AI-Powered Sentiment Analysis Tool
Summary
Developed an advanced AI-powered sentiment analysis tool to process and interpret feedback efficiently.
About
Highly accomplished AI Engineer and Full Stack Developer with robust expertise in designing, optimizing, and deploying scalable machine learning models and AI solutions. Specializing in Natural Language Processing (NLP) and recommendation systems, I integrate advanced AI into full-stack applications, driving impactful automation and enhanced decision-making. Skilled in cloud platforms (AWS, Azure) and containerization (Docker, Kubernetes) for robust deployment. Possessing a curious, problem-solving mindset and strong collaborative skills, I am dedicated to developing ethical, high-performance AI systems that deliver significant business value and user engagement.
Work
eHealth4Everyone
|AI Intern
Summary
Driving innovation in healthcare through AI-powered solutions, enhancing clinical decision-making and automating medical workflows.
Highlights
Developed and deployed AI-powered healthcare tools, significantly enhancing decision-making capabilities and automating complex medical workflows.
Built and fine-tuned advanced NLP models for precise medical text analysis and interactive chatbot applications, improving data utility.
Integrated sophisticated AI solutions into existing web platforms via robust REST APIs, enabling real-time data processing and seamless user interaction.
Freelancer
|AI Engineer & Full Stack Developer
Summary
Led end-to-end development of AI-driven applications, from model design to full-stack deployment, for diverse client needs.
Highlights
Designed and optimized machine learning models, delivering personalized recommendations and AI-driven automation systems that enhanced user engagement.
Developed comprehensive AI-powered applications using the MERN stack, integrating complex ML models for real-time decision-making and improved functionality.
Engineered and deployed robust REST APIs and microservices, ensuring scalable and high-performance AI applications.
Successfully deployed ML models on leading cloud platforms (AWS, Azure) and managed containerized applications using Docker and Kubernetes, ensuring high availability and scalability.
FSS DS Technologies
|Field Data Analyst Intern
Summary
Contributed to data preparation and analytical processes, laying the groundwork for robust AI model development and operational efficiency.
Highlights
Preprocessed large, complex datasets, effectively preparing them for AI model training and streamlining operational automation workflows.
Implemented advanced anomaly detection techniques, significantly improving data reliability and accuracy within predictive analytics initiatives.
Education
Landmark University
Bachelor of Engineering
Mechatronics Engineering
Courses
Machine Learning
Artificial Intelligence
Data Science
Engineering Mathematics
Robotics
Automation
AI-driven Control Systems
Skills
Machine Learning
Supervised Learning, Unsupervised Learning, Reinforcement Learning.
Natural Language Processing (NLP)
GPT, BERT, Text Generation, Sentiment Analysis.
Recommendation Systems
Collaborative Filtering, Matrix Factorization, Deep Learning Models.
Computer Vision
YOLO, GANs, Object Detection.
Ethical AI
Fairness, Bias Mitigation, Explainability.
Backend Development
Node.js, Express.js, Flask.
API Development
RESTful APIs, FastAPI, GraphQL.
Cloud & DevOps
AWS, Azure, GCP, Docker, Kubernetes, CI/CD Pipelines.
Frontend Development
React.js, Next.js, TypeScript, JavaScript, HTML, CSS.
Databases
PostgreSQL, MySQL, MongoDB.
Programming Languages
Python, JavaScript.
Programming Languages
TypeScript, SQL.
Programming Languages
C++.
Projects
Scalable Cloud-Deployed AI Models
Summary
Engineered and deployed scalable AI models on leading cloud platforms, optimizing for performance and reliability.
Machine Learning API Integration
Summary
Designed and integrated machine learning APIs into various applications to enhance functionality and user interaction.