The essential steps in my learnings and skills expanding are working on different projects from university to research center to industry. Provided below is a summary of the projects that I have participated in.
UniFeat is an open-source tool, developed completely in Java, for performing feature selection process in different areas of research. UniFeat provides a set of well-known and state-of-the-art feature selection methods within the significant auxiliary tools, including performance evaluation criteria, visual displays, and statistical analysis to compare the performance of feature selection methods.
PyKale is a library in the PyTorch ecosystem that aims to make machine learning more accessible to interdisciplinary research. It provides an accessible, scalable, and sustainable design, focusing on multimodal learning and transfer learning for graphs, images, and videos. PyKale promotes green machine learning principles and enables interdisciplinary research in various applications such as bioinformatics, graph analysis, and medical imaging.
Onco Gene Selector is a Java-based software for gene selection in microarray data using machine learning techniques. After graduating from university, this project was my first attempt to apply artificial intelligence in solving real-world problems that challenged me with cancer detection/classification on high-dimensionality microarray data with mislabels or unreliable samples.
I have been developing a website for the data science and artificial intelligence community at the University of Sheffield. This project is funded by the Turing Network Development Award.
An online platform for crowdfunding to support start-ups in Iran. It works by making financial contribution from a large group of people for financing projects or business operations.
Title: New feature selection methods based on filter approach using ant colony optimization algorithm