Jiawei Shi | curriculum teaching | Best Researcher Award

Mrs. Jiawei Shi | curriculum teaching | Best Researcher Award

Senior Lecturer | Zhoukou Normal University | China

Mrs. Jiawei Shi is a Senior Lecturer and Research Scholar at Zhoukou Normal University and HUANGHE S&T University, specializing in the intersection of art education, digital pedagogy, and educational equity. His research focuses on addressing structural challenges in China’s basic art education—particularly teacher shortages, disparities in resource allocation, and uneven regional development—through evidence-based digital innovation. As the sole author of the high-impact empirical study “Digital applications inject new vitality into art education—Path analysis based on data of art teachers in basic education in China,” Shi has contributed a rigorous and multidimensional analytical framework that integrates literature review, policy analysis, national education statistics, survey research, Delphi method, Analytic Hierarchy Process (AHP), and the CIPP evaluation model. His work constructs a weighted evaluation index system (Y=0.35X1+0.15X2+0.22X3+0.28X4) and provides robust empirical evidence demonstrating the significant effectiveness of digital applications in enhancing teaching environments, resource distribution, and instructional outcomes in art education. The study’s findings—such as the expert authority coefficient Cr=0.632 and comparative evaluation results between digital demonstration schools and traditional schools—offer both scholarly insight and practical policy value. Shi has authored multiple academic publications and collaborated with interdisciplinary teams and provincial research initiatives, including the 2024 Henan Xingwenhua Cultural Engineering Project (No. 2024XWH241). His research has attracted growing academic attention and citation within the fields of digital education reform and art education modernization. Beyond theoretical contributions, Shi’s work supports national and regional decision-making by proposing actionable strategies for optimizing teacher training, funding mechanisms, and digital resource integration. Committed to advancing educational modernization, he continues to pursue research that promotes equity, innovation, and high-quality development in China’s basic education system, ensuring that digital transformation contributes meaningfully to cultural transmission, artistic literacy, and social progress.

Profile: ORCID

Featured Publications

Shi, J. (n.d.). Digital applications inject new vitality into art education: Path analysis based on data of art teachers in basic education in China.

Jiawei Shi’s research advances the digital transformation of art education by providing a scientifically validated framework that supports equitable resource distribution and improved instructional quality across China’s basic education system. His work guides policymakers, educators, and institutions in adopting evidence-based digital strategies that enhance cultural literacy, modernize teaching practices, and promote inclusive, high-quality education with broad societal impact.

Mohsin Hasan | Management science and engineering | Best Researcher Award

Mr . Mohsin Hasan | Management science and engineering | Best Researcher Award

Student at Nanjing University of Aeronautics and Astronautics , China

Mohsin Hasan is a dedicated and impactful researcher currently pursuing a PhD in Management Science and Engineering at Nanjing University of Aeronautics and Astronautics, China. His research focuses on epileptic seizure prediction using advanced machine learning techniques, including LSTM, SHAP, and deep neural networks, addressing a critical healthcare challenge. With publications in top-tier SCIE-indexed journals such as Engineering Applications of Artificial Intelligence and Annals of Operations Research, he demonstrates strong academic rigor and innovation. Mohsin possesses expertise in Python programming, big data analysis, and research writing, supported by a multi-disciplinary academic background in sociology. He has also actively contributed to community health initiatives in Pakistan, reflecting a blend of technical and social impact. While improved English proficiency and expanded international collaboration could enhance his profile, his current achievements make him a strong candidate for the Best Researcher Award, showcasing both research excellence and real-world relevance.

Professional Profile

Education🎓

Mohsin Hasan has a diverse and interdisciplinary educational background that bridges social sciences and engineering. He is currently pursuing a PhD in Management Science and Engineering at Nanjing University of Aeronautics and Astronautics in China, with a research focus on epileptic seizure prediction using machine learning and deep learning techniques. Prior to his doctoral studies, he completed an M.S. in Rural Sociology from the University of Agriculture Faisalabad and a Master’s degree in Sociology from the University of Sargodha, Pakistan. His academic journey began with a Bachelor of Arts from Government College University Faisalabad, followed by intermediate studies at Government Islamia College Chiniot and matriculation at Government High School Chak No. 152 JB Chiniot. Throughout his education, Mohsin has developed strong skills in Python programming, big data analysis, and research writing, positioning him to apply advanced technological solutions to both social and engineering problems, particularly in healthcare and community development.

Professional Experience📝

Mohsin Hasan has a well-rounded professional background that spans academic research and community development. Currently, he is engaged in cutting-edge research as a PhD scholar, working on epileptic seizure prediction using machine learning, with multiple SCIE-indexed publications to his name. His earlier professional experience includes various social outreach and coordination roles across Pakistan. As a Social Outreach Worker with UNODC, he led awareness campaigns and community mobilization for drug addiction treatment. He also served as Supervisor for the Sehat Sahulat Insaaf Card project with RCDP, managing field staff and overseeing healthcare card distribution. As a Dosti Coordinator with Muslim Hands International, he trained teachers and encouraged school enrollment and student participation in extracurricular activities. Additionally, he worked as an Assistant Constituency Coordinator for the FAFEN Election Project, monitoring electoral processes and data collection. His experience demonstrates a strong blend of technical expertise, leadership, and community-oriented service.

Research Interest🔎

Mohsin Hasan’s research interests lie at the intersection of artificial intelligence, healthcare, and data science, with a strong focus on real-world applications that enhance human well-being. His primary area of interest is the prediction and classification of epileptic seizures using advanced machine learning and deep learning techniques, including Long Short-Term Memory (LSTM), Kolmogorov Arnold Network Theorem, SHAP-driven feature analysis, and attention-based neural networks. He is particularly passionate about leveraging electroencephalography (EEG) data to develop interpretable and accurate models for early seizure detection. His research also extends to reliability engineering, operational research, and the integration of AI in medical diagnostics. With a background in sociology and rural development, Mohsin brings a unique, human-centered approach to technological innovation, aiming to bridge the gap between data-driven solutions and community health challenges. His interdisciplinary perspective fuels his commitment to creating scalable, impactful tools for healthcare and beyond, particularly in under-resourced and developing contexts.

Award and Honor🏆

Mohsin Hasan has earned recognition for his dedication to academic excellence and impactful research, positioning him as a strong candidate for prestigious honors. His most notable achievement is his contribution to high-impact, SCIE-indexed journals such as Engineering Applications of Artificial Intelligence and Annals of Operations Research, where his research on epileptic seizure prediction has gained international attention. In addition to academic publications, Mohsin has been involved in global policy discussions and training sessions, including regional dialogues hosted by the Asian Institute of Technology and certification courses by the World Health Organization on emerging health threats and COVID-19 response. His ability to translate complex data science techniques into meaningful healthcare solutions reflects both innovation and social commitment. These accomplishments highlight his exceptional talent, work ethic, and relevance in critical global issues. Such recognition not only underscores his scholarly contributions but also establishes him as a deserving candidate for awards celebrating research excellence and societal impact.

Research Skill🔬

Mohsin Hasan possesses a comprehensive set of research skills that enable him to conduct advanced, data-driven investigations with real-world impact. He is highly proficient in Python programming and well-versed in tools such as Jupyter Notebook, PyCharm, and Google Colab, which he utilizes for building and testing machine learning models. His core expertise lies in deep learning, particularly in applying algorithms like Long Short-Term Memory (LSTM), 1D-ResNet, and attention mechanisms for medical data analysis, especially EEG-based epileptic seizure prediction. Mohsin is skilled in big data analytics, neural network development, and SHAP-based model interpretation, which enhances the transparency and usability of AI models. Additionally, he is experienced in academic research writing, LaTeX formatting, and data visualization using software like Edraw Max and Visio. His ability to integrate technical depth with scientific communication, along with a strong foundation in statistical methods and real-time problem-solving, marks him as a capable and innovative researcher.

Conclusion💡

Yes, Mohsin Hasan is a strong and deserving candidate for the Best Researcher Award.

His profile demonstrates a rare and valuable combination of technical AI research, medical applications, and community-level engagement. His high-quality publications, technical skills, and international academic involvement position him as a rising researcher with significant impact potential.

Publications Top Noted✍

  • Title: Long Short-Term Memory and Kolmogorov Arnold Network Theorem for Epileptic Seizure Prediction

  • Authors: Mohsin Hasan, Xufeng Zhao, Wenjuan Wu, Jiafei Dai, Xudong Gu, Asia Noreen

  • Year: 2025

  • Journal: Engineering Applications of Artificial Intelligence

  • Volume and Issue: Volume 154

  • Pages: Article 110757

  • Publisher: Elsevier

  • Indexing: SCIE

  • Citation Format (APA Style):
    Hasan, M., Zhao, X., Wu, W., Dai, J., Gu, X., & Noreen, A. (2025). Long Short-Term Memory and Kolmogorov Arnold Network Theorem for epileptic seizure prediction. Engineering Applications of Artificial Intelligence, 154, 110757. https://doi.org/10.1016/j.engappai.2025.110757 (DOI placeholder if needed)

 

Bhargob Deka | Bayesian machine learning | Best Researcher Award

🌟Dr. Bhargob Deka, Bayesian machine learning, Best Researcher Award🏆

Doctorate at Polytechnique Montreal, Canada

Professional Profiles:

Bio Summary

AI Research Scientist and Data Scientist with over 4 years of experience in applied probability, statistics, and machine learning. Specialized in Bayesian neural networks, time series modeling, and industrial research. Enthusiastic about AI and continuous learning. Proven track record in developing innovative ML models, leading projects, and collaborating with R&D teams.

Education

Polytechnique Montréal | Sep 2018-Dec 2022

  • Ph.D. in Civil Engineering: Machine Learning Specialization – GPA 4/4.3
  • Research Grant: Hydro Québec, NSERC

McGill University | Sep 2015-Mar 2018

  • M. Eng. in Civil Engineering: Structural Engineering – GPA 3.88/4
  • Research Grant: Graduate Research Assistantship

Assam Engineering College | Aug 2010-June 2014

  • B. Eng. in Civil Engineering: First-Class Honours with 75.78%
  • Research Grant: North-Eastern Council Merit Scholarship

Research Focus

Advanced Machine Learning Research

  • Bayesian Neural Networks, Regression, Classification, Time Series

Industrial Research Leadership

  • End-to-end ML solutions, process automation, software training

Machine Learning Research Scholarship

  • Neurocomputing, Adaptive Control, Signal Processing

AI Enthusiast

  • Diverse end-to-end deep learning projects in CV, NLP, Generative AI

Professional Journey

Machine Learning Researcher | Polytechnique Montréal | Sep 2018 – Present

  • Developed AGVI for uncertainty quantification in Bayesian neural networks.
  • Improved training time significantly, applied in regression, classification, and time series.
  • Published AGVI in the International Journal of Adaptive Control and Signal Processing.

Research Consultant | Polytechnique Montréal | Sep 2018 – Present

  • Developed ML approach for nonlinear dependencies in time series.
  • Collaborated with dam engineers for real-time anomaly detection, winning competitions.

Honors & Awards

Eliminated hyper-parameter tuning and sped up Bayesian neural network training.

First and fourth rankings in predictive modeling competition at ICOLD-BW2022.

Author Metrics

Number of publications: 4

Conferences and Talks: 2

First-author publications: 2

Research Timeline

2018-2022: Ph.D. in Civil Engineering with a focus on Machine Learning.

2018-Present: Machine Learning Researcher at Polytechnique Montréal.

2018-Present: Research Consultant for industrial projects in collaboration with Hydro Québec.

2022: Published AGVI in the International Journal of Adaptive Control and Signal Processing.

2022: First and fourth rankings in predictive modeling competition at ICOLD-BW2022.

Publications & Contributions

Journals:
  • Tractable Uncertainty Quantification in Bayesian Neural Networks (Neurocomputing, 2023).
  • Gaussian Variance Inference for State-Space Models (IJACSP, 2023).
  • Inspector’s Uncertainty Inference Using Network-Scale Visual Inspections (J. Computing in Civil Engineering, 2023).
  • Gaussian Multiplicative Approximation for State-Space Models (Structural Control and Health Monitoring, 2022).
Conferences and Talks:
  • Online aleatory uncertainty quantification for probabilistic time series (ICASP14, 2023).
  • Dam Behavior Prediction Using Bayesian Models (Benchmark Workshop on Numerical Analysis of Dams, 2022).
Publications Top Noted

1. Building Classification Scheme and Vulnerability Model for the City of Guwahati, Assam

  • Authors: J Pathak, R Bharali, B Deka, S Pathak, IJ Ahmed, DH Lang, A Meslem
  • Published in: EQRisk Project Report
  • Year: 2015
  • Cited By: 6

2. The Gaussian Multiplicative Approximation for State-Space Models

  • Authors: B Deka, L Ha Nguyen, S Amiri, JA Goulet
  • Published in: Structural Control and Health Monitoring
  • Volume: 29 (3)
  • Page: e2904
  • Year: 2022
  • Cited By: 5

3. Damage Assessment of RC Frame Structures under Long Duration Aftershock Ground Motion

  • Authors: B Deka, SN Rahman, P Tamuly
  • Published in: International Journal of Innovative Research in Science, Engineering, and Technology
  • Volume: 3 (9)
  • Pages: 16144-16149
  • Year: 2014
  • Cited By: 5

4. Analytical Bayesian Parameter Inference for Probabilistic Models with Engineering Applications

  • Author: B Deka
  • Published at: Polytechnique Montréal
  • Year: 2022
  • Cited By: 3

5. Analytically Tractable Heteroscedastic Uncertainty Quantification in Bayesian Neural Networks for Regression Tasks

  • Authors: B Deka, LH Nguyen, JA Goulet
  • Published in: Neurocomputing
  • Pages: 127183

Youngmi Song | Biology | Best Researcher Award

🌟Assoc Prof Dr. Youngmi Song, Kagbuk Samsung Hospital/Medical Research institute, South Korea: Biology🏆
Professional Profiles:
Bio Summary

I am Dr. Youngmi Song, a dedicated researcher with a Ph.D. in Biomedical Science from Yonsei University College of Medicine. Throughout my academic and professional journey, I have contributed significantly to the fields of hepatosteatosis, autophagy, and gut microbiota, among others.

Education
  • Ph.D. in Biomedical Science
    • Period: September 2011 to February 2015
    • Institution: Yonsei University College of Medicine, Seoul, Republic of Korea
Research Focus

My research primarily focuses on understanding and addressing metabolic disorders, with a particular emphasis on hepatosteatosis, nonalcoholic steatohepatitis, and the role of gut microbiota in these conditions. Additionally, I have explored pathways related to autophagy, GLP-1 secretion, and the effects of various pharmacological interventions.

Professional Journey
  • Research Professor
    • Institution: Medical Research Institute, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
    • Period: October 2019 onwards
  • Postdoctoral Fellow
    • Institution: Luenfeld-Tanenbaum Research Institute, Sinai Health System, University of Toronto, Canada
    • Period: April 2016 to 2019
  • Postdoctoral Fellow
    • Institution: Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
    • Period: February 2015 to February 2016
Honors & Awards
  • Academic Award for Highest Achievement
    • Institution: Yonsei University College of Medicine
    • Date: February 2015
  • Travel Grant
    • Event: 9th International Diabetes Federation Western Pacific Region Congress, Kyoto, Japan
    • Date: November 2012
Author Metrics
  • Citations: 825
  • Documents: 11
  • h-index: 10
Publications Top Noted & Contributions

I have made substantial contributions to scientific literature, particularly in prestigious journals, shedding light on topics such as gut microbiota, GLP-1 secretion, hepatosteatosis, and autophagy. Noteworthy publications include studies on Gemigliptin, metformin, and the impact of glycated albumin on pancreatic beta-cell function.

Gemigliptin, a DPP4 inhibitor, ameliorates nonalcoholic steatohepatitis through AMP-activated protein kinase-independent and ULK1-mediated autophagy

  • Journal: Molecular Metabolism (2023)
  • Citations: 0

Intestine-selective reduction of Gcg expression reveals the importance of the distal gut for GLP-1 secretion

  • Journal: Molecular Metabolism (2020)
  • Citations: 37

Gut-Proglucagon-Derived Peptides Are Essential for Regulating Glucose Homeostasis in Mice

  • Journal: Cell Metabolism (2019)
  • Citations: 78

Ezetimibe ameliorates steatohepatitis via AMP activated protein kinase-TFEB-mediated activation of autophagy and NLRP3 inflammasome inhibition

  • Journal: Autophagy (2017)
  • Citations: 146

Association between betatrophin/ANGPTL8 and non-alcoholic fatty liver disease: Animal and human studies

  • Journal: Scientific Reports (2016)
  • Citations: 76

Metformin restores parkin-mediated mitophagy, suppressed by cytosolic p53

  • Journal: International Journal of Molecular Sciences (2016)
  • Citations: 67

Metformin alleviates hepatosteatosis by restoring SIRT1-mediated autophagy induction via an AMP-activated protein kinase-independent pathway

  • Journal: Autophagy (2015)
  • Citations: 229
Research Timeline
  • 2011-2015: Pursued Ph.D. in Biomedical Science at Yonsei University College of Medicine.
  • 2015-2016: Conducted postdoctoral research on hepatosteatosis and autophagy at Yonsei University College of Medicine.
  • 2016-2019: Engaged in postdoctoral research as a Kangbuk Samsung-BBDC International Research Fellow at the University of Toronto.
  • 2019-Present: Currently serving as a Research Professor at the Medical Research Institute, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, focusing on metabolic disorders.

Scientific Advancement Achievement Award

Introduction: Scientific Advancement Achievement Award

Welcome to the forefront of innovation and discovery. The Scientific Advancement Achievement Award celebrates those who push the boundaries of knowledge and lead the charge in scientific progress. This prestigious award recognizes outstanding contributions to the field of New Science Inventions, applauding individuals for their groundbreaking achievements.

Eligibility:

Open to scientists, researchers, and innovators across all disciplines, the Scientific Advancement Achievement Award is bestowed upon individuals who have demonstrated exceptional advancements in scientific knowledge and technology.

Age Limits:

No age restrictions apply; this award values contributions irrespective of age.

Qualification:

Candidates must hold a relevant academic degree or demonstrate equivalent experience in their respective fields.

Publications:

Applicants are required to have a strong record of impactful publications showcasing their contributions to scientific advancement.

Requirements:
  • A comprehensive biography highlighting the nominee's career and achievements.
  • An abstract outlining the significance of the nominee's work.
  • Supporting files, such as publications, patents, or prototypes, showcasing the nominee's contributions.
Evaluation Criteria:

Judged on the basis of innovation, impact, originality, and significance, the evaluation process considers the nominee's overall contribution to advancing scientific knowledge.

Submission Guidelines:

Submissions should be sent electronically and include a biography, abstract, and supporting files in the specified format. Incomplete or late submissions may not be considered.

Recognition:

Recipients of the Scientific Advancement Achievement Award will receive a prestigious honor, public recognition, and opportunities for further collaboration and funding.

Community Impact:

The award recognizes not only individual accomplishments but also the broader impact on the scientific community and society at large.

Biography:

A detailed biography should highlight the nominee's educational background, career achievements, and contributions to scientific advancement.

Abstract and Supporting Files:

The abstract should succinctly convey the significance of the nominee's work. Supporting files, such as publications or prototypes, should provide tangible evidence of their contributions.

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