Dr. Jiaheng Peng | Data Science | Best Researcher Award

PhD Candidate, East China Normal University, China

Jiaheng Peng is a dedicated Ph.D. candidate at East China Normal University, specializing in Open Source Ecosystem, Natural Language Processing, and Evaluation Science. With a strong academic record and a passion for research, he has contributed significantly to understanding Open Source dataset evaluation. His work bridges the gap between academic research and real-world Open Source applications, earning him recognition in the field.

Publication Profile

Academic Background

Jiaheng Peng is pursuing his Ph.D. at East China Normal University, focusing on innovative methods to assess Open Source datasets. His research emphasizes citation network analysis, evaluating long-term dataset usage, and developing advanced Natural Language Processing (NLP) models. His academic journey is marked by high-impact publications in top-tier journals and international conferences, reflecting his expertise in computational analysis and data evaluation.

Professional Experience

Although Jiaheng does not have industry consultancy or ongoing research projects, his scholarly contributions have made a substantial impact on Open Source ecosystem analysis. He actively publishes in high-impact scientific journals and conferences, ensuring that his findings help enhance dataset evaluation metrics. His commitment to advancing data-driven methodologies sets a solid foundation for future research in Open Source analysis.

Awards and Honors

Jiaheng Peng’s research excellence has been acknowledged with the Best Paper Award at the 1st Open Source Technology Academic Conference (2024). His publications in Q1-ranked journals further highlight his academic impact. His continuous contributions to the Open Source community demonstrate his dedication to advancing research and innovation in Open Source evaluation.

Research Focus

Jiaheng’s research primarily addresses the limitations of traditional Open Source data insight metrics. His work connects Open Source datasets with their corresponding academic papers, evaluating their significance through citation network mining. By bridging Open Source data with academic insights, he introduces novel evaluation methodologies that enhance dataset usability and long-term impact analysis. His research also extends into Aspect-Based Sentiment Classification, employing advanced Graph Attention Networks and NLP models to extract meaningful insights.

Conclusion

Jiaheng Peng is a rising scholar in the Open Source and NLP domains, with a keen focus on dataset evaluation, citation network analysis, and sentiment classification. His academic contributions, recognized through prestigious awards and top-tier publications, establish him as a promising researcher dedicated to advancing Open Source dataset analytics. With a commitment to scientific excellence, his work continues to influence the global research community.

Publication Top Notes

Evaluating long-term usage patterns of open source datasets: A citation network approach
BenchCouncil Transactions on Benchmarks, Standards and Evaluations (2025)
Cited by: Pending

DRGAT: Dual-relational graph attention networks for aspect-based sentiment classification
Information Sciences (2024)
Cited by: Pending

Data Driven Visualized Analysis: Visualizing Global Trends of GitHub Developers with Fine-Grained Geo-Details
International Conference on Database Systems for Advanced Applications (2024)
Cited by: Pending

ASK-RoBERTa: A pretraining model for aspect-based sentiment classification via sentiment knowledge mining”
Knowledge-Based Systems (2022)
Cited by: Multiple researchers in NLP and sentiment analysis

Prof. Dr. Hamid Arabnia | Data Science | Best Researcher Award

Professor Emeritus, University of Georgia, United States

Dr. Hamid R. Arabnia is a distinguished Professor Emeritus of Computer Science at the University of Georgia, USA . With a Ph.D. in Computer Science from the University of Kent, England (1987), he has made substantial contributions to the fields of Artificial Intelligence, Data Science, Machine Learning, HPC, and STEM education . Over his career, he has mentored 23 Ph.D. students and played a vital role in advancing computational science and intelligence. He has been an active advocate against cyber-harassment and cyberbullying, winning a landmark lawsuit in 2017–2018, securing a $3 million ruling . Prof. Arabnia has an extensive publication record with 300+ peer-reviewed papers and 200+ edited research books, establishing himself among the top 2% most impactful scientists, as recognized by Stanford University .

Publication Profile

Education

Dr. Arabnia earned his Ph.D. in Computer Science from the University of Kent, England (1987) . His research during his doctoral studies laid the foundation for his pioneering contributions in supercomputing and artificial intelligence .

Experience

Dr. Arabnia has been with the University of Georgia since 1987, contributing as a Professor, Graduate Coordinator, and Research Director . He has served as Editor-in-Chief of The Journal of Supercomputing (Springer) and is the book series editor for Transactions of Computational Science and Computational Intelligence (Springer) . His leadership has also extended to roles as a senior adviser for global corporations and National Science Foundation (NSF) committees for over 10 years .

Awards and Honors

Prof. Arabnia has received numerous prestigious awards, including recognitions from IEEE BIBE, ACM SIGAPP, and IMCOM . His legal victory against cyber-harassment was a landmark case, setting an important precedent in the U.S. legal system . His contributions to STEM education and securing $12 million in funding for graduate research at UGA have also been widely recognized .

Research Focus

Dr. Arabnia’s research spans Data Science, AI, HPC, Machine Learning, Imaging Science, and Compute-Intensive Problems . He has been actively involved in cybersecurity legislation advocacy, focusing on cyberstalking and online harassment . His latest work integrates deep learning, upsampling techniques, and AI-driven smart city applications .

Conclusion

Dr. Hamid R. Arabnia is a highly influential researcher, educator, and advocate for ethical AI and cybersecurity . With over 500 publications and millions in research funding, his contributions have shaped modern supercomputing, artificial intelligence, and digital security . Recognized among the top 2% impactful scientists globally, his work continues to inspire the next generation of AI and computer science researchers .

Publications

Comprehensive Analysis of Random Forest and XGBoost Performance with SMOTE, ADASYN, and GNUS Upsampling under Varying Imbalance Levels (2025) – Preprint

A New Efficient Hybrid Technique for Human Action Recognition Using 2D Conv-RBM and LSTM with Optimized Frame Selection (2025) – Technologies | DOI

SWAG: A Novel Neural Network Architecture Leveraging Polynomial Activation Functions for Enhanced Deep Learning Efficiency (2024) – IEEE Access | DOI

Hyperparameter Optimization and Combined Data Sampling Techniques in Machine Learning for Customer Churn Prediction: A Comparative Analysis (2023) – Technologies | DOI

A Review of Deep Transfer Learning and Recent Advancements (2023) – Technologies | DOI

Embodied AI-Driven Operation of Smart Cities: A Concise Review (2021) – TechRxiv | DOI