Ing. Vamsi krishna Kommineni

• Leveraged deep learning to extract critical information from digital images, including image classification and instance segmentation. • Designed a RAG-supported LLM pipeline to analyze and extract information from private documents. • Constructed a knowledge graph automatically using LLMs from extracted data in documents. • Worked with multimodality models to extract relevant information using text prompts from images • Designed a series of AI agents to automate the decision-making processes.

• Led end-to-end projects at Max Planck Institute for Biogeochemistry, applying machine learning models like Random Forest and Regression Trees to predict leaf area based on environmental factors. • Collected and annotated data, focusing on delivering actionable insights and optimizing models for real-world applications. • Utilized a range of machine learning techniques to solve regression problems and achieve impactful results in the environmental sector.

Reconstruction of noisy signals using compressed sensing and Fourier transformation

Scientific computing (python)

Operational research, CNC Programming