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

 

Raksmey Sann | Quantitative Hypotheses | Best Researcher Award

Raksmey Sann | Quantitative Hypotheses | Best Researcher Award

Prof Raksmey Sann, Khon Kaen university, Thailand

Dr. Raksmey Sann is an accomplished academic specializing in International Tourism, Hospitality, and Events Management. He earned his Ph.D. from the National Pingtung University of Science and Technology, Taiwan, with First-Rank Honor and a dissertation on cross-cultural online complaining behavior in the hospitality industry πŸ“š. Dr. Sann is currently a faculty member at Khon Kaen University, Thailand, where he teaches research methodology, tourism management, and sustainable event management 🌏. His research focuses on service marketing, data mining, and consumer behavior, with numerous publications in top-tier journals. He has received multiple scholarships and research grants for his outstanding work in the field πŸŽ“.

Publication profile

google scholar

Education

I hold a distinguished academic background in International Tourism, Hospitality, and Events Management, having earned a degree with First-Rank Honor from the National Pingtung University of Science and Technology, Taiwan, in September 2020 πŸŽ“. His dissertation, β€œInvestigating Cross-Cultural Online Complaining Behavior in the Hospitality Industry,” was guided by a notable committee, including Professor Li, Yi-Ming (chair). I was awarded the Excellent Foreign Student Scholarship πŸ†. His MSc, also from the same university, focused on β€œCross-Cultural Tourist Online Hotel Booking Behaviour” and received Second-Rank Honor. I previously graduated with a BA from Mahasarakham University, Thailand, with First-Class Honor, supported by the Princess Maha Chakri Sirindhorn Scholarship πŸ‘‘. My academic journey began with a BS Ed in TEFL from the Royal University of Phnom Penh, Cambodia πŸ“š.

Honors and Awards

During my academic journey, I was honored to receive multiple prestigious scholarships. From 2018 to 2020, I was awarded the Excellent Foreign Student Scholarship, a full government scholarship by the Ministry of Education, Taiwan πŸ‡ΉπŸ‡Ό. Similarly, from 2016 to 2018, I received the same distinguished scholarship πŸ‡ΉπŸ‡Ό. Earlier, I was privileged to earn the Her Royal Highness Princess Maha Chakri Sirindhorn Scholarship from 2011 to 2015, a full government scholarship by the Ministry of Education, Thailand πŸ‡ΉπŸ‡­. My academic excellence was also recognized in Cambodia πŸ‡°πŸ‡­, where I received the National Excellent Student Scholarship from 2009 to 2011.

 

Research Experience

In 2020, at the National Pingtung University of Science and Technology, Taiwan, I completed my dissertation titled “Investigating Cross-Cultural Online Complaining Behavior in the Hospitality Industry: An Application of Content Analysis and Data Mining Approach,” under the guidance of Professor Pei-Chun Lai. This research delved into service marketing, service quality, and online consumer behavior, employing natural language processing, data mining, and big data analytics to uncover insights πŸ“Š. Previously, in 2018, I conducted exploratory research on cross-cultural tourist online hotel booking behavior, focusing on the impact of electronic word-of-mouth (eWOM). This thesis, also advised by Professor Lai, encompassed e-commerce, cross-cultural studies, and eWOM, using multivariate analysis, qualitative methods, and content analysis to draw its conclusions 🌐.

 

Teaching Experience

Since December 2021, I have been a faculty member at Khon Kaen University’s Faculty of Business Administration and Accountancy in the Department of Tourism Innovation Management. I teach courses such as Research Methodology, Research Project, English for Tourism Business, and Sustainable Event Management, engaging with 120 undergraduate students each semester. For graduate students (MSc. & PhD), I cover Qualitative Research Methodology, Multivariate Analysis, and other advanced topics with over 20 students per semester. Previously, I taught various hospitality and tourism management courses at Khon Kaen University International College (Dec 2020 – Nov 2021). My teaching career began as a teaching assistant at National Pingtung University of Science and Technology (2016-2020) and teaching English to orphaned children in Phnom Penh (2009-2011). πŸ“šπŸŒπŸŽ“

Recognition πŸ…

His accolades include the Best Outstanding PhD Research Performance (2021) from NPUST, Taiwan, and the Distinguished Master Thesis Award (2018) from the TSC Thesis Symposium, Taiwan. He has also won several presentation and competition awards throughout his academic career. πŸ₯‡

Research focus

R. Sann’s research primarily focuses on the hospitality industry, particularly on online customer behavior and sentiment analysis using advanced data analytics techniques. Key areas of interest include understanding online complaining behavior, the impact of cultural backgrounds on service perceptions, and the application of big data analytics to online reviews. Sann’s work also explores the effects of service quality, guest experiences, and health-related concerns on consumer behavior, integrating theories like the theory of planned behavior. This multidisciplinary approach leverages tools like NLP and machine learning to derive insights from large datasets, aiming to enhance service quality and customer satisfaction in hospitality. πŸ¨πŸ“ŠπŸ§ πŸ’¬

Publication top notes

Understanding homophily of service failure within the hotel guest cycle: Applying NLP-aspect-based sentiment analysis to the hospitality industry

Predicting Online Complaining Behavior in the Hospitality Industry: Application of Big Data Analytics to Online Reviews

Online complaining behavior: Does cultural background and hotel class matter?

Modelling theory of planned behavior on health concern and health knowledge towards purchase intention on organic products

Review papers on eWOM: prospects for hospitality industry

Analysis of online customer complaint behavior in Vietnam’s hotel industry

Crisis Adaptation in a Thai Community-Based Tourism Setting during the COVID-19 Pandemic: A Qualitative Phenomenological Approach

An extension of the theory of planned behaviour in Thailand cycling tourism: The mediating role of attractiveness of sustainable alternatives

Multidimensional scale development and validation: university service quality (UNIQUAL)

Topic modeling of the quality of guest’s experience using latent Dirichlet allocation: Western versus eastern perspectives