Research Papers (Published):
Mahmud , A. and Rayhan, M.I. 2025. Weather Forecasting Using Recurrent Neural Networks and Vector Autoregressive Model: A Comprehensive Analysis of Time Series Data from Rohingya Camps and Control Areas: Weather Forecasting Using Recurrent Neural Networks and Vector Autoregressive Model. Dhaka University Journal of Science. 73, 2 (Jul. 2025), 93–99. DOI: https://doi.org/10.3329/dujs.v73i2.82766.
Research Papers (Under Review/Working):
Factors Associated with Inadequate Supervision of Under Five Children in Bangladesh. (under review)
A Deep Learning Approach to Forecasting Mobile Banking Subscribers and Transactions: Evidence from Bangladesh (2016–2024) (under review)
Projects:
"Skill for Growth: Human Capital Deficits, Labor Market Frictions," with the professors of the University of Minnesota, the University of California, San Diego, and the economist of the Federal Reserve Bank of Richmond.
"Facilitate Adoption of Modern Machinery" with Swisscontact.
"Shariah Objectives of Islamic Banking in Bangladesh" with a PhD student.
Packages:
"sendemail," a Stata package: This package builds upon and integrates features from the existing pr0078 and tknz packages. It introduces a user-friendly dialog box that allows users to input the essential details needed to send an email. The package relies on PowerShell to execute the email-sending process, so it may not function correctly on systems where PowerShell is unavailable or disabled. You can explore the original sendemails package here.
To install this package, use "net install sendemail, from("https://raw.githubusercontent.com/armanmahmud1/sendemail/main/") replace"
"basicstat," a Stata package: This command produces two Excel files, named "basicstat_string_output.xlsx" and "basicstat_numeric_output.xlsx", that summarize key statistics from a dataset. For string variables, it generates frequency tables, with each variable placed on its own sheet within the string output file. For numeric variables, the command first checks whether the number of observations is greater than zero. If so, it compiles a comprehensive set of statistics for each variable, including the variable name, number of observations, mean, standard deviation (SD), skewness, kurtosis, minimum and maximum values, and percentiles at the 25th (P25), 50th (P50), and 75th (P75) levels. This structured output provides a quick and organized overview of both categorical and numerical data characteristics.
To install this package, use "net install basicstat, from("https://raw.githubusercontent.com/armanmahmud1/basicstat/main/") replace"
"autochart" a R package: This R package is a new tool designed to simplify data visualization. Its core function, autochart(), takes a data file path and two variable names as input. It automatically handles data loading for both CSV and Excel files. To use the package, you will first need to install the ggplot2 and readxl packages. The package then intelligently analyzes the data types of the two specified variables and selects the most appropriate plot for visualization. If both variables are numeric, it generates a scatter plot. If one is numeric and the other is a string, it creates a bar plot. For two string variables, it produces a stacked bar plot. This design allows users to quickly generate relevant charts without needing to manually specify plot types or write complex plotting code.
To install this package, use "devtools::install_github("armanmahmud1/autochart")"