I am Currently an undergraduate student of Computer Engineering at Amirkabir University of Technology (Tehran Polytechnic). I am Highly interested in Machine Learning and Artificial Intelligence, particularly in the realms of Computer Vision, Image Processing, AI for Medicine, Natural Language Processing, and Deep Learning; some related projects to these subjects and a few more fields can be found on my GitHub account.

Research and Development Experiences

AIMedic Co.

• AI mini projects
  In 2021’s summer, I spent my summer internship at AIMedic, an AI-based company that works in the medical field. Throughout the first phase of the training, I learned about the basics of machine learning and the principles of model building. The syllabus included regression, convolutional neural networks, semantic segmentation, and how to work with relevant frameworks such as Keras and TensorFlow. Assignments regarding these subjects were given to the trainees as mini-projects. You can view the complete source code here.

• EEG signal
  The following phase of the internship started after selecting some top trainees. I joined the signal processing team and worked on developing a PyTorch-based program that employs EEG signals to predict epileptic seizures. It was a priceless experience as it helped me improve my team-working skills and put me in situations resulting in boosting my accountability. Managing time to keep up with the team members, completing tasks assigned to me during a sprint, and presenting the results to the whole team and scrum master, were some of the invaluable soft skills I gained from this internship phase.

• Mammography
  After that, top trainees got hired as artificial intelligence developers. I got into the Mammography team to enhance my proficiency in image processing. As a team member, my tasks mainly consisted of two parts; first, searching for different datasets of breast images, including various formats such as DICOM, and finding related papers on how to preprocess and train a model on the data—second, employing those preprocessing technics and training convolutional neural networks such as VGG-16 and LSTM, using the images to get good values for precision and recall on automatic breast cancer detection.

Metodata Co.

Visualizing network graph

When I was a trainee at Metodata, a Data Science company, I worked with a massive amount of data gathered from Twitter. Tasks assigned to me were of two types: extracting detailed information from the tweets, such as most mentioned website domains and most frequent unigram and bigram collocations, and the ranking of most mentioned and retweeted accounts. The other task was to figure out the relations between accounts (based on how much they retweeted and mentioned each other’s usernames or the number of mutual followers) and plot the graph of their connections, using Gephi to facilitate comprehending the extracted information.

Hesaba Co.

Data analysis and presentation

Newly fascinated by AI, I enrolled in an internship program offered by Hesaba, a data-driven company, in 2020’s summer. During this internship, I gained experience analyzing different datasets such as Covid-19 data from Johns Hopkins University (you can find the implemented R package here, records of football matches, and classical literature. I also practiced writing visual reports in R Markdown format. For the final project, I trained a homicide vs. suicide classification model using the H2O platform and uploaded it on a Shinyapp host, which you can find here.