Prof. Hua Zhang | Machine Learning | Best Researcher Award

Prof. Hua Zhang | Machine Learning | Best Researcher Award

Professor at Wuhan University of Science and Technology, China

Profiles

Scopus

Research Gate

Summary:

Prof. Hua Zhang is a distinguished professor at Wuhan University of Science and Technology (WUST), specializing in clean steel production technology, numerical simulation, and the development of iron-based amorphous alloys. With a Ph.D. in Metallurgical Engineering, he has made significant contributions to steelmaking technology, securing multiple prestigious awards, including provincial science and technology awards and the Baosteel Outstanding Teacher Award. As the vice dean of the School of Materials Science at WUST, Dr. Zhang has published over 100 papers and holds numerous patents.

Education

  • Ph.D. in Metallurgical Engineering (2012)

💼 Professional Experience

  • Professor, Wuhan University of Science and Technology (2019–Present)
  • Postdoctoral Researcher, MCC Continuous Casting Technology Engineering Co., Ltd. (2015–2017)
  • Vice Dean, School of Materials Science, WUST

🔬 Research Interests

  • Clean steel production technology
  • Continuous casting new technology
  • Numerical simulation
  • Iron-based amorphous soft magnetic alloys
  • Secondary utilization of metallurgical resources

 

Publications

Modulating Fe/P Ratios in Fe-P Alloy through Smelting Reduction for Long-Term Electrocatalytic Overall Water Splitting

  • Authors: Zhang, T., Ren, X., Mo, S., Zhang, H., Ni, H.
  • Journal: Journal of Materials Science and Technology
  • Year: 2024
  • Authors: Li, J., Wu, G., Fang, Q., Zhang, H., Ni, H.
  • Journal: Journal of the Taiwan Institute of Chemical Engineers
  • Year: 2024

Investigation on the Characteristics of Porosity, Melt Pool in 316L Stainless Steel Manufactured by Laser Powder Bed Fusion

  • Authors: Liu, C.-S., Xue, X., Wang, Y., Xiong, L., Ni, H.-W.
  • Journal: Journal of Materials Research and Technology
  • Year: 2024

Suppression of Free-Surface Vortex in Tundish by Rotating Stopper-Rod and Its Impact on Multiphase Flow in Mold

  • Authors: Huang, K., Zhang, H., Lu, P., Fang, Q., Ni, H.
  • Journal: Metallurgical and Materials Transactions B: Process Metallurgy and Materials Processing Science
  • Year: 2024

Optimization of Multiphase Flow and Initial Solidification Behaviors in a Stainless Steel Mold by SEN Design

  • Authors: Gao, F., Fang, Q., Zha, W., Zhang, H., Ni, H.
  • Journal: Metallurgical and Materials Transactions B: Process Metallurgy and Materials Processing Science
  • Year: 2024

Dr. Irsa Sajjad | Machine Learning | Best Researcher Award

Dr. Irsa Sajjad, Machine Learning, Best Researcher Award

Doctorate at Central South University, China

Profiles

Scopus

Google Scholar

🌍 Academic Background:

Dr. Irsa Sajjad is a Research Scholar at Central South University, Changsha, China, known for her expertise in hybrid choice modeling and machine learning. Her innovative research integrates deep learning and attention mechanisms, significantly advancing methodologies and applications in the field.

🎓 Education:

Dr. Irsa’s academic background is marked by advanced studies in machine learning and choice modeling, equipping her with a comprehensive understanding of both theoretical concepts and practical applications in her field.

👩‍🏫 Professional Experience:

Dr. Irsa has actively contributed to significant research projects, including developing novel hybrid choice models and Gaussian mixture models. She has collaborated with industry partners on machine learning applications and data visualization techniques and is currently publishing a book on advanced choice modeling.

🔬 Research Interests:

Dr. Irsa’s research interests center on Hybrid Choice Models (HCM), particularly those incorporating attention mechanisms, deep learning, and latent class analysis. Her work aims to enhance the accuracy and effectiveness of choice modeling by addressing complex data structures and improving analytical insights.

📖 Publications:

Advancing Covid-19 Data Modeling: Introducing a Neutrosophic Extension of Ramous Louzada Distribution
  • Authors: Al-Aziz, S.N., Sajjad, I., Dar, J.G., El Bagoury, A.A.-A.H.
  • Journal: International Journal of Neutrosophic Science
  • Year: 2023
Quantile regression-ratio-type estimators for mean estimation under complete and partial auxiliary information
  • Authors: Shahzad, U., Hanif, M., Sajjad, I., Anas, M.M.
  • Journal: Scientia Iranica
  • Year: 2022
Mathematical Simulation and Numerical Computation of the Temperature Profiles in the Peripherals of Human Brain during the Tepid Sponge Treatment to Fever
  • Authors: Aijaz, M., Dar, J.G., Almanjahie, I.M., Sajjad, I.
  • Journal: Computational and Mathematical Methods in Medicine
  • Year: 2022
Imputation based mean estimators in case of missing data utilizing robust regression and variance–covariance matrices
  • Authors: Shahzad, U., Al-Noor, N.H., Hanif, M., Sajjad, I., Muhammad Anas, M.
  • Journal: Communications in Statistics: Simulation and Computation
  • Year: 2022
A new family of robust regression estimators utilizing robust regression tools and supplementary attributes
  • Authors: Sajjad, I., Hanif, M., Koyuncu, N., Shahzad, U., Al-Noor, N.H.
  • Journal: Statistics in Transition New Series
  • Year: 2021

Mr. Nikolaos Argirusis | Machine Learning | Industry Impact Award

Mr. Nikolaos Argirusis, Machine Learning, Industry Impact Award

Nikolaos Argirusis at mat4nrg GmbH, Germany

Profiles

Scopus

Orcid

🎓Education:

Mr. Nikolaos Argirusis pursued his education at Ostfalia University of Applied Sciences, specializing in Energy Systems and Environmental Engineering, achieving a “Very Good” rating in his Master’s degree. Previously, he completed his Bachelor’s in Electrical and Information Technology at Ostfalia University, with a focus on Electromobility and Energy Technology. He also holds a Bachelor’s degree in Electrical Engineering from Technische Universität Braunschweig, specializing in Energy Technology.

💼 Work Experience:

Currently, Nikolaos serves as a Student Assistant at CZM – TU Clausthal, where he contributes to electronics development and plasma technology experiments. He also engages in a research project for mat4nrg GmbH, focusing on prototype development and project organization. As the Co-founder and Managing Director of mat4nrg GmbH, he oversees the management, supervision, and development of research and customer projects. Additionally, Nikolaos supports his family’s business, aeras GmbH, focusing on power electronics assembly.

🌐 Skills and Languages:

He possesses advanced skills in Microsoft Office, PSpice, and LTspice, with foundational knowledge in C++ and Java programming languages. Fluent in German and Greek, Nikolaos also communicates proficiently in English.

🎯 Interests:

Outside of academics and professional endeavors, Nikolaos enjoys swimming, team sports, and engaging in DIY projects, reflecting his diverse interests and active lifestyle.

📖 Publications:

Evaluation of the effectiveness and performance of environmental impact assessment studies in Greece
  • Authors:Papamichael, I., Tsiolaki, F., Stylianou, M., Argirusis, C., Zorpas, A.A.
  • Journal:Comptes Rendus Chimie
  • Year: 2023
End-of-Life Management and Recycling on PV Solar Energy Production
  • Authors:Papamichael, I., Voukkali, I., Jeguirim, M., Argirusis, C., Zorpas, A.A.
  • Journal: Energies
  • Year: 2022
Research Progress in Metal-Organic Framework Based Nanomaterials Applied in Battery Cathodes
  • Authors: Mechili, M., Vaitsis, C., Argirusis, N., Zorpas, A.A., Argirusis, C.
  • Journal: Energies
  • Year: 2022
Research progress in transition metal oxide based bifunctional electrocatalysts for aqueous electrically rechargeable zinc-air batteries
  • Authors: Mechili, M., Vaitsis, C., Argirusis, N., Sourkouni, G., Argirusis, C.
  • Journal: Renewable and Sustainable Energy Reviews
  • Year: 2022
MOF nanomaterials for battery cathodes
  • Authors: Vaitsis, C., Mechili, M., Pandis, P.K., Argirusis, N., Sourkouni, G.
  • Year: 2022