Resume

Led product strategy and full-stack development of 3 SaaS products for digital marketing agencies.

• Implemented AI-powered automation with RAG patterns and LangChain for intelligent content processing
• Designed workflow automation systems using n8n to streamline business processes and reduce manual tasks by 65%
• Built real-time dashboards with Next.js and developed Chrome extensions for enhanced productivity
• Managed cross-functional teams using agile methodologies and continuous deployment pipelines

Designed and implemented DevOps solutions for enterprise applications.

• Architected and implemented CI/CD pipelines using Docker, Jenkins, GitLab, and OpenShift
• Designed and deployed containerized microservices architecture for enterprise applications
• Built custom workflow automation tools with n8n and Power Automate to streamline DevOps processes
• Implemented infrastructure as code (IaC) using Terraform and Ansible for cloud resource management
• Conducted security audits and optimized infrastructure performance, reducing deployment time by 35%

Developed a marketplace application (SellSafe) for local reselling communities.

• Architected comprehensive Flutter application using MVVM pattern and clean architecture principles
• Implemented advanced state management with Provider and BLoC patterns for predictable flows
• Integrated Stripe payment gateway and Auth0 authentication
• Followed Test-Driven Development approach with comprehensive test coverage

Led development of a social media application using Flutter frontend and Firebase backend.

• Led development of UruMee social media application from concept to production
• Implemented real-time data synchronization using GraphQL for efficient state management
• Solely designed all screens using Figma and developed frontend with Flutter
• Set up CI/CD pipeline with GitHub Actions for automated testing and deployment
• Successfully published application to Google Play Store and App Store

Developed a Push-To-Talk conversation app (Talker Network) using Flutter and WebSockets.

• Implemented Socket programming for real-time communication between users
• Integrated Branch.io for deep linking functionality
• Applied MVC architecture for organized codebase structure
• Mentored junior developers on Flutter best practices

Co-founded digital solutions startup for strategic marketing.

• Grew company LinkedIn presence to 16,000+ followers
• Led technical direction and product development
• Managed a team of 50 interns across software development, HR, and marketing
• Designed and implemented MVP from concept to launch

Specialized in practical AI applications, deep learning, and natural language processing.

• Graduated with Distinction
• Developed novel approaches to retrieval augmented generation (RAG)
• Conducted research on fine-tuning large language models for specific domains

Specialized in AI and machine learning with practical applications in computer vision and NLP.

• Top-ranking student in final year
• Published 4 research papers in international journals and conferences
• Developed a vehicle detection system using TensorFlow Lite

Advanced Vehicle Detection Heads-Up Display with TensorFlow Lite

Proceedings of Third International Conference on Sustainable Expert Systems

This paper presents a novel approach to real-time vehicle detection on mobile devices using TensorFlow Lite. The system is designed to run efficiently on resource-constrained devices while maintaining high accuracy and low latency. The approach combines transfer learning with model optimization techniques to create a lightweight yet powerful detection system suitable for heads-up display applications in automotive safety.

Smart Moisture Sensor-Based Irrigation System

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)

This paper proposes an IoT-based smart irrigation system that optimizes water usage in agricultural applications. By combining soil moisture sensors with weather data and predictive algorithms, the system can determine optimal irrigation schedules. Field tests demonstrate significant water savings and yield improvements compared to traditional irrigation methods.

Enhanced Early Detection Of Brain Tumor Using Deep Belief Network For Improvising Human Life Span And Health

2021 Innovations in Power and Advanced Computing Technologies (i-PACT)

This research presents an improved approach to brain tumor detection using Deep Belief Networks (DBNs). The proposed method achieves higher accuracy and faster processing times compared to conventional CNN approaches, particularly when working with limited labeled data. The system is designed to assist medical professionals in early diagnosis, potentially improving patient outcomes.

Sentinel – A Neighbourhood based Live Location Streaming Safety APP for Women and Children

Revista Gestão Inovação e Tecnologias

This paper introduces Sentinel, a mobile application designed to enhance the safety of women and children through real-time location sharing and community safety features. The system incorporates emergency alerts, trusted contacts, and neighborhood watch functionality. The paper discusses both the technical implementation and the social impact potential of such safety applications.