Building intelligent, scalable solutions that solve real-world problems. Specializing in AI agent architectures, LLM orchestration, and robust backend engineering.
I'm Om Rameshwar Surase, a Master's student in Computer Science specializing in Big Data and Artificial Intelligence at SRH University of Applied Sciences Heidelberg — currently based in Leipzig, Germany.
My journey started in Electronics & Telecommunication Engineering, providing me with a strong foundation in systems thinking. This curiosity evolved into a deep passion for Artificial Intelligence, specifically in building systems where intelligent agents interact with real-world data in structured, measurable ways.
Whether orchestrating LLMs locally with Ollama, building agentic backends using FastAPI, or performing statistical analysis on complex datasets, I thrive at the intersection where data meets intelligent design.
Grade: 1.4
CGPA: 8/10 (German Grade: 2.0)
Developed an agent-based backend system enabling AI to reason and execute tasks using locally hosted LLMs via Ollama. Built with a modular architecture separating agent logic, tool execution, and orchestration using FastAPI.
View RepositoryBuilt a multi-agent AI platform for real-time emergency detection and intelligent dispatch. Integrated Azure OpenAI GPT-4o, Azure Vision, and Speech agents to process multi-modal inputs into structured incident reports.
View RepositoryAnalyzed heterogeneous datasets to study AI adoption trends and workforce impact. Performed thorough EDA and applied statistical techniques including correlation analysis, regression modeling, and ANOVA.
View RepositoryBuilt a Python-based voice assistant capable of executing tasks using speech commands. Integrated NLP pipelines for intent detection, enabling real-time data retrieval and hands-free system control.
View RepositoryDeveloped an AI chatbot to generate automated, human-like replies using GPT models. Improved maintainability through clean backend architecture and modular design, allowing seamless workflow integration.
View RepositoryDeveloped an intelligent system to detect and prevent overloading in trucks and wagons using sensor-based monitoring and real-time data processing. Designed to improve transportation safety, reduce structural damage, and ensure regulatory compliance.
View DetailsLearn Python from Scratch
Fundamental Concepts & Applications
Data Querying & Management
Publication: Solution for Overloaded Trucks and Wagons
Whether you are looking for a motivated Werkstudent, want to collaborate on a data-driven project, or simply wish to discuss AI architectures — I would be delighted to hear from you.
Leipzig, Germany · Remote possible · Open for Mandatory Internship from August
Send an Email