Hi, I'm Tamoghno Ghosh, a Computer Science and Artificial Intelligence undergraduate at Institute of Engineering and Management (IEM), Kolkata.

I am passionate about building intelligent systems, scalable software solutions, and AI-powered applications by combining advanced artificial intelligence techniques with strong software engineering principles.

My work focuses on the intersection of AI research and product engineering, where I develop practical solutions using machine learning, deep learning, full-stack development, and backend system design.

My areas of interest include:

• Artificial Intelligence & Machine Learning
• Deep Learning and Computer Vision
• Natural Language Processing
• Full Stack Development
• Backend Engineering
• System Design and Scalable Architecture

I gained research experience as an AI & Machine Learning Research Intern at National Institute of Technology (NIT) Sikkim, working on forecasting systems, predictive modeling, feature engineering, and machine learning pipelines.

I have also worked as a Full Stack Developer Intern at Qusbi Infotech Pvt. Ltd., developing scalable APIs, secure authentication systems, responsive applications, and backend architectures.

Currently, I am exploring Collaborative Learning, Federated Learning, and advanced AI architectures while continuously improving my engineering and problem-solving skills.

I believe in learning through collaboration, building impactful projects, and transforming innovative ideas into real-world technology solutions.

• Collaborative Learning and Federated Learning Systems
• AI/ML Research Projects
• Scalable Full Stack Applications
• Advanced Machine Learning Workflows

• Generative AI
• Large Language Models
• Deep Learning Optimization
• System Design
• Production Machine Learning

May 2026 — July 2026 | Remote

Worked on research-driven artificial intelligence projects involving machine learning forecasting systems, predictive modeling, and automated ML pipelines.

• Built AQI forecasting models using Linear Regression, Ridge Regression, and XGBoost achieving an R² score of 0.71.
• Developed stock market prediction pipelines using XGBoost, CatBoost, Random Forest, and LSTM architectures.
• Processed and feature-engineered 100,000+ environmental and financial records.
• Automated end-to-end workflows including preprocessing, training, tuning, and evaluation.
• Performed comprehensive model analysis using MAE, RMSE, Accuracy, Precision, Recall, F1-score, and R² metrics.

Skills:

Python Machine Learning Deep Learning XGBoost LSTM Scikit-Learn Pandas NumPy

(Startup Incubated at Jadavpur University)

December 2025 — March 2026 | Kolkata

Worked on scalable web application development and backend engineering for the Techdarshi platform.

• Developed 50+ RESTful APIs using Django REST Framework.
• Built responsive React.js interfaces with reusable components.
• Implemented JWT authentication and role-based access control.
• Integrated Razorpay payment gateway for secure transactions.
• Optimized backend performance through query optimization, indexing, and caching strategies.
• Reduced API response time by 35%.

Skills:

React.js Django REST APIs MongoDB JWT Backend Engineering System Design

Learning:
  - Advanced Deep Learning
  - Generative AI
  - Large Language Models
  - MLOps
  - System Design

Building:
  - AI Powered Applications
  - Scalable Backend Systems
  - Real-Time Web Applications
  - Intelligent Automation Platforms

Exploring:
  - Collaborative Learning
  - Federated Learning
  - Computer Vision Systems
  - Natural Language Processing
  - Cloud Architecture

Open To:
  - AI/ML Research Opportunities
  - Software Engineering Internships
  - Open Source Collaboration
  - Building Innovative AI Products