Vipul Tyagi

Topic: Leveraging Generative AI for Technical Literature: An Adaptive RAG Framework. • Conducting advanced research on optimizing RAG architectures to enhance retrieval accuracy and generative performance. • Developing a multimodal chatbot using RAG to retrieve and generate responses from proprietary documents. Skills: Business Understanding, python, azure-openai, langchain, llamaindex, langfuse, unstructured, streamlit, git, gitlab, docker, gitlab-actions, neo4j, chromadb, among others.

- Developed a conversational AI chatbot using LLMs and agent systems to guide users and extract information for ML project templates. - Fine-tuned the LLaMA2 with QLoRA technique for interdepartmental chatbot deployment on a proprietary cluster and served as an API. - Conducted knowledge transfer sessions for department-wide Generative AI technology adoption. Skills: python, azure-openai, langchain, langgraph, streamlit, bitsandbytes, accelerate, peft, trl, huggingface, git, MLOps, etc

- Utilized the CRISP-DM workflow to analyze Diesel Injector's time-series sensor data, from cleaning the data to extracting meaningful features. - Developed ML/DL models for Diesel Injector's quality improvement (90% accuracy) and deployed in production using MLOPs tools. - Created XAI dashboards using SHAP values and sensor signal visualizations. - Ensured model alignment with project objectives through continuous evaluation and communication with domain experts and stakeholders.

- Translated MATLAB scripts into efficient C++ code for 3-D grayscale image pre-processing. Skills: C++, MATLAB, Git, GitLab, etc.

- Led a Cross functional team of 10 to implement new products and processes in production for New Product Development (NPD) using agile methodology. - Established manufacturing standards through early involvement in process design and development. - Managed IATF audits, defended auditor questions, and created documentation for new products including (PFD, PFMEA, QCPC).

Current GPA - 1.5 Coursework: Machine learning, Very Deep Learning, Application of Machine learning and Data Science, Embedded Intelligence, Enterprise Data Science, Introduction to Autonomous System, Automotive Software and System Engineering, C++ Programming Project, etc.

Final Grade - 1.1