Muhammad Waheed Rasheed | Artificial Intelligence | Best Researcher Award

Mr. Muhammad Waheed Rasheed | Artificial Intelligence | Best Researcher Award

Research Assistant at COMSATS University Islamabad, Vehari Campus, Pakistan

Muhammad Waheed Rasheed is a dedicated mathematician and researcher known for his contributions to cryptography, fuzzy graph theory, and QSPR analysis. His academic and professional pursuits focus on creating innovative solutions to global challenges, particularly in molecular descriptors, graph theory, and their applications in chemistry and physics. With a passion for research and education, Mr. Rasheed embodies excellence in both theoretical and applied mathematics. His publications in high-impact journals like Frontiers in Chemistry and Frontiers in Physics reflect his ability to bridge disciplines and address real-world problems. As a motivated and dependable team player, he thrives in collaborative environments while excelling independently. His research outputs, which span drug efficacy studies and complex mathematical modeling, contribute significantly to scientific advancements and underscore his role as a rising star in the global mathematical community.

Profile

Scopus

Education 🎓

Mr. Rasheed earned an MS in Mathematics (2021–2023) and a BS (Hons) in Mathematics (2017–2021) from the University of Education Lahore, Pakistan, achieving CGPAs of 3.64/4.00 and 3.61/4.00, respectively. His coursework encompassed advanced topics such as algebraic graph theory, numerical methods, Galois theory, real analysis, and differential geometry. This robust educational foundation equipped him with the analytical and problem-solving skills needed to excel in multidisciplinary research areas, including graph theory and mathematical modeling.

Work Experience 💼

Muhammad Waheed Rasheed is an accomplished researcher with expertise in cryptography, fuzzy graph theory, and QSPR analysis. His work focuses on molecular descriptors, graph labeling, energy graphs, and metric dimensions, addressing challenges in networking and drug efficacy analysis. With five impactful publications in journals like Frontiers in Chemistry and Frontiers in Physics, he demonstrates excellence in both independent and collaborative research. His ability to tackle complex problems and deliver innovative solutions highlights his readiness for advanced research roles in academia and industry.

Research Interests

Mr. Rasheed’s research interests include cryptography, group theory, fuzzy graph theory, and QSPR analysis. He focuses on molecular descriptors, graph labeling, energy graphs, and metric dimensions, aiming to address critical issues in mathematics and its applications in healthcare and networking.

Research Skills

Muhammad Waheed Rasheed’s research interests lie at the intersection of advanced mathematics and real-world applications. He specializes in cryptography, fuzzy graph theory, and group theory, with a strong emphasis on molecular descriptors, graph labeling, energy graphs, and metric dimensions. His work extends to QSPR (Quantitative Structure-Property Relationship) analysis, where he investigates the properties of chemical compounds, such as alkaloids and medications, to improve therapeutic efficacy and understand their thermodynamic behavior. He is particularly passionate about exploring the role of graph theory in networking and healthcare, focusing on innovative solutions to complex problems. Through his interdisciplinary research, Mr. Rasheed aims to contribute significantly to global challenges, combining theoretical insights with practical applications in chemistry, physics, and beyond.

📚 Publications

Neighborhood Face Index: A New QSPR Approach for Predicting Physical Properties of Polycyclic Chemical Compounds

  • Authors: A. Raza, M.W. Rasheed, A. Mahboob, M. Ismaeel
  • Journal: International Journal of Quantum Chemistry
  • Year: 2024
  • Volume: 124(24), e27524
  • Citations: 0

Block Cipher Construction Using Minimum Spanning Tree from Graph Theory and Its Application with Image Encryption

  • Authors: M.W. Rasheed, A. Mahboob, M. Bilal, K. Shahzadi
  • Journal: Science Progress
  • Year: 2024
  • Volume: 107(4)
  • Citations: 0

Entropy Measures of Dendrimers Using Degree-Based Indices

  • Authors: A. Ovais, F. Yasmeen, M. Irfan, M.W. Rasheed, S. Kousar
  • Journal: South African Journal of Chemical Engineering
  • Year: 2024
  • Volume: 50, pp. 168–181
  • Citations: 0

Computing Connection-Based Topological Indices of Carbon Nanotubes

  • Authors: E.U. Haq, A. Mahboob, M.W. Rasheed, S. Sattar, M. Waqas
  • Journal: South African Journal of Chemical Engineering
  • Year: 2024
  • Volume: 48, pp. 121–129
  • Citations: 0

QSPR Analysis of Physicochemical Properties and Anti-Hepatitis Prescription Drugs Using a Linear Regression Model

  • Authors: A. Mahboob, M.W. Rasheed, A.M. Dhiaa, I. Hanif, L. Amin
  • Journal: Heliyon
  • Year: 2024
  • Volume: 10(4), e25908
  • Citations: 5

Approximating Properties of Chemical Solvents by Two-Dimensional Molecular Descriptors

  • Authors: A. Mahboob, M.W. Waheed Rasheed, I. Hanif, I. Siddique
  • Journal: International Journal of Quantum Chemistry
  • Year: 2024
  • Volume: 124(1), e27305
  • Citations: 3

Role of Molecular Descriptors in QSPR Analysis of Kidney Cancer Therapeutics

  • Authors: A. Mahboob, M.W. Rasheed, I. Hanif, L. Amin, A. Alameri
  • Journal: International Journal of Quantum Chemistry
  • Year: 2024
  • Volume: 124(1), e27241
  • Citations: 9

Face Irregular Evaluations of Family of Grids

  • Authors: J.H.H. Bayati, A. Ovais, A. Mahboob, M.W. Rasheed
  • Journal: AKCE International Journal of Graphs and Combinatorics
  • Year: 2024 (In Press)
  • Citations: 0

Enhancing Breast Cancer Treatment Selection Through 2TLIVq-ROFS-Based Multi-Attribute Group Decision Making

  • Authors: M.W. Rasheed, A. Mahboob, A.N. Mustafa, Z.A.A. Ali, Z.H. Feza
  • Journal: Frontiers in Artificial Intelligence
  • Year: 2024
  • Volume: 7, 1402719
  • Citations: 0

QSAR Modeling with Novel Degree-Based Indices and Thermodynamics Properties of Eye Infection Therapeutics

  • Authors: M.W. Rasheed, A. Mahboob, I. Hanif
  • Journal: Frontiers in Chemistry
  • Year: 2024
  • Volume: 12, 1383206
  • Citations: 0

Conclusion 

Muhammad Waheed Rasheed is a talented researcher whose academic achievements and innovative research demonstrate a promising career in mathematics and its applications. His dedication, interdisciplinary focus, and impactful publications make him a strong candidate for prestigious accolades and research opportunities.

 

Ling Mei | Cognitive Science | Best Researcher Award

Dr. Ling Mei | Cognitive Science | Best Researcher Award

Doctorate at Wuhan University of Science and Technology, China

Dr. Ling Mei is an accomplished researcher in artificial intelligence and cognitive science, with a robust academic and professional background. He holds a Ph.D. in Engineering from Sun Yat-sen University, one of China’s top universities, and completed a prestigious visiting scholar program at the University of British Columbia (UBC). Currently serving as a tenured faculty and master’s supervisor, Dr. Mei has published 16 papers, including 7 in SCI-indexed journals, contributed to nine books, and has three national invention patents granted. Recognized as a Provincial Research Talent of China in 2024, he work integrates advanced computational models with societal needs, such as urban planning and public safety. Dr. Mei has collaborated internationally with top-tier institutions like UBC and Carnegie Mellon University, cementing he reputation as a leader in he field.

Profile

Google Scholar

Orcid

Education 🎓

Dr. Mei earned he Ph.D. in Engineering from Sun Yat-sen University in 2021, a prestigious institution ranked among China’s top 10 universities. He academic journey also includes a year-long visiting scholar program at the Department of Computer Science, UBC, as part of the National Outstanding Young Researchers Program. This international exposure provided he with cutting-edge knowledge and interdisciplinary skills, enabling he to excel in artificial intelligence and cognitive science.

Work Experience 💼

Currently, Dr. Mei is a tenured faculty member and master’s supervisor at a leading Chinese university. He experience includes overseeing multiple research projects, consulting on seven industry-sponsored projects, and serving as a reviewer for the IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY. He has also been instrumental in fostering international collaborations with institutions like UBC and CMU, contributing to impactful research publications and patents.

Awards and Honors

In 2024, Dr. Mei was recognized as a Provincial Research Talent of China, highlighting he exceptional contributions to science and technology. He has also earned accolades through he impactful patents and high-quality publications.

Research Interests

Dr. Mei’s research focuses on artificial intelligence, pedestrian trajectory prediction, and public safety strategies. He innovations include the LSN-GTDA framework, which integrates behavioral and stochastic factors for better uncertainty management. He interdisciplinary approach bridges cognitive science, computational models, and societal applications, ensuring he work’s relevance and impact.

Research Skills

Dr. Mei possesses advanced skills in AI modeling, thermal diffusion processes, and signal and system theory. He expertise includes patent development, SCI journal publications, and interdisciplinary collaborations. He is adept at integrating computational techniques with practical applications, as seen in he trajectory prediction research.

📚 Publications

Crowd Density Estimation via Global Crowd Collectiveness Metric

  • Journal: Drones
  • Date: 2024-10-28
  • DOI: 10.3390/drones8110616
  • Contributors: Ling Mei, Mingyu Yu, Lvxiang Jia, Mingyu Fu

More Quickly-RRT: Improved Quick Rapidly-Exploring Random Tree Star Algorithm Based on Optimized Sampling Point with Better Initial Solution and Convergence Rate*

  • Journal: Engineering Applications of Artificial Intelligence
  • Date: 2024-07
  • DOI: 10.1016/j.engappai.2024.108246
  • Contributors: Xining Cui, Caiqi Wang, Yi Xiong, Ling Mei, Shiqian Wu

Learning Domain-Adaptive Landmark Detection-Based Self-Supervised Video Synchronization for Remote Sensing Panorama

  • Journal: Remote Sensing
  • Date: 2023-02-09
  • DOI: 10.3390/rs15040953
  • Contributors: Ling Mei, Yizhuo He, Farnoosh Fishani, Yaowen Yu, Lijun Zhang, Helge Rhodin

Illumination-Invariance Optical Flow Estimation Using Weighted Regularization Transform

  • Journal: IEEE Transactions on Circuits and Systems for Video Technology
  • Date: 2020-02
  • DOI: 10.1109/TCSVT.2019.2890861
  • Contributors: Ling Mei, Jianhuang Lai, Xiaohua Xie, Junyong Zhu, Jun Chen

Feature Visualization Based Stacked Convolutional Neural Network for Human Body Detection in a Depth Image

  • Type: Book Chapter
  • Year: 2018
  • DOI: 10.1007/978-3-030-03335-4_8
  • Contributors: Xiao Liu, Ling Mei, Dakun Yang, Jianhuang Lai, Xiaohua Xie

Conclusion 

Dr. Ling Mei is a strong contender for the Best Researcher Award due to he robust academic background, impactful research, and significant contributions to AI and cognitive science. To further enhance he candidacy, increasing citation influence and emphasizing community impact would solidify he position as an exemplary researcher deserving of recognition. 🌟