Colour Scheme
About Me
Fourth-year Computer Science student at Dalhousie University, focusing on Artificial Intelligence and Data Science. With a strong foundation in mathematics, I excel in problem-solving and critical thinking, which I apply to programming and software development. I am proficient in various programming languages, tools, libraries, frameworks and many different areas of Computer Science from Software Development and Database Design to AI and Data Science.
I have successfully completed three internships involving Software and Web Development, as well as Deep Learning, Natural Language Processing, and Generative AI. Through my studies at Dalhousie University and internship positions, I have developed a versatile skill set and the ability to quickly learn and adapt to new technologies. I thrive in both team environments and individual settings and enjoy collaborating with others to achieve common goals. I am committed to continuous learning and growth, both as a developer and as a collaborator.
Outside of my work and studies, I enjoy playing the piano, listening to music, playing video games, and hiking.
Skills
Technical Skills
Software Development, Web Development, Data Structures, Algorithm Design and Analysis, Machine Learning, Data Mining, Generative AI, Natural Language Processing, Database Design, User Interface Design, Object Oriented Programming, Test-Driven Development, Software Testing, REST API Design, Agile Methodology, Game Development
Programming Languages
Java, Python, C, C#, HTML, CSS, JavaScript, SQL
Libraries
React, Node.JS, Spring Boot, Bootstrap, JUnit, NumPy, PyTorch, Pandas, Scikit-learn, PEFT, NLTK, Unity
Tools
Git, Figma, Linux, AWS, Google Cloud, Microsoft Office, MySQL Workbench, Visual Studio, Google Colab
Education
Dalhousie University
GPA: 3.94/4.30
Bachelor of Computer Science (2020 - 2025)
Courses
Experience
Software Developer Intern
Rayleigh Solar Tech
01/2025 - 04/2025
Developed and improved software used to automate lab procedures at a solar technology startup. Built new Python applications and improved existing tools to support automated testing, data collection, and onboarding operations. Refactored codebases for maintainability, designed user-friendly interfaces for users without a technical background, and integrated applications with lab hardware such as cameras and testing equipment. Collaborated closely with scientists and engineers to identify their requirements to develop reliable and user-friendly software. Contributed to improving internal productivity by automating manual processes and lab operations.
Generative AI Extern
Cognizant
06/2024 - 08/2024
Completed two projects with Cognizant and Udacity. The first project focused on software development with Python for animal image classification using different CNN models and the second one involved enhancing sequence classification accuracy through model fine-tuning.
Software Developer Intern
AloDoctor
05/2022 - 08/2022
Worked on enhancing a healthcare platform’s functionality and user experience through implementing new features, improving the design and ensuring responsiveness. Collaborated with a team of software developers, utilizing Agile Methodology for iterative improvements.
Web Developer Intern
Sharif University of Technology
06/2019 - 09/2019
Designed, developed, and maintained a responsive and user-friendly website for a university professor.
Selected Projects
Boardify
A collaborative list-sharing web app developed using React.js, Spring Boot, and MySQL, supporting user registration and authentication, resetting passwords, creating workspaces and task lists, assigning users to workspaces, modifying task status and task filtering and searching.
Scheme Interpreter
A comprehensive Java-based interpreter for Scheme programming language, supporting all the common Scheme operations, recursion and lambda expressions. Developed in a Test-Driven (TDD) process, utilizing Object-Oriented Programming for maintainability and code reusability.
Applying Lightweight Fine-Tuning to a Foundation Model
Used Hugging Face's PEFT library to fine-tune the GPT-2 model for text classification using Python and PyTorch, optimizing the model through targeted fine-tuning to enhance accuracy.
Research
Computationally Lightweight Human Motion Generation
Developed a diffusion-based model for realistic and computationally efficient human motion generation in collaboration with UBC researchers, supervised by Dr. Peyman Servati and Dr. Z. Jane Wang. The work resulted in a collaboratively authored research paper, currently published as an arXiv preprint. Contributions included assisting with model design, implementation, and quantitative/qualitative evaluation of generated motion sequences.
Languages
English
Fluent
Persian
Fluent
French
Beginner
Resume
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