Building intelligent systems at the intersection of AI and human experience.
MCA student (2026) at IEM Kolkata with a passion for AI/ML, data analytics, and full-stack development. I craft solutions that bridge the gap between complex data and meaningful insights — from emotion recognition pipelines to Power BI dashboards that drive real decisions.
From building privacy-hardened emotion recognition models to designing AI-powered sustainability dashboards — I gravitate toward problems where data meets real human impact. Currently pursuing MCA with a specialization in AI, Data Science & Cloud Computing.
12+
Projects Built
5★
HackerRank Python
80.9%
MCA CGPA
2026
Graduating
Recent Certifications
Education
Institute of Engineering & Management
Pursuing Master of Computer Applications with specialization in Artificial Intelligence, Data Science, and Cloud Computing. CGPA: 80.9% (up to 3rd Semester).
Education
Sarada Ma Girls' College, Barasat
Foundation in computer science, programming, database management, and software development. Graduated with 71.30%, building skills in Python, Java, and web technologies.
Training
Euphoria GenX
Built real-world Power BI dashboards integrated with AI/ML capabilities. Gained deep expertise in data transformation, DAX measures, and AI visual features applicable to enterprise analytics and BI workflows.
Research
IEM Kolkata (Agile Team)
Led ML development for a privacy-focused emotion recognition system. Collaborated in an Agile team of 4 with weekly sprints, peer code reviews, and structured SDLC documentation.
AI / NLP
A RAG-powered resume screening system that semantically matches candidate PDFs to job descriptions. Uses OpenAI embeddings, Pinecone vector search, and GPT for LLM-generated match reasoning.
AI / ML Security
An emotion recognition model hardened against adversarial, inference, and reconstruction attacks — protecting facial data privacy in real-world ML deployment scenarios.
Data Analytics / BI
Interactive Power BI dashboard tracking CO₂ emissions, renewable energy usage, and recycling impact for organizational sustainability reporting, with AI-driven insights surfacing reduction opportunities.
ML / Cybersecurity
Locally-executable phishing detection using Genetic Algorithm feature selection — improving classification accuracy while reducing noise and model overfitting in offline email security.
Full-Stack Web
Real-time restaurant booking system handling 50+ daily reservations with a 30% reduction in booking errors. PHP backend with MySQL database achieving 99.9% uptime.
A compact tech stack grid with a clean dark interface, subtle glow, and soft hover motion.
Robust server-side solutions built for performance, stability, and clean architecture.
Designing scalable systems that grow with your product and team.
Careful analysis to improve quality, maintainability, and security.
Leveraging modern frameworks to accelerate delivery without unnecessary complexity.
Connecting systems with clean, well-documented interfaces and reliable data flow.
End-to-end development from concept to production-ready software.
Move fast with focused prototypes, then refine the best ideas into production-ready features.
Use AI tools to improve speed, clarity, and decision-making without losing engineering quality.
Treat schema changes, migrations, and data rules as versioned assets so every change stays traceable.
Test the parts that matter most: validation, critical flows, and edge cases that protect users.
Keep environments reproducible and deployment-ready through versioned configuration and automation.
Ship consistently with automated checks, predictable releases, and a low-friction delivery pipeline.
Work closely with people, share context early, and keep the solution moving together.
Plan rollouts, reduce downtime, and keep releases calm, observable, and reversible.
Meet deadlines through realistic scoping, steady progress, and honest trade-offs.
Make progress visible, surface blockers early, and keep expectations aligned.
Keep updates short, clear, and frequent so no one is surprised by the next step.
Write just enough for the next person to move forward confidently without confusion.
Expect invalid input, validate assumptions, and handle edge cases before they become issues.
Stop early when assumptions break so problems stay small and easy to fix.
Keep layers focused so UI, logic, and data responsibilities stay easy to change.
Prefer simple solutions and avoid building extra complexity you do not need yet.
Extract reusable logic so the same idea lives in one place and stays maintainable.
Design components and services so they are easier to extend, test, and maintain.
Use expressive names and clean structure so the code explains itself naturally.
Model software around real business concepts so the product stays understandable.
Apply proven patterns when they solve a real problem, not just because they exist.
Keep business logic independent from frameworks so the system stays flexible.
Use types to catch mistakes early and communicate intent clearly.
Open to internships, AI/ML projects, data analytics roles, and product engineering work. Reach out if you want to collaborate on an idea, research project, or modern web experience.
Ready for