Zakir Hussain | Neural Networks | Best Researcher Award

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Dr. Zakir Hussain | Neural Networks | Best Researcher Award

Dr. Zakir Hussain, University of Baltistan, Skardu, Pakistan

Dr. Zakir Hussain is the Head of the Department of Mathematics at the University of Baltistan, Skardu, Pakistan. He holds a PhD in Fluid Mechanics from Quaid-i-Azam University, Islamabad, and has extensive expertise in data science, artificial intelligence, and computational fluid dynamics. With over 140 research publications and a significant impact factor, Dr. Hussain is an established reviewer for international journals and an active contributor to advancements in data-driven solutions, numerical simulations, and AI applications in fluid mechanics. His research and teaching emphasize machine learning, mathematical modeling, and innovative computational techniques in applied mathematics.

Summary:

Dr. Zakir Hussain exemplifies the qualities of a Best Researcher Award recipient through his extensive contributions to fluid mechanics, AI, and applied mathematics. With a solid academic background, proven research impact, and substantial publication record, he has made significant advancements in computational fluid dynamics and data science applications. His leadership role in the Department of Mathematics also underscores his commitment to fostering research and innovation within his institution and beyond.

 

Professional Profiles:

Scopus

šŸŽ“Education:

Dr. Hussain completed a PhD in Fluid Mechanics from Quaid-i-Azam University, Islamabad, followed by multiple diplomas and certifications, most recently in Data Science and Artificial Intelligence at the National University of Sciences and Technology, Islamabad. His earlier qualifications include an MSc and MPhil in Applied Mathematics from Quaid-i-Azam University.

šŸ¢Experience:

With over a decade in academia, Dr. Hussain currently serves as Head of the Mathematics Department at the University of Baltistan, Skardu. His roles have included lecturer positions and research associate roles at multiple institutions, with a focus on applied mathematics and fluid mechanics. He has progressively taken on more administrative responsibilities, including serving on various university committees and leading examination processes for affiliated colleges.

šŸ› ļøSkills:

Dr. Zakir Hussain possesses extensive expertise in various technical and computational techniques, including Python, MATLAB, Mathematica, ANSYS, COMSOL, and advanced numerical methods like the Keller Box and Finite Volume Method. His skills span data science, machine learning, artificial intelligence, and computational fluid dynamics, along with specific proficiencies in data visualization, image processing, and numerical simulations.

Awards :

Dr. Hussain is a highly recognized academic, having reviewed over 20 leading international journals and authored more than 141 articles, with a collective impact factor exceeding 150. His accolades include merit scholarships during both his MPhil and PhD studies, in addition to his participation in varsity athletics, representing Quaid-i-Azam University in hockey and athletic championships.

Conclusion:

Dr. Zakir Hussainā€™s credentials make him a suitable candidate for the Best Researcher Award, with his numerous high-impact publications, academic service, and research contributions establishing him as a leader in his field. Enhancing international collaborations and research funding opportunities would further bolster his already strong candidacy for this honor.

 

Research Focus:

Dr. Hussainā€™s research interests are centered on data science, artificial intelligence, and fluid dynamics, with a specific focus on machine learning, deep learning, and neural networks. His expertise includes applied mathematics in computational fluid dynamics and non-Newtonian fluid flow, numerical simulations in blood flow and boundary layer analysis, as well as innovative applications of AI in mathematical modeling and data-driven solutions in fluid dynamics.

Publications :
  • Hussain, Z., Alghamdi, M., Aslam, M. N., & Muhammad, T. (2025). Morlet-wavelet neural networks and sensitivity analysis in magnetized peristaltic flow subject to Soretā€“Dufour effects: An unsupervised approach. International Communications in Heat and Mass Transfer, 160, 108259.

 

  • Hussain, Z., Fazia, & Anwar, M. S. (2024). Neural network approach to investigate heat transfer in SWCNTs nanofluid within trapezoidal cavity with varied corrugated rod amplitudes. Physica Scripta, 99(10), 105257.

 

  • Hussain, Z., Alghamdi, M., Muhammad, T., & Anwar, M. S. (2024). Lid-driven effect on convective heat transfer with heated rods in a modified equilateral triangular cavity. Case Studies in Thermal Engineering, 61, 104908.

 

  • Anwar, M. S., Alam, M. M., Khan, M. A., Hussain, Z., & Puneeth, V. (2024). Generalized viscoelastic flow with thermal radiations and chemical reactions. Geoenergy Science and Engineering, 232, 212442.

 

  • Hussain, Z., Alghamdi, M., Fozia, Ali, M. R., & Aslam, M. (2023). Significance of mixed convective heat transfer model in an equilateral triangular enclosure subjected to cylindrical heated objects inside. Case Studies in Thermal Engineering, 47, 103027.

 

  • Anwar, M. S., Hussain, M., Hussain, Z., Puneeth, V., & Irfan, M. (2023). Clay-based cementitious nanofluid flow subjected to Newtonian heating. International Journal of Modern Physics B, 37(14), 2350140.

 

  • Alghamdi, M., Fatima, B., Hussain, Z., Nisar, Z., & Alghamdi, H. A. (2023). Peristaltic pumping of hybrid nanofluids through an inclined asymmetric channel: A biomedical application. Materials Today Communications, 35, 105684.

 

  • Raza, U., Anwar, M. S., Ali, H., Irfan, M., & Hussain, Z. (2023). Fixed points in n-gonal graphical b-metric spaces under contractive conditions. International Journal of Modern Physics B, 37(4), 2350039.

 

  • Anwar, M. S., Puneeth, V., Hussain, M., Hussain, Z., & Irfan, M. (2023). Heat Convection in a Viscoelastic Nanofluid Flow: A Memory Descriptive Model. Journal of Applied Nonlinear Dynamics, 12(2), 363ā€“378.

 

  • Hussain, Z., Alshomrani, A. S., Muhammad, T., & Anwar, M. S. (2022). Entropy analysis in mixed convective flow of hybrid nanofluid subject to melting heat and chemical reactions. Case Studies in Thermal Engineering, 34, 101972.

Jianliang Gao | simulation |Best Researcher Award

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Dr. Jianliang Gao | simulation |Best Researcher AwardĀ 

Dr.Jianliang Gao,South China University of Technology,China

Dr. Jianliang Gao is a distinguished professor at the South China University of Technology in China, known for his expertise and contributions in advanced materials engineering. His research focuses on materials science, nanotechnology, and applications of novel materials in energy and environmental solutions. Dr. Gao has published extensively in prestigious journals and has received multiple accolades for his innovative research. He actively collaborates with industry and academic partners worldwide, advancing cutting-edge technologies and inspiring the next generation of engineers and scientists.

Summary:

Dr. Jianliang Gao is a dedicated and well-published researcher with a strong foundation in acoustics research, including sound field simulations and site measurements. His academic journey, awards, and research funding all illustrate his deep commitment to advancing knowledge in architectural acoustics. His recent research funding and his postdoctoral role at a prominent Chinese university highlight his potential to make impactful contributions to the field.

Professional Profiles:

Scopus

šŸŽ“Education:

Dr. Jianliang Gao has an extensive educational background in architectural acoustics. He earned his Ph.D. in Architectural Acoustics from the Hong Kong Polytechnic University in 2021, under the guidance of notable supervisors including Prof. Shiu Keung Tang, Prof. Shuoxian Wu, and Prof. Yuezhe Zhao. Earlier, he pursued part of his Ph.D. at South China University of Technology but eventually completed his doctoral studies in Hong Kong. His master’s degree, M.Sc. in Building Technology Science, was awarded by the South China University of Technology in 2014. Dr. Gao also holds a B.Sc. in Architecture from the China University of Petroleum, where he began his academic journey.

šŸ¢Experience:

Currently, Dr. Gao serves as a Postdoctoral Fellow at the State Key Laboratory of Subtropical Building and Urban Science within the School of Architecture at the South China University of Technology. His research, overseen by Prof. Yuezhe Zhao, focuses on critical areas in architectural acoustics. He has also gained valuable teaching experience as a lecturer and supervisor in architectural courses, such as CAD fundamentals, at institutions including The Hong Kong Polytechnic University and Guangdong Polytechnic of Science and Technology.

šŸ› ļøSkills:

Dr. Gaoā€™s skills are specialized in room acoustics, acoustic scale model experimentation, signal processing and analysis, and sound absorption and scattering properties of materials. His expertise further extends to computer simulations and site measurement of sound fields in performance halls. Additionally, he is proficient in using scientific software and methodologies to analyze complex acoustic environments.

Awards :

Dr. Gao has received numerous awards and honors, notably including the Postdoctoral Fellowship of the Pearl River Talent Scheme (2022-2024), which supports distinguished researchers in Guangdong Province. During his Ph.D. studies, he was awarded a full scholarship by The Hong Kong Polytechnic University and received several scholarships and awards for academic excellence throughout his educational journey, including the First Class Academic Scholarship for Masters from the South China University of Technology.

Conclusion:

Dr. Jianliang Gao is a highly suitable candidate for the Research for Best Researcher Award. His achievements and dedication to acoustics research, combined with a proactive approach to both publishing and grant acquisition, underscore his readiness for this recognition. With further outreach and cross-disciplinary engagements, he could increase the influence of his work even further, making him an outstanding candidate for this award.

Research Focus:

Dr. Gaoā€™s research is primarily centered on architectural acoustics, specifically in areas such as room acoustics, energy decay in performance spaces, and acoustical parameters in theaters and auditoriums. His work often involves experimental and computational approaches to analyze and optimize sound properties in various architectural settings, with a recent focus on the acoustics of proscenium theaters and the vocal characteristics relevant to performance halls in Chinese folk singing. Dr. Gaoā€™s contributions are evidenced by his publications in reputable journals and presentations at international conferences..

Publications :

  • “Semi-analytical prediction of energy-based acoustical parameters in proscenium theatres”
    • Authors: Gao, J.; Keung Tang, S.; Zhao, Y.; Wu, S.; VorlƤnder, M.
    • Journal: Applied Acoustics
    • Year: 2025
    • Citations: 0

 

  • “The Effects of Sound Absorption of Stage House on the Acoustics of Auditorium in an Opera House”
    • Authors: Gao, J.; Zhao, Y.; Pan, L.
    • Journal: Buildings
    • Year: 2024
    • Citations: 1

 

  • “Aero-acoustics study of coupled cavities in close proximity along a rectangular flow duct at low Mach number”
    • Authors: Tang, Y.J.; Gan, L.; Liang, C.; Gao, J.L.; Zhang, S.Z.
    • Journal: Journal of Physics: Conference Series
    • Year: 2024
    • Citations: 0

 

  • “On the performance of existing acoustic energy models when applied to multi-purpose performance halls”
    • Authors: Gao, J.; Tang, S.K.; Zhao, Y.; Cai, Y.; Pan, L.
    • Journal: Applied Acoustics
    • Year: 2020
    • Citations: 6

 

  • “Factors influencing scattering coefficient measurement accuracy in scaled reverberation room”
    • Authors: Pan, L.; Zhao, Y.; Gao, J.
    • Journal: Applied Acoustics
    • Year: 2020
    • Citations: 5

 

  • “Applicability analysis of the revised acoustic energy model for concert auditoriums to predict energy relations in a scaled opera house”
    • Authors: Gao, J.; Tang, S.-K.; Zhao, Y.; Wu, S.
    • Year: 2017
    • Citations: 2