Muhammad Zubair | Computer Science and Artificial Intelligence | Best Researcher Award

Mr. Muhammad Zubair | Computer Science and Artificial Intelligence | Best Researcher Award

Mr. Muhammad Zubair | Computer Science and Artificial Intelligence | Masterโ€™s Student at Nanjing University of Science and Technology | China

Mr. Muhammad Zubair is a committed academic and emerging researcher recognized for his structured approach to hypothesis-driven research and scholarly development. He has completed advanced academic training culminating in a doctoral-level qualification from a recognized university, providing him with a strong foundation in research methodology, critical analysis, and ethical scientific practice. His education reflects rigorous exposure to interdisciplinary learning, advanced analytical tools, and scholarly writing aligned with international academic standards.He demonstrates familiarity with global indexing platforms and maintains a verifiable research profile, having authored 0 documents with 1 citation and a 0 h-index, indicating an early but authenticated research presence with clear potential for expansion.

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Featured Publications

Abnormal Alliance Detection Method Based on a Dynamic Community Identification and Tracking Method for Time-Varying Bipartite Networks
โ€“ AI Switzerland, Open Access

Flexible Visually Secure Image Encryption with Meta-Learning Compression and Chaotic Systems
โ€“ Neural Networks

A High-Acceptance-Rate VxWorks Fuzzing Framework Based on Protocol Feature Fusion and Memory Extraction
โ€“ Future Internet, Open Access

Visually Secure Image Encryption: Exploring Deep Learning for Enhanced Robustness and Flexibility
โ€“ Expert Systems with Applications

Textual Data De-Privatization Scheme Based on Generative Adversarial Networks
โ€“ Conference Paper

Faroque Ahmed | Quantitative Hypotheses | Best Researcher Award

Faroque Ahmed | Quantitative Hypotheses | Best Researcher Award

Mr Faroque Ahmed, Ural Federal University, Russia, Russia

Faroque Ahmed is a PhD researcher at Ural Federal University, Russia ๐Ÿ‡ท๐Ÿ‡บ, specializing in development studies and financial economics ๐Ÿ“Š. He holds an M.Sc. and B.Sc. in Statistics from Islamic University, Kushtia-Jhinaidah, where he achieved top positions in his class ๐Ÿฅ‡. With research interests in quantile-based methods, VARs, data mining, and machine learning ๐Ÿค–, he has served as a Senior Research Associate at the Bangladesh Institute of Governance and Management (BIGM) and as a Research Assistant at the Islamic University, working on credit card fraud detection. Faroque also boasts excellent academic achievements and IELTS proficiency ๐Ÿ…๐Ÿ“š.

Publication profile

Scopus

Education

๐Ÿ“š With a strong academic background, I hold a Master’s in Statistics from Islamic University, Kushtia-Jhinaidah, completed in 2015 with an ‘A’ grade and a CGPA of 3.91, securing first-class first position ๐Ÿฅ‡. My Bachelor’s in Statistics from the same university, completed in 2014, earned me an ‘A’ grade and a CGPA of 3.84, ranking second in first class ๐Ÿฅˆ. Prior to this, I excelled in Science, achieving a perfect GPA of 5.00 in both my Higher Secondary (2009) and Secondary (2006) School Certificates at New Govt. Degree College and Masjid Mission Academy, respectively ๐ŸŒŸ.

Experience

Since 2022, the user has been a PhD Researcher at the Laboratory of International & Regional Economics (LIRE) at the Graduate School of Economics and Management (GSEM), Ural Federal University, Yekaterinburg, Russia ๐Ÿ“š๐ŸŒ. Concurrently, they have served as a Senior Research Associate at the Bangladesh Institute of Governance and Management (BIGM), affiliated with the University of Dhaka, since 2019 ๐Ÿข๐Ÿ‡ง๐Ÿ‡ฉ. Previously, from 2016 to 2019, they worked as a Research Assistant at the Quantitative Financial Economic Development (QFED) Lab in the Dept. of Statistics at Islamic University, Kushtia, Bangladesh, focusing on credit card fraud detection using machine-learning algorithms under the supervision of Md. Altaf Hossain ๐Ÿ’ณ๐Ÿค–.

Research Interest

I am passionate about the fields of development studies and financial economics, focusing on advanced methodologies and data analysis. My expertise includes quantile-based methods, various types of VARs, and data mining techniques. I am proficient in leveraging machine learning and big data analysis for robust econometric modeling. Through these skills, I aim to contribute to the understanding and development of economic policies and practices. ๐Ÿ“Š๐Ÿ’ก๐Ÿ”๐Ÿ“‰๐Ÿ’ป๐Ÿ”Ž

Awards

In 2017-18, I was awarded the UGC research grant for my masterโ€™s project on the socio-economic effects of remittance on Bangladeshi migrant households. Under the supervision of Md. Altaf Hossain, an Associate Professor at Islamic University, Kushtia, Bangladesh, I conducted extensive research in this area. Additionally, in 2017, I completed Big Data Analytics Training through the LICT project of the ICT Ministry, People’s Republic of Bangladesh. ๐Ÿ“š๐Ÿ”๐Ÿ’ผ The grant and training significantly enhanced my research capabilities and data analysis skills, contributing to my academic and professional growth. ๐Ÿ“ˆ๐ŸŒ

Research focus

Faheem Ahmed’s research primarily focuses on the intersection of economics, environmental studies, and technological applications. His work includes examining the impact of geopolitical risks on global finance, analyzing the economic growth-environment nexus, and exploring the implications of AI technology on industrial outputs and energy consumption. Additionally, Ahmed delves into health outcomes influenced by governance and education, social distancing behaviors during Covid-19, and predictive modeling for air quality and credit card fraud detection. His interdisciplinary approach combines machine learning with economic and environmental analysis, reflecting a broad interest in sustainable development and risk management. ๐ŸŒ๐Ÿ“Š๐Ÿ’ก๐ŸŒฑ๐Ÿ“‰๐Ÿ”.

Publication top notes

Robot race in geopolitically risky environment: Exploring the Nexus between AI-powered tech industrial outputs and energy consumption in Singapore

Semi-Supervised Machine Learning Method for Predicting Observed Individual Risk Preference Using Gallup Data

Assessing the impact of Russianโ€“Ukrainian geopolitical risks on global green finance: a quantile dependency analysis

An inquiry into the achievements in health outcomes of Bangladesh: role of health expenditure, income, governance and female education

Integration of theory of planned behavior into actual social distancing behavior amid Covid-19

Economic growth and environmental pollution nexus in Ba

An analysis of energy, environment and economic growth (EEE) nexus: a 2SLS approach

Creative social media use for Covid-19 prevention in Bangladesh: a structural equation modeling approach

A comparative study of credit card fraud detection using the combinati

Predicting air quality of Dhaka and Sylhet divisions in Bangladesh: a time series modeling approach