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

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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 🌍

Huan Zhao | Machine Learning | Best Researcher Award

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Assoc. Prof. Dr . Huan Zhao | Machine Learning | Best Researcher Award

Associate Professor, School of Aeronautics, Northwestern Polytechnical University, China

Huan Zhao is an associate professor at the School of Aeronautics, Northwestern Polytechnical University (NPU), China. He specializes in aerodynamics, multidisciplinary design optimization, uncertainty quantification, and machine learning, focusing on CFD simulation, AI-based global optimization, and surrogate modeling. He is also the executive deputy director of the Institute of Digital Intelligence for Flight Mechanics and Aerodynamic Design (IDIFMAD). Zhao has made significant contributions to the fields of aerodynamic shape optimization, high-dimensional global optimization, and uncertainty-based robust design. He holds several patents and has authored many high-impact publications. 🌐✈️

Publication Profile

Education

Huan Zhao completed his Ph.D. in Fluid Dynamics at Northwestern Polytechnical University (NPU) in 2020, following a B.Eng. in Aircraft Design and Engineering from the same university in 2014. 📚🎓

Experience

Zhao served as a tenure-track assistant professor at Sun Yat-sen University (SYSU) before joining NPU as a tenure-track associate professor in 2023. He has directed and participated in numerous research projects focusing on aerodynamic design optimization, high-speed rotor airfoil design, and surrogate-assisted design techniques. He is a principal investigator (PI) for multiple projects funded by the National Natural Science Foundation of China (NSFC). 👨‍🏫🔬

Awards and Honors

Huan Zhao has received several awards and honors, including recognition as part of the “Hundred Talents Plan” Young Academic Backbone at SYSU and multiple patents for his innovative contributions to aerodynamic design. 🏆🎖️

Research Focus

Zhao’s research interests lie in aerodynamics, including multi-fidelity polynomial chaos-Kriging models, aerodynamic shape optimization, and uncertainty quantification. His work has contributed significantly to the design and optimization of high-lift airfoils, laminar flow airfoils, and robust design methods under uncertainty. His expertise also includes machine learning, AI-based global optimization, and the application of surrogate models in complex design scenarios. 🔍🧑‍💻

Conclusion

Huan Zhao’s innovative work has had a profound impact on the field of aerodynamics and optimization. His research has not only advanced the understanding of aerodynamic design but has also led to practical improvements in the development of high-performance aircraft and related technologies. He continues to drive forward cutting-edge research in aerodynamics and multidisciplinary design optimization. 🚀🌍

Publications

An efficient adaptive forward–backward selection method for sparse polynomial chaos expansion, Computer Methods in Applied Mechanics and Engineering, 2019.

Review of robust aerodynamic design optimization for air vehicles, Archives of Computational Methods in Engineering, 2019.

Effective robust design of high lift NLF airfoil under multi-parameter uncertainty, Aerospace Science and Technology, 2017.

Adaptive multi-fidelity sparse polynomial chaos-Kriging metamodeling for global approximation of aerodynamic data, Structural and Multidisciplinary Optimization, 2021.

Uncertainty-based design optimization of NLF airfoil for high altitude long endurance unmanned air vehicles, Engineering Computations, 2019.

 Efficient aerodynamic analysis and optimization under uncertainty using multi-fidelity polynomial chaos-Kriging surrogate model, Computers & Fluids, 2022.

Research on efficient robust aerodynamic design optimization method of high-speed and high-lift NLF airfoil, Acta Aeronautica et Astronautica Sinica, 2021.

Research on Novel High-Dimensional Surrogate Model-Based Aerodynamic Shape Design Optimization, Acta Aeronautica et Astronautica Sinica, 2022.

Research on novel multi-fidelity surrogate model assisted many-objective global optimization method, Acta Aeronautica et Astronautica Sinica, 2022.

Adaptive multi-fidelity polynomial chaos-Kriging model-based efficient aerodynamic design optimization method, Chinese Journal of Theoretical and Applied Mechanics, 2023.

 

Lukas Petersson | Artificial Intelligence | Best Researcher Award

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Mr. Lukas Petersson | Artificial Intelligence | Best Researcher Award

Founder, Vectorview, United States

Lukas Petersson is a passionate AI and robotics researcher, currently serving as the CTO and Co-founder of Vectorview in San Francisco. With a strong background in software engineering, machine learning, and robotics, Lukas has contributed significantly to AI safety evaluations for major labs such as Anthropic. He has a track record of successful funding, securing $2.2M in capital, and conducting groundbreaking research on agentic capabilities of LLMs. 🌟🤖💡

Publication Profile

Google Scholar

Education:

Lukas is pursuing his M.Sc. and B.Sc. in Engineering Physics and Engineering Mathematics at Lund University, where he has achieved an impressive GPA of 4.9/5 and 5.0/5. He also spent a year at ETH Zurich focusing on Machine Learning and Robotics. 🎓📚

Experience:

Lukas has gathered diverse experience across top organizations such as Google, Disney Research, CommaAI, and the European Space Agency. He has contributed to AI research, robotics, and autonomy engineering, with notable achievements like developing RL algorithms for social robotic interaction and automating data analysis at Google. He has also been part of impactful projects like the viral robot developed at Disney Research. 🏢🧑‍💻🚀

Research Interests:

Lukas’s research interests lie at the intersection of AI Safety, Machine Learning, Robotics, and Autonomous Systems. His work focuses on improving agentic capabilities of large language models (LLMs) and exploring the application of Reinforcement Learning (RL) for social robots. 🤖🔬🌍

Awards:

Lukas’s work has been recognized in the fields of robotics and AI, contributing to significant advancements in safety and performance. He has excelled in competitive programming and autonomous vehicle development, receiving awards and recognition for his innovative approach to solving real-world challenges. 🏆🌟

Publications:

“Taming the Machine” (2023): Contributed research on AI Safety for a book discussing the future of machine learning and its societal impacts. 📚🧠

“MBSE” (2021): Published and presented a paper on Model-Based Systems Engineering at a conference, focusing on advanced methodologies in systems engineering. 📄🔧