Software Engineer | Prev @ ADP
Ex – Research @ Bio-AI Lab, DRDO, ATDC – IIT KGP

Backend Engineering • AI/ML • LLMs • Agentic AI

🎓 B.Tech Computer Science & Engineering — KIIT University (2022–2026)

• 📊 Working on Applied Machine Learning, Healthcare AI (Fairness & Optimization), Pattern Recognition, and Network Security
• 🔬 Exploring research in Explainable AI and Bioinformatics
• ⚙️ Interested in building scalable ML systems and backend infrastructure for AI applications

📫 Contact:
📧 mitulgoswami1212@gmail.com
📞 +91 8584876789

🔗 https://docdynamo.in

• Built a web-based system to ingest, store, and process documents, exposing APIs for efficient querying and retrieval of relevant content.
• Designed document indexing and retrieval workflows to handle unstructured data at scale.
• Deployed the application on Microsoft Azure, serving 2.9K+ global users.

Stack

Python • LangChain • Flask • LLMs • Vector Embeddings • REST APIs • HTML • CSS • Microsoft Azure • Docker

🔗 https://github.com/mitul-goswami/CopyChecker-AI

• Built a backend data-processing pipeline to handle scanned answer sheets by extracting, structuring, and storing textual data for evaluation workflows.
• Implemented an OCR-based preprocessing module to process image uploads and normalize extracted text, reducing manual correction effort by 30%.
• Designed modular services to support file ingestion, processing, and result generation, improving reliability and maintainability of the system.

Stack

Python • Flask • Yolov8 • LLMs • REST APIs • HTML • CSS

🔗 https://github.com/mitul-goswami/LitReviewAI

• Designed and built a multi-agent AI system that autonomously generates structured academic literature reviews from a single research topic by orchestrating specialized agents for paper discovery, PDF extraction, summarization, cross-paper comparison, and final review generation.
• Implemented a backend pipeline to retrieve research papers from the web, extract text from PDFs, and generate structured analyses including methods, results, limitations, and research gaps.
• Developed a full-stack research interface enabling users to generate publishable Markdown and LaTeX literature reviews; containerized the system using Docker for reproducible deployment.

Stack

Python • FastAPI • LLMs • ArXiv & Semantic Scholar REST API • PyPDF • HTML • CSS • JavaScript • Docker

💡 Building intelligent systems that combine software engineering and machine learning to solve real-world problems.