Jiangjun Peng | Mathematics | Best Researcher Award – 1961

Assoc. Prof. Jiangjun Peng | Mathematics | Best Researcher Award 

Associate Professor at Northwestern Polytechnical University | China

Asso. Prof. Jiangjun Peng is a distinguished scholar at the School of Mathematics and Statistics, Northwestern Polytechnical University, whose academic journey has been defined by dedication to advancing high-dimensional data analysis and intelligent algorithms. With a career spanning both academia and industry, he has significantly contributed to the areas of tensor data analysis, deep learning, and hyperspectral image processing. His research outcomes have received recognition in leading international journals, often being cited widely across disciplines. Beyond his technical expertise, he has actively engaged with the academic community as a reviewer, speaker, and contributor to professional associations.

Profile:

Orcid | Google Scholar

Education:

Asso. Prof. Jiangjun Peng’s educational background is deeply rooted in applied mathematics and statistics. He completed his bachelor’s degree in computational mathematics at Northwestern University, securing a strong foundation in analytical and numerical methods. His postgraduate studies at Xi’an Jiaotong University included both master’s and doctoral degrees, where he trained under the guidance of eminent professors. His doctoral research emphasized robust mathematical models for image processing, supported by rigorous statistical frameworks. This academic pathway equipped him with the technical knowledge, critical thinking, and problem-solving skills that now shape his innovative approaches to high-dimensional data representation.

Experience:

Asso. Prof. Jiangjun Peng’s professional experience bridges academia, industry, and collaborative research institutions. He began his career contributing as a researcher at the Tencent Video Search Center, where he developed advanced algorithms for large-scale video analysis. Later, he expanded his expertise as an assistant researcher at the Chinese University of Hong Kong, focusing on smart city applications and computational methods. Currently serving as an associate professor at Northwestern Polytechnical University, he leads multiple funded projects in collaboration with government, academic, and industrial bodies. His cross-sectoral experience underscores his ability to translate theoretical models into impactful real-world applications.

Research Interest:

Asso. Prof. Jiangjun Peng’s research interests lie at the intersection of applied mathematics, artificial intelligence, and remote sensing. He is particularly focused on tensor data analysis, hyperspectral image processing, and deep learning methods for high-dimensional data. His work involves developing robust algorithms that improve data recovery, denoising, and representation under noisy or incomplete conditions. These contributions have advanced the fields of image security, medical imaging, and environmental monitoring. He is also passionate about bridging model-driven and data-driven methodologies, enabling new solutions that integrate theoretical mathematics with cutting-edge machine learning for scientific and industrial innovation.

Awards and Honors:

Asso. Prof. Jiangjun Peng has earned recognition through prestigious institutional and industry awards that reflect both academic excellence and applied research contributions. His early research was honored with multiple scholarships and university-level accolades, highlighting his scholarly potential. His innovative work at Tencent earned him an industry award for advancing video data applications, while his collaborative project with Huawei received the Huawei Spark Award, showcasing successful academia-industry synergy. More recently, he was selected among the Rising Stars of Northwestern Polytechnical University, a distinction reserved for outstanding young faculty whose work shapes the future of scientific and technological advancement.

Publications:

Title: Hyperspectral image restoration via total variation regularized low-rank tensor decomposition
Citation: 474
Year of Publication: 2017

Title: Enhanced 3DTV regularization and its applications on HSI denoising and compressed sensing
Citation: 188
Year of Publication: 2020

Title: Guaranteed tensor recovery fused low-rankness and smoothness
Citation: 108
Year of Publication: 2023

Title: Exact Decomposition of Joint Low Rankness and Local Smoothness Plus Sparse Matrices
Citation: 93
Year of Publication: 2022

Title: Classical scoring functions for docking are unable to exploit large volumes of structural and interaction data
Citation: 90
Year of Publication: 2019

Title: Fast Noise Removal in Hyperspectral Images via Representative Coefficient Total Variation
Citation: 65
Year of Publication: 2022

Title: Learnable representative coefficient image denoiser for hyperspectral image
Citation: 16
Year of Publication: 2024

Conclusion:

Asso. Prof. Jiangjun Peng stands as a highly impactful researcher, educator, and innovator whose career seamlessly integrates theoretical mathematics with practical technological applications. His contributions to tensor analysis, hyperspectral imaging, and deep learning have not only advanced scientific understanding but also enabled real-world breakthroughs in security, healthcare, and environmental monitoring. Through prestigious awards, widely cited publications, and influential collaborations with industry leaders, he has demonstrated both academic brilliance and societal relevance. His nomination for this award is a recognition of his exceptional potential to continue shaping the future of data science and applied mathematics.

Taqmeem Bibi | Mathematics | Best Scholar Award

Ms. Taqmeem Bibi | Mathematics | Best Scholar Award

PhD Scholar at Beijing Forestry University, Beijing, 100083, China, China.

🌍Dr. Taqmeem Bibi is a Pakistani scholar specializing in fluid mechanics, particularly focusing on the analysis of linear and nonlinear partial differential equations (PDEs) using numerical techniques. Her research includes fluid flow with nanoparticles, hybrid nanofluids, and entropy optimization, with applications in heat and mass transfer and energy-efficient systems. She holds an M.Phil. degree, where her thesis explored hybrid nanofluid flow containing motile microorganisms under the Cattaneo-Christov double diffusion model. Dr. Bibi is proficient in advanced computational tools such as MATLAB, Mathematica, and LaTex, and she has published impactful research in peer-reviewed journals. Her accolades include multiple merit scholarships, Dean’s Roll of Honor awards, and a prestigious Chinese Government Scholarship for her PhD studies.

Profile👤

Education 🎓

🎓Dr. Taqmeem Bibi has pursued a stellar academic journey across leading institutions. She earned her B.Sc. from the University of Punjab, Lahore, followed by an M.Sc. in Mathematics from Riphah International University, Islamabad, where she received merit scholarships for academic excellence. Continuing her dedication to higher education, she completed her M.Phil. at Capital University of Science and Technology, Islamabad, with a focus on hybrid nanofluids. Her thesis titled “Flow Analysis of (TiO2 + Ag)/EO Hybrid Casson Nanofluid Containing Motile Micro-Organisms Subjected to Cattaneo-Christov Double Diffusion” reflects her expertise in applying numerical methods to real-world fluid mechanics challenges. Dr. Bibi is now pursuing her Ph.D. at Beijing Forestry University, China, under the Chinese Government Scholarship, where she explores advanced numerical techniques for solving nonlinear PDEs in fluid dynamics. Her education highlights her academic excellence and unwavering commitment to innovative research.🎓

Experience💼

🩺Dr. Taqmeem Bibi has a robust research background in fluid mechanics and numerical analysis. Her work involves solving complex partial differential equations (PDEs) using advanced numerical techniques, particularly focusing on hybrid nanofluids and their applications in energy-efficient systems. She has collaborated with renowned researchers, including Prof. Dr. Wang Ping from Beijing Forestry University and Dr. Muhammad Sagheer from Capital University of Science and Technology, Islamabad. Dr. Bibi has contributed to high-impact journals and participated in academic events such as the CUST Mathematics Conference in 2023. Beyond research, she is skilled in using computational tools like MATLAB and Mathematica, enabling her to tackle multidisciplinary challenges in applied mathematics. Her expertise in fluid dynamics, numerical solutions, and cryptography showcases her versatility as a researcher and academic.👨‍🔬🌍

Awards and Honors 🏆

Dr. Taqmeem Bibi has consistently demonstrated academic excellence, earning several prestigious awards and scholarships. She received merit scholarships during her B.Sc., M.Sc., and M.Phil. studies, recognizing her outstanding academic performance. During her M.Phil. at Capital University of Science and Technology, Islamabad, she was twice awarded the Dean’s Roll of Honor for her exceptional achievements. Currently, she is the recipient of the highly competitive Chinese Government Scholarship for her Ph.D. at Beijing Forestry University, China. These accolades reflect her dedication to advancing knowledge in fluid mechanics and numerical analysis. Dr. Bibi’s recognition for academic excellence underscores her potential as an accomplished researcher and scholar.

Research Interests 🔬

🔬Dr. Taqmeem Bibi’s research centers on fluid mechanics, with a particular focus on hybrid nanofluids and their role in enhancing energy-efficient systems. She employs advanced numerical techniques to analyze linear and nonlinear partial differential equations (PDEs), contributing to the optimization of heat and mass transfer processes. Her work emphasizes the Cattaneo-Christov model for non-Fourier heat flux, entropy optimization, and the behavior of motile microorganisms in hybrid nanofluids. By exploring innovative approaches in computational modeling, Dr. Bibi’s research offers insights into sustainable technologies, including solar energy applications and advanced materials in fluid systems. Her interdisciplinary expertise bridges mathematics, engineering, and environmental sustainability, making significant contributions to applied mathematics and energy-efficient designs.🌿🧪

Conclusion 🔚 

Dr. Taqmeem Bibi stands as a strong candidate for the Best Scholar Award due to her exceptional contributions to applied mathematics and fluid mechanics. Her innovative research, robust publication record, and academic excellence underscore her scholarly impact. Addressing areas such as international engagement and diversified research focus could further elevate her profile. Overall, Dr. Bibi’s expertise and achievements make her highly deserving of recognition as an outstanding scholar.

Publications Top Notes 📚

Numerical investigation of transverse hyperbolic nanofluids flow with motile microorganisms using Cattaneo-Christov model

Authors: Faisal Shah, Taqmeem Bibi, D. Zhang

Journal: Alexandria Engineering Journal

Year: 2023

Citations: Impact Factor = 6.2 (Citation details depend on the indexing database but are not provided in the text).

Computational study of tri-hybrid nanofluid flow through permeable stretching sheet with entropy optimization

Authors: Faisal Shah, Taqmeem Bibi

Journal: ZAMM Zeitschrift Fur Angewandte Mathematik und Mechanik

Year: Under Review (expected publication year may depend on acceptance).

Citations: Not applicable yet.

A theoretical study on (TiO2 + Ag)/EO hybrid Casson nanofluid with motile microorganisms in non-Fourier heat flux model

Authors: Muhammad Sagheer, Taqmeem Bibi, Hussan Shehzad

Journal: Multiscale and Multidisciplinary Modeling

Year: Under Review (expected publication year may depend on acceptance).

Citations: Not applicable yet.

Multidisciplinary optimization approaches for entropy generation in Williamson hybrid nanofluid: Computational insights for solar aircraft efficiency

Authors: Faisal Shah, Taqmeem Bibi

Journal: Structural and Multidisciplinary Optimization

Year: Submitted (expected publication year may depend on acceptance).

Citations: Not applicable yet.