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 πŸ‡·πŸ‡Ί, specializing in development studies and financial economics πŸ“Š. He holds an M.Sc. and B.Sc. in Statistics from Islamic University, Kushtia-Jhinaidah, where he achieved top positions in his class πŸ₯‡. With research interests in quantile-based methods, VARs, data mining, and machine learning πŸ€–, 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 πŸ…πŸ“š.

Publication profile

Scopus

Education

πŸ“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 πŸ₯‡. 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 πŸ₯ˆ. 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 🌟.

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 πŸ“šπŸŒ. 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 πŸ’πŸ‡§πŸ‡©. 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 πŸ’³πŸ€–.

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. πŸ“ŠπŸ’‘πŸ”πŸ“‰πŸ’»πŸ”Ž

Awards

In 2017-18, I was awarded the UGC research grant for my master’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. πŸ“šπŸ”πŸ’Ό The grant and training significantly enhanced my research capabilities and data analysis skills, contributing to my academic and professional growth. πŸ“ˆπŸŒ

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. πŸŒπŸ“ŠπŸ’‘πŸŒ±πŸ“‰πŸ”.

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 Russian–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

 

Quantitative Hypothesis Award

Quantitative Hypothesis Award

Introduction:

Welcome to the Quantitative Hypothesis Award, honoring individuals who excel in proposing and testing hypotheses using quantitative methods. This prestigious award celebrates the rigor, innovation, and impact of quantitative research in advancing knowledge across various domains.

Award Overview:

The Quantitative Hypothesis Award recognizes individuals who demonstrate excellence in formulating, testing, and validating hypotheses using quantitative techniques, contributing to the advancement of scientific inquiry and evidence-based decision-making.

Eligibility:

  • Open to researchers, scientists, and scholars utilizing quantitative methods in their work
  • No age limits apply
  • Qualification: Demonstrated proficiency in quantitative analysis and hypothesis testing
  • Publications: Evidence of quantitative research findings published in peer-reviewed journals or presented at academic conferences
  • Recurrements: Continued engagement in quantitative research and hypothesis-driven inquiry

Evaluation Criteria:

Candidates will be evaluated based on the following criteria:

  1. Clarity and precision in formulating quantitative hypotheses
  2. Soundness and robustness of quantitative methodology used for hypothesis testing
  3. Rigor and validity of data analysis and interpretation
  4. Impact and significance of research findings on advancing knowledge or informing decision-making

Submission Guidelines:

  • Submit a detailed biography highlighting quantitative research expertise and achievements
  • Include an abstract summarizing the quantitative hypothesis, methodology, and key findings
  • Provide supporting files such as research papers, data sets, statistical analyses, and visualizations

Recognition:

Recipients of the Quantitative Hypothesis Award will receive:

  • A prestigious award certificate
  • Recognition at a prominent scientific conference or symposium
  • Opportunities for collaboration and networking with quantitative researchers and practitioners

Community Impact:

Winners of the award are expected to inspire and promote excellence in quantitative research, fostering a culture of data-driven inquiry and evidence-based decision-making within their respective communities and beyond.

Biography:

A comprehensive biography outlining the candidate's quantitative research background, expertise, and contributions to the field is required.

Abstract and Supporting Files:

Candidates must submit an abstract summarizing their quantitative hypothesis, methodology, and key findings, along with supporting files such as research papers, data sets, statistical analyses, and visualizations to demonstrate the rigor and impact of their work.