Md Abubokor Siam
Biographic Data
| ID | 6953623 |
|---|---|
| NAME | Md Abubokor Siam |
| GIVEN NAMES | Md Abubokor |
| FAMILY NAME | Siam |
| SIGNATURE | SIAM M A |
| AFFILIATIONS | Monterey Bay Aquarium Foundation |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Assessing Urban-Rural Income Disparities in the USA
Income inequality in the US is a major quagmire that requires a multifaceted understanding of the difference between urban and rural regions. This study seeks to utilize predictive analytics and machine learning methodologies to help analyze these disparities in a thorough manner. The principal objective of this research was to design machine learning models that classify and analyze the urban-rural gap in income by employing a blend of demograph…
AI-Driven Sentiment Analysis for Bitcoin Market Trends
Cryptocurrency markets in the USA, especially that of Bitcoin, are plagued by extreme volatility fueled by a dynamic intersection of macroeconomic forces, speculator behavior, and sentiment of investors. Conventional financial models cannot keep pace with the high-frequency price changes typical of digital assets, prompting the need for novel methodologies that can better account for unstructured data like social media sentiment, news reports, an…
No prominent works on this page.
Assessing Urban-Rural Income Disparities in the USA
Income inequality in the US is a major quagmire that requires a multifaceted understanding of the difference between urban and rural regions. This study seeks to utilize predictive analytics and machine learning methodologies to help analyze these disparities in a thorough manner. The principal objective of this research was to design machine learning models that classify and analyze the urban-rural gap in income by employing a blend of demograph…
AI-Driven Sentiment Analysis for Bitcoin Market Trends
Cryptocurrency markets in the USA, especially that of Bitcoin, are plagued by extreme volatility fueled by a dynamic intersection of macroeconomic forces, speculator behavior, and sentiment of investors. Conventional financial models cannot keep pace with the high-frequency price changes typical of digital assets, prompting the need for novel methodologies that can better account for unstructured data like social media sentiment, news reports, an…
Computer Science (2 works) · Econometrics (2 works) · Economics (2 works) · Analytics (1 work) · Artificial Intelligence (1 work) · Blockchain Technology Applications and Security (1 work) · Computer security (1 work) · Cryptocurrency (1 work) · Data science (1 work) · Financial economics (1 work)