Faroque Ahmed | Economics, Econometrics and Finance | Best Researcher Award

Faroque Ahmed | Economics, Econometrics and Finance | Best Researcher Award

Mr Faroque Ahmed, Ural Federal University, Russia, Russia

πŸŽ“ Faroque Ahmed holds a Master’s in Statistics from Islamic University, Kushtia-Jhinaidah (2015), securing first class first position with a CGPA of 3.91. He also earned a Bachelor’s in Statistics from the same institution (2014), achieving first class second position with a CGPA of 3.84. Faroque completed his secondary education with top grades. πŸ“Š Currently, he is a PhD researcher at Ural Federal University, Russia, and a Senior Research Associate at Bangladesh Institute of Governance and Management. He has experience as a Research Assistant in credit card fraud detection using machine-learning. His research interests include development studies, financial economics, data mining, and econometric modeling. πŸŒπŸ“ˆ

Publication profile

Scopus

Education

πŸŽ“ With a Master of Science (M.Sc.) in Statistics from Islamic University, Kushtia-Jhinaidah, I achieved a Grade β€˜A’ and a CGPA of 3.91, graduating first in my class in 2017. My Bachelor of Science (B.Sc.) in Statistics from the same institution was also distinguished, with a Grade β€˜A’ and a CGPA of 3.84, securing second place in 2016. πŸ“Š My academic journey began at Masjid Mission Academy in Rajshahi, where I excelled in my Secondary School Certificate (S.S.C.) with a Golden β€˜A+’. πŸ… Additionally, I completed my Higher Secondary School Certificate (H.S.C.) at New Govt. Degree College, Rajshahi, earning a perfect GPA of 5.00. 🌐 I have an IELTS score of 6.0 across all sections, proving my proficiency in English.

Experience

Currently, 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, since 2022. Serving as a Senior Research Associate at the Bangladesh Institute of Governance and Management (BIGM), affiliated with the University of Dhaka, since 2019. Previously worked as a Research Assistant at the Quantitative Financial Economic Development (QFED) Lab, Dept. of Statistics, Islamic University, Kushtia, Bangladesh, from 2016 to 2019, focusing on credit card fraud detection using machine-learning algorithms under the supervision of Associate Professor Md. Altaf Hossain. πŸ“ŠπŸ§ πŸŒ

Awards

In 2017-18, a UGC research grant was awarded for a master’s student project focused on the socio-economic effects of remittance on Bangladeshi migrant households. The project was supervised by Md. Altaf Hossain, an Associate Professor at Islamic University, Kushtia, Bangladesh. Additionally, in 2017, the student participated in Big Data Analytics Training under the LICT project of the ICT Ministry, People’s Republic of Bangladesh, enhancing their skills in data analysis and technology applications. This combination of research and training provided a strong foundation for understanding the economic impacts of remittance and advanced data analysis techniques. πŸ“šπŸ’»πŸŒ

Research focus

Dr. F. Ahmed’s research spans several critical areas within the realm of socio-economic and environmental studies. His work focuses on the intersection of AI-powered technology, energy consumption, and geopolitical risks, particularly in regions like Singapore. Additionally, Dr. Ahmed explores global green finance impacted by geopolitical tensions, and health outcomes influenced by socio-economic factors in Bangladesh. He delves into the dynamics of economic growth and environmental pollution, while also examining social behaviors during the COVID-19 pandemic. His contributions extend to machine learning applications in predicting individual risk preferences and detecting credit card fraud. πŸ“ŠπŸŒπŸ”¬πŸ’‘πŸŒ±

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 Bangladesh: revisiting the environmental Kuznets curve hypothesis

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 combination of machine learning techniques with data imbalance solution

Giorgio Consigli | Financial optimization Award | Best Researcher Award

Assoc Prof Dr. Giorgio Consigli | Financial optimization Award | Best Researcher Award

Assoc Prof Dr. Giorgio Consigli, Khalifa University of Science and Technology, United Arab Emirates

Assoc. Prof. Dr. Giorgio Consigli is a distinguished figure in mathematical finance and optimization. Currently an Associate Professor at Khalifa University of Science & Technology, his expertise spans various esteemed organizations including the Bachelier Finance Society and the Euro Working Groups on Commodities and Stochastic Optimization. With a robust academic background from the University of Cambridge and extensive professional experience, he’s contributed significantly to the field. As an elected member of prestigious committees like COSP, his influence extends globally, shaping research and education. πŸŽ“πŸ“Š

Publication Profile

Orcid

Google Scholar

πŸŽ“ Academic and Professional Journey

Dr. Consigli serves as an Associate Professor at Khalifa University of Science & Technology. Prior to this, he held a similar position at the University of Bergamo. His professional journey includes significant roles in finance and academia, including a Postdoctoral Research Fellowship at the University of Cambridge.

πŸ… Professional Appointments and Achievements

Dr. Consigli’s contributions extend beyond academia; he has been involved in various institutional and academic appointments. Notably, he’s served as an elected member of the International Committee on Stochastic Programming (COSP) and acted as an expert reviewer for grant applications, showcasing his expertise in the field. Additionally, his role as an external examiner and opponent in PhD defenses reflects his commitment to academic excellence and advancement.

 

Research Focus

Assoc. Prof. Dr. Giorgio Consigli’s research spans dynamic asset-liability management, stochastic programming, and financial optimization. With a keen interest in risk management and portfolio selection, he explores innovative methodologies to tackle financial instability and uncertainty. His contributions include pioneering work on multistage stochastic programs, tail estimation in portfolio selection, and scenario tree generation for dynamic decision-making. Consigli’s research also delves into retirement planning, individual asset-liability management, and the predictive ability of financial models. With a blend of theoretical rigor and practical relevance, his research endeavors aim to enhance decision-making processes in finance, providing valuable insights for practitioners and academics alike. πŸ“ˆ

 

Publication Top Notes

πŸ“š “Scenarios for multistage stochastic programs” by J DupačovΓ‘, G Consigli, SW Wallace, cited by 680, published in 2000. πŸ“ˆ

πŸ“š “Dynamic stochastic programming for asset-liability management” by G Consigli, MAH Dempster, cited by 360, published in 1998. πŸ“Š

πŸ“š “Tail estimation and mean–VaR portfolio selection in markets subject to financial instability” by G Consigli, cited by 125, published in 2002. πŸ“‰

πŸ“š “Stochastic optimization methods in finance and energy: New financial products and energy market strategies” by M Bertocchi, G Consigli, MAH Dempster, cited by 42, published in 2011. 🌐

πŸ“š “Retirement planning in individual asset–liability management” by G Consigli, G Iaquinta, V Moriggia, M Di Tria, D Musitelli, cited by 37, published in 2012. πŸ“Š

The predictive ability of the bond-stock earnings yield differential model

Asset-liability management for individual investors

Path-dependent scenario trees for multistage stochastic programmes in finance

Heavy-tailed distributional model for operational losses

Optimal financial decision making under uncertainty