About Me.
I am a Software Engineer with 4 years of experience in designing, developing, and maintaining scalable web applications. My expertise includes microservices architecture, database optimization, and enhancing user experience. I am passionate about collaborating with cross-functional teams and delivering high-quality solutions.
Experience
- University of Central Florida Graduate Research Assistant
- University of Central Florida Software Engineer Intern
- Caspian Debt Software Engineer
- Micronet Techniks Software Engineer (Consultant)
"Great experiences lead to even greater stories."
Development Skills
- Full Stack Development
- Microservices Architecture
- UI/UX Development
- CI/CD Pipelines
- RESTful APIs
- Database Management
Core SDE Skills
- Testing and Quality Assurance
- Agile Methodologies
- Project Management
- Performance Optimization
- Cross-functional Collaboration
- API Development
Integration & Deployment
- Cloud Computing
- Data Analysis & Quality
- Automation (Scripting)
- Large Language Models
- Machine Learning Integration
- Cloud Platforms (AWS, GCP)
Selected Works.
Full-Stack Development
ReachOut Web Application
Built a feature-rich platform using Next.js and GraphQL to connect international master’s students abroad. Features include user authentication, dynamic posts, chats, and comment systems, delivering seamless connectivity and community engagement.
Medical AI Solution
Breast Cancer Detection Using CNN
Developed an early-detection system for breast cancer using Convolutional Neural Networks (CNN) with TensorFlow. Enhanced diagnostic precision by integrating robust analysis tools like Matplotlib and Pandas.
AI & Machine Learning
Melanoma Detector
Created a high-accuracy skin cancer detection system leveraging SVM and CNN models with ISIC image datasets. Achieved classification accuracies of 83% (SVM) and 81% (CNN), showcasing expertise in computer vision and machine learning.
Deep Learning for Safety
Dizziness Detection While Driving
Engineered a real-time facial analysis system using deep learning and computer vision to identify dizziness or fatigue in drivers. Integrated facial landmark detection, data augmentation, and a fine-tuned CNN model for in-car safety applications.
Cloud-Native Solutions
Inventory Management System
Developed a dynamic inventory system using Node.js and Seaborn for intelligent database analysis and visualization. Deployed using Docker and Kubernetes on AWS, enabling SQL-free operations with robust scalability.