About me

I'm Amir Hossein, a driven software engineer with a passion for ML, deep learning, and data mining. With over ten years of experience in the tech industry, I have a diverse background as an Android developer, team leader, and technical manager. Coding is my hobby, but creating impactful software solutions is my true passion.

As a Ph.D. holder in Software Engineering, I bring a wealth of knowledge and expertise to the table. My passion for AI and machine learning drives me to stay at the forefront of these cutting-edge domains, and I am constantly seeking out new challenges and opportunities to grow my skills.

Education

Work Experience

Projects

• Twitter Like Prediction
  Hackathon (Kaggle Dataset)
  The goal was to predict the number of likes for a tweet. The final architecture was a complex combination of a BERT model trained on the tweet text and a CNN model trained on the numerical features of tweets.

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  Abstractive Summarization of Source Code
  ETS University
  We generated abstractive summaries using LLMs such as BERT, BART, and GPT for Android APIs discussed on StackOverflow and evaluated by ROUGE and BLEU.

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  Summary Generation for Code Blocks Using Their Surrounding Context
  ETS University
  We used TextRank as an unsupervised learning algorithm to generate extractive summaries for code blocks based on their surrounding natural languages such as descriptions, discussions and comments.

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  Multi-label Classification of Image Data
  Kaggle Competition - Ranked 2nd / 300 with %98 accuracy
  The competition’s goal was to develop a model to detect hand-written sequences of numbers using CNN models and data augmentation.

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  Analyzing COVID-19 Search Trends and Hospitalization on Google dataset
  Mcgill University - Mila Institution
  We were interested in analyzing and predicting the rate of COVID-19 hospitalization based on the symptoms using Google Covid-19 Open Data utilizing PCA, K-means, KNN, and decision trees.