Ardalan Askarian ArdalanAskarian

🎓 Computer Science Student | 💻 Software Developer | 🔬 AI Research Intern

🚀 About Me

I'm a passionate Computer Science student at the University of Saskatchewan with hands-on research and development experience. Currently working as a Software Developer Intern at BEAP Lab, where I spearhead the development of front-end and back-end systems for the BEAP Engine - a platform for processing and analyzing large datasets for Smartwatches.

🎯 What I Do

🤖 Fine-tuning LLMs for automated bug classification (94.54% accuracy)
🖼️ Building AI-assisted image annotation platforms
📊 Processing & analyzing large-scale smartwatch datasets
🔬 Conducting research at the intersection of AI & software engineering

🎓 Current Status

Education: Computer Science @ USask
Position: Software Developer Intern @ BEAP Lab
Duration: Oct 2024 - Present
Research: AI-Assisted Annotation @ IMG Lab
Focus Areas:
  - Artificial Intelligence & ML
  - Data Processing & Analysis
  - Full-Stack Development
  - Research & Development

🔭 Current Projects

🤖 AI-Assisted Image Annotation Platform (Leading Development)

Django-based system combining ML with human expertise
Mass-labeling computer vision datasets
Research focus on inter-annotator agreement & cognitive workload
Tech: Django, Python, OpenCV, scikit-image, JavaScript, Selenium

📊 BEAP Engine Development (Software Developer Intern)

Building front-end and back-end systems for smartwatch data
Processing & analyzing large-scale datasets
Real-time data visualization & insights
Tech: Full-stack development, data processing pipelines

🧠 Fine-Tuning LLMs for Bug Classification (Research Completed)

94.54% accuracy using GraphCodeBERT
Manually labeled 1,552 GitHub issues across 4 major projects
Transformer models outperformed traditional ML baselines
Models: CodeBERT (93.99%), GraphCodeBERT (94.54%), DistilBERT (92.90%)

⚡ Circuit Optimization Research (Coming Soon)

Developing ML algorithms for electronic circuit layout optimization
AI-driven routing algorithms & performance analysis
Applications in semiconductor industry & chip design

🌱 Research Interests

Area	Focus
🤖 AI & Machine Learning	Computer vision, data modeling, human-AI collaboration
🧠 Large Language Models	Fine-tuning transformers, automated classification systems
⚙️ Software Engineering	Bug classification, software maintenance, AI-driven debugging
📊 Data Processing	Large-scale dataset processing, optimization algorithms

🛠️ Tech Stack

💻 Languages

🚀 Frameworks & Libraries

🧠 AI & Research Tools

🛠️ Tools & Platforms

🔬 Featured Research & Projects

🏆 Highlighted Research

🤖 Fine-Tuning LLMs for Bug Classification

Advanced Software Engineering Research

+ 94.54% Accuracy with GraphCodeBERT
+ 1,552 Manually Labeled GitHub Issues
+ Outperformed Traditional ML Baselines

Key Results:

GraphCodeBERT: 94.54%
CodeBERT: 93.99%
DistilBERT: 92.90%

Dataset: React, VS Code, Scikit-learn, TensorFlow

📄 Read Full Paper

👥 Team: Princess Tayab, Timofei Kabakov, Marmik Patel, Ardalan Askarian

🖼️ AI-Assisted Image Annotation Platform

Current Research @ IMG Lab

Research Focus:

🎯 Inter-annotator agreement optimization
🧠 Cognitive workload assessment
⚡ Annotation efficiency improvements
🤝 Human-AI collaboration workflows

Tech Stack:

Backend: Django, Python
Computer Vision: OpenCV, scikit-image
Automation: Selenium
Frontend: JavaScript

Timeline: May 2025 - August 2025

💡 Other Notable Projects

⚡ Circuit Optimization

ML for Electronic Design Automation

Circuit placement optimization
AI-driven routing algorithms
Performance analysis
Applications in semiconductor design

📱 iOS Weather App

Native iOS Development

Real-time weather data
Core Location integration
WeatherKit API
Clean Apple UI design

🏥 Dentistry Website

Professional Web Development

Appointment booking system
Google Maps integration
Responsive CSS Grid
Form validation

⚽ Sports Scheduler

React & Redux Platform

Team scheduling & management
Calendar integration
Push notifications
Real-time updates

🏰 Darkness Defenders

Unity Game Development

Tower-defense mechanics
Progressive difficulty
Game AI implementation
Multiple enemy types

📊 BEAP Engine

Data Processing Platform

Smartwatch data analysis
Front-end & back-end systems
Large-scale dataset processing
Real-time insights

📊 GitHub Analytics

🏆 GitHub Achievements

📈 Most Used Languages

🎯 Current Focus Areas

AI Research
_{LLMs & Transformers}

Full-Stack Dev
_{Django & React}

Computer Vision
_{Image Processing}

Data Science
_{Large-Scale Processing}

🤝 Let's Connect & Collaborate

📫 How to reach me

💼 Open to Opportunities

🔬
Research
Collaborations

💼
Internship
Opportunities

🚀
Freelance
Projects

📚
Academic
Partnerships

🤖
AI/ML
Projects

Primary Research Interests: Large Language Models • Automated Bug Classification • Computer Vision • Human-AI Collaboration • Software Engineering

💡 Quick Facts About Me

🎓 Education: Computer Science @ University of Saskatchewan (Dec 2026)
🔬 Research Achievement: 94.54% accuracy in LLM-based bug classification
🤖 Passion: Intersection of AI and software engineering
💼 Experience: Theoretical research + practical development
🏗️ Building: Large-scale data processing & analysis systems
🎮 Hobbies: Game development (Unity, C#), AI experimentation
🧠 Vision: AI-powered revolution in software maintenance

⭐ If you find my work interesting, consider starring my repositories!

📈 Profile Stats

💬 Thanks for visiting! Always open to research collaborations, internships, and AI/ML projects!

_{Last Updated: September 2025}