 Indonesian Journal of Electrical Engineering and Computer Science, 2024Indexed in Scopus
 Cited by: 6 articles

Dr. Biao Zhang | Technology | Best Researcher Award

Dr. Biao Zhang | Technology | Best Researcher Award

Xi’an Research Institute of High-Tech, China

Zhang Biao is a promising doctoral student specializing in Nuclear Science and Technology at the PLA Rocket Force Engineering University, Xi’an, China. With a focus on advancing safety and efficiency in nuclear environments, his research emphasizes radiation field reconstruction and dose-optimized path planning. He has authored multiple peer-reviewed articles in top-tier journals like Annals of Nuclear Energy and Nuclear Technology. Zhang’s contributions to computational modeling and intelligent algorithms mark him as an emerging innovator in his field 🧠⚛️.

Publication Profile

ORCID

🎓 Education Background:

Zhang Biao pursued his higher education at the esteemed PLA Rocket Force Engineering University in Xi’an, Shaanxi, China 🎓. Currently engaged in his doctoral studies, his academic journey is rooted in nuclear science with an inclination toward computational applications in radiation detection and safety mechanisms.

💼 Professional Experience:

Although still in academia, Zhang has demonstrated notable professional-level impact through his published works. He is affiliated with the Xi’an Research Institute of High-Tech and is a proud member of the Chinese Nuclear Society 🧪. His hands-on experience with mathematical modeling and radiation path optimization contributes to future applications in nuclear facility safety.

🏆 Awards and Honors:

While formal accolades are pending, Zhang’s scholarly output—particularly his recent algorithmic improvements in radiation path planning—have earned recognition in high-impact journals and among nuclear technology scholars. His nomination for the Best Researcher Award by the Computer Scientists Awards underscores his rising prominence in scientific research 🥇📚.

🔬 Research Focus:

Zhang Biao’s work revolves around enhancing the safety of radiation environments through efficient detection and computational path planning. His innovations include a modified A* algorithm for minimizing radiation dose exposure and improved reconstruction techniques for gamma-ray source fields using interpolation and mathematical modeling 🔍🛰️.

🔚 Conclusion:

Zhang Biao represents the new generation of nuclear technologists who integrate artificial intelligence with radiation safety science. With multiple first-author publications, innovative algorithms, and a clear vision for nuclear safety, he is well on track to make substantial contributions to science and society 🌏💡.

📚 Top Publications:

A modified A* algorithm for path planning in the radioactive environment of nuclear facilitiesAnnals of Nuclear Energy, 2025.
Cited by: Referenced in dose optimization and nuclear safety path planning studies.

Path planning of PRM based on artificial potential field in radiation environmentsAnnals of Nuclear Energy, 2024.
Cited by: Utilized in advanced robotics navigation within hazardous nuclear zones.

Minimum dose walking path planning in a nuclear radiation environment based on a modified A* algorithmAnnals of Nuclear Energy, 2024.
Cited by: Recognized for efficient personnel routing in nuclear facilities.

A comparative study of different radial basis function interpolation algorithms in the reconstruction and path planning of γ radiation fieldsNuclear Engineering and Technology, 2024.
Cited by: Referenced in computational gamma field modeling research.

Reconstruction of γ Dose Rate Field and Algorithm Validation Based on Inverse Distance Weight InterpolationNuclear Technology, 2024.
Cited by: Applied in gamma dose field reconstruction validations.

Sikandar Ali | Artificial Intelligence Award | Best Researcher Award

Dr. Sikandar Ali | Artificial Intelligence Award | Best Researcher Award

Postdoc Fellow, Inje University, South Korea

🎓 Sikandar Ali is a passionate AI researcher and educator specializing in Artificial Intelligence applications in healthcare. Currently pursuing a PhD at Inje University, South Korea, he has a strong academic background and extensive research experience in digital pathology, medical imaging, and machine learning. As a team leader of the digital pathology project, he develops innovative AI algorithms for cancer diagnosis while collaborating with a global team of researchers. Sikandar is a recipient of prestigious scholarships, accolades, and recognition for his contributions to AI and healthcare innovation.

Publication Profile

Google Scholar

Education

📘 Sikandar Ali holds a PhD in Artificial Intelligence in Healthcare (CGPA: 4.46/4.5) from Inje University, South Korea, where his thesis focuses on integrating pathology foundation models with weakly supervised learning for gastric and breast cancer diagnosis. He earned an MS in Computer Science from Chungbuk National University, South Korea (GPA: 4.35/4.5), with research on AI-based clinical decision support systems for cardiovascular diseases. His undergraduate degree is a Bachelor of Engineering in Computer Systems Engineering from Mehran University of Engineering and Technology, Pakistan, with a CGPA of 3.5/4.0.

Experience

💻 Sikandar is an experienced researcher and AI specialist. Currently working as an AI Research Assistant at Inje University, he focuses on cutting-edge projects in digital pathology, cancer detection, and medical imaging. Previously, he worked as a Research Assistant at Chungbuk National University, focusing on cardiovascular disease diagnosis using AI. His industry experience includes roles such as Search Expert at PROGOS Tech Company and Software Developer Intern at Hidaya Institute of Science and Technology.

Awards and Honors

🏆 Sikandar has received multiple awards, including the Brain Korean Scholarship, European Accreditation Council for Continuing Medical Education (EACCME) Certificate, and recognition as an outstanding Teaching Assistant at Inje University. He has also earned full travel grants for international conferences, extra allowances for R&D industry projects, and certificates for reviewing research papers in leading journals. Additionally, he is a Guest Editor at Frontiers in Digital Health.

Research Focus

🔬 Sikandar’s research focuses on developing AI algorithms for medical imaging, with expertise in weakly supervised learning, self-supervised learning, and digital pathology. His projects include designing AI systems for cancer detection, COVID-19 prediction, and IPF severity classification. He also works on object detection applications using YOLO models and wearable sensor-based activity detection for pets. His commitment to explainability and interpretability in AI models ensures their practical utility in healthcare.

Conclusion

🌟 Sikandar Ali is a dedicated AI researcher driving innovation in healthcare through artificial intelligence. With his strong educational foundation, diverse research experience, and impactful contributions, he aims to bridge the gap between AI and medicine, making healthcare more efficient and accessible.

Publications

Detection of COVID-19 in X-ray Images Using DCSCNN
Sensors 2022, IF: 3.4

A Soft Voting Ensemble-Based Model for IPF Severity Prediction
Life 2021, IF: 3.2

Metaverse in Healthcare Integrated with Explainable AI and Blockchain
Sensors 2023, IF: 3.4

Weakly Supervised Learning for Gastric Cancer Classification Using WSIs
Springer 2023

Classifying Gastric Cancer Stages with Deep Semantic and Texture Features
ICACT 2024

Computer Vision-Based Military Tank Recognition Using YOLO Framework
ICAISC 2023

Activity Detection for Dog Well-being Using Wearable Sensors
IEEE Access 2022

Cat Activity Monitoring Using Wearable Sensors
IEEE Sensors Journal 2023, IF: 4.3

Deep Learning for Algae Species Detection Using Microscopic Images
Water 2022, IF: 2.9

Comprehensive Review on Multiple Instance Learning
Electronics 2023

Hybrid Model for Face Shape Classification Using Ensemble Methods
Springer 2021

Cervical Spine Fracture Detection Using Two-Stage Deep Learning
IEEE Access 2024

 

Robin Augustine | Artificial Intelligence | Excellence in Research

Assoc. Prof. Dr. Robin Augustine | Artificial Intelligence | Excellence in Research

Associate Professor, Uppsala University, Sweden

🎓 Associate Professor Robin Augustine is a renowned expert in Medical Engineering and Microwave Technology, leading research at Uppsala University in Sweden. He heads the Microwaves in Medical Engineering Group at the Angstrom Laboratory, Department of Electrical Engineering, and serves as an Associate Editor for IET journals. His interdisciplinary work spans medical sensor development, bioelectromagnetic interactions, and innovative in-body communication technologies. Robin has collaborated globally as a visiting professor and researcher, focusing on advancements in medical engineering through impactful research projects.

Publication Profile

Scopus

Education

📚 Dr. Robin Augustine earned his Ph.D. in Electronics and Optronics Systems from Université de Paris Est Marne La Vallée, specializing in human tissue electromagnetic modeling and its implications for medical sensor design. He holds an MSc in Electronics Science with a focus on Robotics from Cochin University of Science and Technology, and a BSc in Electronics Science from Mahatma Gandhi University. His expertise is further strengthened by advanced training in Diagnostic and Therapeutic Applications of Electromagnetics from Politecnico di Torino, Italy.

Experience

💼 Robin’s career includes extensive experience as a senior lecturer and associate professor at Uppsala University, where he has been leading research in microwave applications for medical technology since 2011. He has held visiting professorships and research roles at institutions such as the Beijing Institute of Nanoenergy and Nanosystems and University Medical Center Maastricht, contributing to medical sensor innovation and orthopedic measurement systems. Robin has also worked internationally, including postdoctoral research in France, with expertise in antenna design, bioelectromagnetics, and microwave characterization.

Research Focus

🔬 Robin’s research focuses on medical engineering, bioelectromagnetics, and intra-body communication, including developing microwave-based sensors for diagnosing conditions like osteoporosis, skin cancer, and muscular atrophy. As a leader in the B-CRATOS and COMFORT projects, he explores body-centric technologies and in-body wireless communication to enhance medical diagnostics. His pioneering work addresses the integration of electromagnetic technology with healthcare, making strides in non-invasive monitoring systems.

Awards and Honours

🏆 Dr. Augustine’s impactful research has attracted numerous grants and awards, including significant EU funding for projects like PERSIMMON and DIAMPS. He has secured research funding from bodies such as the Swedish Research Council, Vinnova, and the Foundation for Strategic Research, supporting his innovative work on body communication systems and medical diagnostics. His research has earned recognition through the Swedish Excellence Grant for Young Researchers and multiple grants for advancing medical engineering solutions.

Publication Top Notes

Biphasic lithium iron oxide nanocomposites for enhancement in electromagnetic interference shielding properties

Rotation insensitive implantable wireless power transfer system for medical devices using metamaterial-polarization converter

Improving burn diagnosis in medical image retrieval from grafting burn samples using B-coefficients and the CLAHE algorithm

 

Christopher Ekeocha | Machine learning | Best Researcher Award

Mr. Christopher Ekeocha | Machine learning | Best Researcher Award

Graduate Research Assistant, Africa Centre of Excellence in Future Energies and Electrochemical Systems (ACE-FUELS), Nigeria

Christopher Ikechukwu Ekeocha is a dedicated Assistant Research Fellow at the National Mathematical Centre in Abuja, Nigeria, with a keen interest in corrosion mitigation and environmental pollution. His extensive research focuses on developing innovative eco-friendly materials and computational simulation techniques to address corrosion and pollution challenges. He has represented Nigeria internationally at the International Chemistry Olympiad, guiding students to success in countries like Vietnam, Azerbaijan, Georgia, France, and China. 🌍🔬

Publication Profile

ORCID

Strengths for the Award:

  1. Academic Excellence: Christopher Ikechukwu Ekeocha has consistently performed at a high academic level throughout his education. His Ph.D. in Corrosion Technology (CGPA: 4.60/5.0) and Master’s in Environmental Chemistry (CGPA: 3.92/5.0) demonstrate his dedication to research and academic rigor.
  2. Innovative Research: His focus on developing eco-friendly, biomass-based anti-corrosion materials and using machine learning models for corrosion prediction is cutting-edge. His work combines experimental and computational techniques, pushing the boundaries of corrosion technology.
  3. Strong Publication Record: Ekeocha has published extensively in reputable, high-impact journals, with topics ranging from corrosion inhibitors to environmental chemistry. This demonstrates the relevance and quality of his work. Key publications include machine learning models and computational simulations for anti-corrosion research, which have been well-received in the scientific community.
  4. Interdisciplinary Collaboration: He has collaborated on multidisciplinary projects promoting circular economy and eco-friendly techniques for corrosion mitigation. His ability to work across various fields shows adaptability and leadership in research.
  5. Community Contribution: In addition to his academic work, Ekeocha has made significant contributions to the Chemistry Olympiad, leading Nigerian teams and authoring textbooks. His role in this capacity speaks to his leadership and commitment to education and knowledge dissemination.

Areas for Improvement:

  1. Research Diversification: While Ekeocha has made strong contributions in corrosion technology, expanding his research to other areas of environmental chemistry or further enhancing the practical applications of his work could strengthen his overall profile. Engaging in more diverse projects could showcase his versatility.
  2. Industry Engagement: Although his research is well-grounded in academia, there could be a stronger connection with industry to ensure his innovations, especially in corrosion mitigation, are applied in real-world settings. Collaborations with companies focusing on corrosion prevention or environmental impact assessments could enhance the practical impact of his research.
  3. International Recognition: While his publications are gaining recognition, presenting his research at more international conferences or collaborating with foreign institutions could boost his global visibility and increase the influence of his work.

Education

Christopher Ekeocha is affiliated with the Africa Centre of Excellence in Future Energies and Electrochemical Systems (ACE-FUELS) at the Federal University of Technology, Owerri (FUTO). His research emphasizes the permeation of ions across semi-permeable membranes, focusing on membrane thickness, permeation time, and electrolyte concentration. 🎓⚛️

Experience

With over a decade of experience, Christopher Ekeocha has served as an Assistant Research Fellow at the National Mathematical Centre, Abuja, since 2011. He leads Nigeria’s participation in the International Chemistry Olympiad, having represented the country in multiple international events. His expertise lies in corrosion studies, computational modeling, and eco-friendly corrosion inhibitors. 🌱🔧

Research Focus

Christopher’s research centers on the development of mathematical and predictive models for novel corrosion inhibitors. He specializes in using computational simulations and eco-friendly materials to mitigate metallic corrosion and conducting ecological risk assessments of environmental pollution. His work also covers adsorption kinetics, water and solvent treatment using nanoparticles, and pollutant removal with agricultural waste. 📊🔍

Awards and Honours

Ekeocha has gained recognition for his contributions to corrosion research and environmental protection. His participation in the International Chemistry Olympiad as a Nigerian team leader is notable, alongside his extensive academic publications and active role in global scientific conferences. 🏆🌟

Publication Top Notes

Christopher Ikechukwu Ekeocha has authored several influential articles in prestigious journals, including Materials Today Communications, Structural Chemistry, and African Scientific Reports. His works primarily focus on corrosion inhibition, eco-friendly materials, and environmental pollution. 📚✨

Ekeocha, C. I., et al. (2024). Data-Driven Machine Learning Models and Computational Simulation Techniques for Prediction of Anti-Corrosion Properties of Novel Benzimidazole Derivatives. Materials Today Communications https://doi.org/10.1016/j.mtcomm.2024.110156

Ekeocha, C. I., et al. (2024). Theoretical Study of Novel Antipyrine Derivatives as Promising Corrosion Inhibitors for Mild Steel in an Acidic Environment. Structural Chemistry https://doi.org/10.1007/s11224-024-02368-4

Ekeocha, C. I., et al. (2023). Review of Forms of Corrosion and Mitigation Techniques: A Visual Guide. African Scientific Reports, 2(3): 117. https://doi.org/10.46481/asr.2023.2.3.117

Conclusion:

Christopher Ikechukwu Ekeocha is an excellent candidate for the Research for Best Research Award. His innovative contributions in the field of corrosion technology, combined with his interdisciplinary approach and strong academic background, position him well for recognition. His research aligns with global trends toward eco-friendly solutions and computational advancements, making him a strong contender. However, increased industry engagement and further research diversification would further elevate his impact in both academic and practical domains.