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 π·πΊ, specializing in development studies and financial economics π. He holds an M.Sc. and B.Sc. in Statistics from Islamic University, Kushtia-Jhinaidah, where he achieved top positions in his class π₯. With research interests in quantile-based methods, VARs, data mining, and machine learning π€, 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 π π.
Publication profile
Education
π 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 π₯. 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 π₯. 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 π.
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 ππ. 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 π’π§π©. 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 π³π€.
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. ππ‘πππ»π
Awards
In 2017-18, I was awarded the UGC research grant for my masterβs 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. πππΌ The grant and training significantly enhanced my research capabilities and data analysis skills, contributing to my academic and professional growth. ππ
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. πππ‘π±ππ.
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 RussianβUkrainian 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