Solving Data-Centric Challenges,
One Model at a Time!

This project analyzed *1 (Setare 1), a payment application linked to Hamrah-e-Aval, Iran's main mobile provider, using questionnaire data from both users and the general population. The analysis, conducted in Python, included diverse visualizations such as bar plots, violin plots, heat maps, and interactive maps using the Plotly library. The visualizations were categorized into static and dynamic, with interactive treemaps allowing users to delve deeper into categories based on population size. This comprehensive analysis provided insights into user preferences and behaviors, aiding in identifying areas for improvement. While the data is confidential, the visual assets and plots can be discussed privately.

In this project I have participated as the developer and implemented the designed task by the Ms. Sharifi in PsychoPy. This task consisted of 36 routines and 3 loops. Each section of this task comprises two subsections: images and statements. Additionally, this task includes two rest periods, one between the image and statement subsections in the training section, and the other between the practice and main testing sections. In each section of this task, instructions are displayed for 2 seconds, and images and statements are displayed for 15 seconds each. During the interpretation stage, the participant has 150 seconds to prove their interpretations.

In this project, I served as the developer, implementing Ms. Sharifi's designed task in PsychoPy. The test comprises 10 routines and 2 loops, divided into two sections: training and main test. During the training phase, participants view 5 word pairs on a white background and identify the valence of the target word using the + (positive) and - (negative) keys. Response time is recorded as the main parameter. The screen displays a black plus sign for 1 second before presenting the words, divided horizontally with one part showing white words on a black background and the other showing black words on a white background.

This Project houses the code and data for a research paper conducted by Ramin Ferdos and Ali Hossein Noorafrooz. In this study, we leverage data from Altmetric to analyze the impact and visibility of research output from Iranian universities on the global stage. Our analysis is based on a variety of metrics, including mentions in news articles, patent creation, policy influence, and more. We have followed the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology to guide our research.

In this project, which is a multiple-stage project, I developed a software for optimizing MPT trading strategy in FX trading. The mathematical optimization which is constrained for this project was done with the SciPy package and resulted in more accurate optimization than Excel's GRG non-linear solver. Also, a comprehensive pipeline for this project was designed to be able to use MetaTrader application outputs. Logging and, data tracking mechanism was also developed and, implemented.

In this project, I try to implement and teach multiple and different GANs architectures and tackle well-known challenges in this area. These contents are mostly tightly knitted to the posts shared on the LinkedIn account and can be reviewed as additional resources for those posts.