Prof. Igor Belenichev | Machine Learning | Excellence in Innovation

Posted on by ScienceFather

Prof. Igor Belenichev | Machine Learning | Excellence in Innovation

Professor at Zaporizhzhia State Medical University, Ukraine

Profiles

Scopus

Orcid

Google Scholar

📚 Summary

Prof. Igor Fedorovich Belenichev is a distinguished Full Professor and Head of the Department of Pharmacology and Medical Formulation at Zaporizhzhia State Medical University. Renowned for his innovative research in neuroprotection and pharmacology, he is a laureate of the Cabinet of Ministers of Ukraine Prize for the development and implementation of groundbreaking technologies.

Education

  • Zaporizhzhia State Medical Institute (1988): Graduated with a degree in medicine.
  • Postgraduate studies (1988), professor assistant (1991), senior teacher (1999), associate professor (2004), and full professor (2006).

💼 Professional Experience

  • Zaporizhzhia State Medical University: Head of the Department of Pharmacology and Medical Formulation since 2005.
  • Main Scientific Researcher at «Pharmatrone» (since 1993).
  • Head of the regional branch of the Association of Pharmacologists of Ukraine.
  • Co-worker of the regional group of the National Expert Centre of the Ministry of Health of Ukraine.

🔬 Research Interests

Prof. Belenichev’s research focuses on the molecular and biochemical mechanisms of ischemic brain damage and the development of effective neuroprotectors. His work explores the roles of reactive oxygen and nitrogen species, thiol-disulfide systems, pro-/anti-apoptotic proteins, estrogen receptors, and endogenous neuroprotection factors. He also investigates drugs for CNS pathologies and effective neuro- or cardioprotectors from derivatives of 1,2,4-triazole, chinazoline, and xanthine.

🏆 Achievements

  • Scientific Works: Authored and co-authored 715 scientific publications.
  • Patents: Holder of 182 patents in Ukraine and the Russian Federation.
  • Theses: Supervised 3 Dr. Habs and 7 Ph.D. theses.
  • Drug Development: Contributed to the creation of drugs like Thiotriazoline, Thiocetam, and Thiodarone.
  • Awards: Token of the Bibliographical Society of America (2003), Regional Program “Zoryaniy Shlyakh” Prize (2000), and Cabinet of Ministers of Ukraine Prize (2017).

 

Publications

5+1-Heterocyclization as preparative approach for carboxy-containing triazolo[1,5-c]quinazolines with anti-inflammatory activity

  • Authors: Krasovska, Natalya; Berest, Galina; Belenichev, Igor; Severina, Hanna; Nosulenko, Inna; Voskoboinik, Oleksii; Okovytyy, Sergiy; Kovalenko, Serhii
  • Journal: European Journal of Medicinal Chemistry
  • Year: 2024

Beta-Blockers of Different Generations: Features of Influence on the Disturbances of Myocardial Energy Metabolism in Doxorubicin-Induced Chronic Heart Failure in Rats

  • Authors: Igor Belenichev; Olexiy Goncharov; Nina Bukhtiyarova; Oleh Kuchkovskyi; Victor Ryzhenko; Lyudmyla Makyeyeva; Valentyn Oksenych; Oleksandr Kamyshnyi
  • Journal: Biomedicines
  • Year: 2024

Characteristics of HIF-1α and HSP70 mRNA Expression, Level, and Interleukins in Experimental Chronic Generalized Periodontitis

  • Authors: Parkhomenko Daria; Igor Belenichev; Kuchkovskyi Oleh; Ryzhenko Victor
  • Journal: MicroRNA
  • Year: 2024

Comparative Analysis of the Effect of Beta Blockers of Different Generations on the Parameters of Myocardial Energy Metabolism in Experimental Doxorubicin-Induced Chronic Heart Failure

  • Authors: Igor Belenichev; Olexiy Goncharov; Nina Bukhtiyarova; Oleh Kuchkovskyi; Victor Ryzhenko; Lyudmyla Makyeyeva; Valentyn Oksenych; Oleksandr Kamyshnyi
  • Journal: Preprint
  • Year: 2024

Development and Optimization of Nasal Composition of a Neuroprotective Agent for Use in Neonatology after Prenatal Hypoxia

  • Authors: Igor Belenichev; Olena Aliyeva; Bogdan Burlaka; Kristina Burlaka; Oleh Kuchkovskyi; Dmytro Savchenko; Valentyn Oksenych; Oleksandr Kamyshnyi
  • Journal: Pharmaceuticals
  • Year: 2024

Dr. Kais Iben Nassar | Machine Learning | Best Researcher Award

Posted on by ScienceFather

Dr. Kais Iben Nassar | Machine Learning | Best Researcher Award

Doctorate at University of Aveiro , Portugal

Profiles

Scopus

Orcid

Google Scholar

Academic Background

Dr. Kais Iben Nassar is a researcher with a focus on Condensed Matter Physics and Computational Chemistry. He completed his PhD in Physics of Condensed Materials in 2022 through a joint program between the University of Aveiro, Portugal, and the University of Sfax, Tunisia. Dr. Nassar is renowned for his work in materials science, particularly in the study of 2D materials like MXenes and their applications in energy storage and catalysis.

Education

  • PhD in Physics of Condensed Materials
    Université de Sfax & Universidade de Aveiro (2022)
    Achieved with highest honors.
  • Master’s in Condensed Matter Physics
    Université de Sfax (2018)
    Graduated with distinction.
  • Fundamental License in Physics-Chemistry
    Université de Sfax (2016)
    Graduated with distinction.

Professional Experience

  • Postdoctoral Researcher
    Universidade de Aveiro, CICECO (2023 – Present)
    Focus on MXenes catalysts and computational chemistry.
  • Researcher
    Université de Sfax & Universidade de Aveiro (2018 – 2021)
    Conducted research on perovskites and materials science.
  • Invited Assistant Professor
    Université de Sfax (2021 – 2022)
    Taught and mentored students in physics and chemistry.

🔬 Research Interests

Dr. Nassar’s research interests encompass Condensed Materials Physics, nano-materials, computational chemistry, and machine learning. His work includes investigating the properties of 2D materials such as MXene, exploring their potential in energy storage, catalysis, and electronics. He is actively engaged in the preparation and characterization of new perovskite ceramics and the study of their structural, electrical, and magnetic properties. Dr. Nassar is also a member of the European Materials Acceleration Center for Energy (EU-MACE) under the COST Action CA22123.

 Publications

Tailoring of structural, morphological, electrical, and magnetic properties of LaMn1−xFexO3 ceramics
  • Authors: Thakur, P., Nassar, K.I., Kumar, D., Essid, M., Lal, M.
  • Journal: RSC Advances
  • Year: 2024
Structural, electrical properties of bismuth and niobium-doped LaNiO3 perovskite obtained by sol–gel route for future electronic device applications
  • Authors: Nassar, K.I., Benamara, M., Kechiche, L., Teixeira, S.S., Graça, M.P.F.
  • Journal: Indian Journal of Physics
  • Year: 2024
Investigating Fe-doped Ba0.67Ni0.33Mn1−xFexO3 (x = 0, 0.2) ceramics: insights into electrical and dielectric behaviors
  • Authors: Tayari, F., Iben Nassar, K., Algessair, S., Hjiri, M., Benamara, M.
  • Journal: RSC Advances
  • Year: 2024
Sol–gel synthesized (Bi0.5Ba0.5Ag)0.5 (NiMn)0.5O3 perovskite ceramic: An exploration of its structural characteristics, dielectric properties and electrical conductivity
  • Authors: Tayari, F., Iben Nassar, K., Benamara, M., Soreto Teixeira, S., Graça, M.P.F.
  • Journal: Ceramics International
  • Year: 2024
Study of Electrical and Dielectric Behaviors of Copper-Doped Zinc Oxide Ceramic Prepared by Spark Plasma Sintering for Electronic Device Applications
  • Authors: Benamara, M., Iben Nassar, K., Rivero-Antúnez, P., Serrà, A., Esquivias, L.
  • Journal: Nanomaterials
  • Year: 2024

Ms. Linjing Wei | Deep Learning | Best Researcher Award

Posted on by ScienceFather

Ms. Linjing Wei | Deep Learning | Best Researcher Award

Linjing Wei at Gansu Agricultural University, China

Profile

Scopus

Academic Background:

Ms. Linjing Wei is a distinguished female professor at Gansu Agricultural University, specializing in Grassland Science with a research focus on Grassland Informatics. Born in July 1977, she has made significant contributions to her field through her extensive research, academic guidance, and numerous publications.

Education:

Ms. Wei earned her PhD in Grassland Science from Gansu Agricultural University in June 2015. Her educational background has provided a strong foundation for her academic and research pursuits.

Professional Experience:

Ms. Wei teaches several courses for master’s students, including Introduction to Cloud Computing, Case Analysis of Software Engineering, Information Systems and Information Resource Management, and Distributed Systems and Cloud Computing Technology. As the first supervisor, she has guided numerous master’s students in various majors, particularly in Agricultural Engineering and Information Technology.

Research Interests:

Ms.Wei's research interests lie in Grassland Informatics. Over the past five years, she has led several key research projects with significant funding, focusing on areas such as data resource integration, intelligent cloud platforms for agricultural logistics, ecosystem restoration and monitoring, sustainable development planning, and trustworthy traceability systems for agricultural products. Her published works include papers in prestigious journals like Sensors and the Canadian Journal of Remote Sensing, as well as contributions to national-level textbooks and academic monographs.

📝 Academic Achievements:

Ms. Wei has an impressive list of published papers, including "Fine Segmentation of Chinese Character Strokes Based on Co-ordinate Awareness and Enhanced BiFPN" in Sensors (2024), "Enhanced Wheat Head Detection in Images Using Fourier Domain Adaptation and Random Guided Filter" in Canadian Journal of Remote Sensing (2024), and "Feature Selection in High Dimensional Biomedical Data Based on BF-SFLA" in Neurogenetics (2022).

 Publications:

Fine Segmentation of Chinese Character Strokes Based on Coordinate Awareness and Enhanced BiFPN
  • Authors:Mo, H., Wei, L.
  • Journal: Sensors
  • Year: 2024
A Smart Chicken Farming Platform for Chicken Behavior Identification and Feed Residual Estimation
  • Authors: Yang, J., Gao, J., Li, Y., Lu, Q., Zheng, H.
  • Journal: Proceedings - 2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023
  • Year: 2023
Feature Selection in High Dimensional Biomedical Data Based on BF-SFLA
  • Authors: Dai, Y., Niu, L., Wei, L., Tang, J.
  • Journal: Frontiers in Neuroscience
  • Year: 2022
Jointly Learning Topics in Sentence Embedding for Document Summarization
  • Authors: Gao, Y., Xu, Y., Huang, H., Wei, L., Liu, L.
  • Journal: IEEE Transactions on Knowledge and Data Engineering
  • Year: 2020
Study on the Matching Algorithm of Turf Grass Introduction Features Based on Big Data Analysis
  • Authors: Wei, L., Dong, W., Gan, S., Wang, Y.
  • Year: 2019

Dr. Seyed Hamed Godasiaei | Deep Learning | Best Researcher Award

Posted on by ScienceFather

Dr. Seyed Hamed Godasiaei, Deep Learning, Best Researcher Award

Doctorate at Xi’an Jiaotong University, China

Professional Profile

Summary:

Dr. Seyed Hamed Godasiaei is a versatile professional with a rich background in chemical engineering, research, and development. His career spans various disciplines, showcasing expertise in computational fluid dynamics (CFD), machine learning applications, environmental experiments, and heat transfer analysis.

🎓 Education:

  • Ph.D. in Chemical Engineering: Xi’an Jiaotong University
  • M.S. in Chemical Engineering: Islamic Azad University of Shahrood
  • Bachelor’s in Chemical Engineering: Islamic Azad University of Birjand

💼 Professional Experience

  • Welding and Mapping GIS: Dr. Godasiaei has applied his skills in welding techniques and Geographic Information System (GIS) mapping to various projects.
  • Lab Researcher: His research includes extensive work in environmental experiments and heat transfer studies.
  • Python for Machine Learning: He leverages Python programming for advanced applications in machine learning.
  • C++ Programming: Proficient in C++ for developing computational models and simulations.

🏆 Achievements & Awards:

  • elected as a top researcher by the Iranian National Standards Organization.
  • Recognized for environmental research contributions at KhatamToos Co, Iran.

Skills and Expertise:

Dr. Godasiaei is proficient in a wide array of software and tools essential for his research and professional endeavors, including Ansys Fluent, Ansys CFX, CFD-Post, ICEM CFD, Space Claim, Gambit, STAR-CCM+, AutoCAD, Photoshop, CorelDRAW, SolidWorks, Comsol, openLB, and Python programming.

 

Publications Top Noted:

Paper Title: Water jet angle prediction in supersonic crossflows: Euler–Lagrange and machine learning approaches
  • Authors: S.H. Godasiaei, H. Kamali
  • Journal: European Physical Journal Plus
  • Volume: 139
  • Issue: 3
  • Pages: 251
  • Year: 2024
  • Citations: 3
Paper Title: Exploring novel heat transfer correlations: Machine learning insights for molten salt heat exchangers
  • Authors: S.H. Godasiaei, A.J. Chamkha
  • Journal: Numerical Heat Transfer; Part A: Applications
  • Year: 2024
  • Citations: 2
Paper Title: Ballistic limit evolution of field-aged flexible multi-ply UHMWPE-based composite armour inserts
  • Authors: S.H. Godasiaei
  • Journal: Numerical Heat Transfer; Part A: Applications
  • Year: 2024
Paper Title: Saturated/subcooled flow boiling heat transfer inside micro/mini-channels: A new prediction correlation and experiment evaluation
  • Authors: X. Ma, X. Ji, C. Hu, J. Wei, S.H. Godasiaei
  • Journal: International Journal of Heat and Mass Transfer
  • Volume: 210
  • Pages: 124184
  • Year: 2023
  • Citations: 5
Paper Title: Advancing heat transfer modeling through machine learning: A focus on forced convection with nanoparticles
  • Authors: S.H. Godasiaei, A.J. Chamkha
  • Journal: Numerical Heat Transfer; Part A: Applications
  • Year: 2023