About Me

I build intelligent systems that bridge AI research and real-world business applications. With a background in Cognitive Systems and Software Engineering, my experience spans LLMs, Agentic AI, Computer Vision, and Document Intelligence, with a focus on developing scalable AI solutions that automate complex workflows and create measurable impact in industrial and enterprise environments.

My main interests include:

• Generative AI
• Large Language Models (LLMs)
• Multimodal AI
• Computer Vision
• Human-AI Interaction
• Industrial AI systems

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Technical Skills

Programming & Machine Learning

• Python
• PyTorch
• Hugging Face Transformers
• scikit-learn
• SpaCy

Generative AI & LLM Systems

• LangChain
• LangGraph
• Retrieval-Augmented Generation (RAG)
• Agentic AI Workflows
• Prompt Engineering

Computer Vision

• OpenCV
• YOLO
• CLIP
• Stable Diffusion
• scikit-image

Cloud, MLOps & Deployment

• Azure Databricks
• Azure AI Search
• Azure Blob Storage
• Docker
• GitHub CI/CD
• Bitbucket
• Chainlit
• Gradio

Web Development

• JavaScript
• TypeScript
• Angular

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Experience

Data Science Intern

Liebherr Digital Center, Ulm, Germany
July 2025 – Present

• Engineered agentic LLM pipelines for efficient information retrieval across internal knowledge repositories utilizing LangChain, LangGraph, and Databricks.
• Innovatively developed document intelligence workflows using advanced computer vision tools such as YOLO and SAM to extract structured data from complex engineering drawings.
• Designed and implemented a vision-based safety monitoring system tailored for construction site scenarios, employing PyTorch for optimal performance.
• Contributed to continuous integration/continuous deployment (CI/CD) processes and agile development workflows through effective use of GitHub and Jira.

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Software Engineer

PricewaterhouseCoopers (PwC), Kolkata, India
July 2019 – August 2022

• Developed workflow management features to create, assign, track, and manage work requests across distributed delivery teams.
• Built a financial reconciliation module, supporting automated matching, manual exception handling, secure access, and reporting.
• Developed a financial journal application capturing workflows for structured data entry, validation, approvals, and SAP IA integration.

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Research & Projects

Master’s Thesis at Visual Computing Group, Ulm University

• Engineered a comprehensive benchmarking framework to evaluate state-of-the-art text-to-3D generative models, enhancing the understanding of model effectiveness.
• Analyzed and identified performance trade-offs across various model architectures in aspects such as semantic alignment, output quality, and structural plausibility, contributing valuable insights to the field.

View GitHub Repository

Generative AI Project

Investigated the effectiveness of human feedback in identifying artifacts in AI-generated human portraits.

Explainable AI Project

Analyzed the impact of image segmentation techniques on the runtime and quality of local explanation methods used to interpret CNN predictions.

Research Assistant at Dept. of Applied Cognitive Psychology, Ulm University

Analyzed material perception using visual and haptic cues of object properties.

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Education

M.Sc. Cognitive Systems
Ulm University, Germany
Grade: 1.5 • 2022 – 2025

B.Tech Computer Science
Institute of Engineering and Management, Kolkata, India
Grade: 8.7/10 • 2015 – 2019

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Languages

• English (C1)
• German (A2)
• Bengali (Native)
• Hindi (Native)

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Interests

Professional

Generative AI • Multimodal AI • Computer Vision • Human-AI Interaction • Autonomous Systems

Personal

Painting • Badminton • Dancing • Cooking • Yoga

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Contact

Open to discussions on AI research and emerging AI technologies, and interested in AI Engineering job opportunities. Feel free to connect.

📧 chandramita.bhattacharya@gmail.com
🔗 LinkedIn: https://www.linkedin.com/in/chandramita-bhattacharya