CV
Work experience
2025- : Researcher, LTU, Luleå, Sweden
Implemented AI-powered ReACT agents in industrial automation to enhance human-machine collaboration, optimize production workflows, and enable real-time decision-making for adaptive manufacturing environments. These agents leveraged reasoning and planning techniques to autonomously execute tasks, predict system failures, and ensure continuous operational efficiency.
- Skills & Tools: OpenAI API, GPT-4, OPC UA, Prompt Engineering, LlamaIndex, Knowledge Graphs, AI Planning Algorithms.
Built an AI service platform that integrates SQL chatbot agents for seamless interaction with industrial automation databases and real-time sensor data visualization. The platform enables automated decision-making, optimizing control system efficiency through advanced LLM-based reasoning and real-time execution of industrial tasks.
- Skills & Tools: Python, LangChain, Vector Databases, Retrieval-Augmented Generation (RAG), FastAPI, SQL, REST APIs, IEC 61499, OPC UA.
Developed a multi-agent AI framework for distributed control systems, integrating AI-driven decision-making and real-time task execution across industrial automation platforms. The system enables seamless agent collaboration, intelligent workload distribution, and optimized performance monitoring in decentralized environments.
- Skills & Tools: Multi-Agent Reinforcement Learning (MARL), MAS Frameworks, Distributed Computing, LangGraph.
Optimized LLM fine-tuning for generating IEC 61499 function blocks in industrial automation, enhancing accuracy and response times for AI-driven control system design. This involved iterative benchmarking and training of models to ensure optimal function block generation and seamless integration into automation workflows.
- Skills & Tools: PyTorch, LoRA (Low-Rank Adaptation), IEC 61499.
Developed an AI evaluation pipeline to test model responses for accuracy, factual consistency, and unintended biases, optimizing feedback analysis in an AI-driven workplace well-being platform. Tested various LLMs for benchmarking and evaluation using LangSmith to improve sentiment analysis and stress prediction from employee feedback surveys.
- Skills & Tools: PyTest, LangChain Evaluation, LangSmith, Benchmarking Frameworks, A/B Testing, AI Explainability Tools.
2019-2020: Full Stack developer, RCKR Software Pvt Ltd, Bengaluru, India
- Designed, developed, and deployed end-to-end machine learning solutions, including preprocessing, model training, evaluation, and deployment, using frameworks like TensorFlow, PyTorch, and Scikit-learn.
- Developed scalable and efficient full-stack applications integrating machine learning models, front-end interfaces, and back-end services using technologies such as Python, Next.Js, and DyanamoDB.
2017-2019: System Engineer, Tata Consultancy Services (TCS) , Kochi, India
- Integrated machine learning models into web and mobile applications by developing RESTful APIs and deploying models using cloud platforms like AWS and Azure, ensuring scalability and reliability.
- Designed and developed visually compelling dashboards and reports using tools like Power BI, or Python libraries (Matplotlib, Seaborn) to effectively communicate data findings to stakeholders.
2017: Data Analyst - Research Intern, Uvionics Tech India Pvt Ltd
- Designed, developed, and implemented machine learning models for disease prediction, utilizing algorithms such as logistic regression, random forest, support vector machine, and neural networks to analyze medical data and predict disease risks and outcomes.
- Evaluated and validated machine learning models using techniques such as cross-validation, ROC curve analysis, and confusion matrix to assess model performance and optimize models through hyperparameter tuning and ensemble methods to achieve robust and reliable predictions in real-world healthcare applications.
Education
- B.S. in Electronics and Communication Engineering, SCMS, Kochi, MG University, India, 2014
- M.S. in Computer Science and Engineering, NIT Trichy Campus, (IIIT), India, 2017
- PhD in Industrial AI Agents, LTU, Sweden, 2025 (expected)
Skills
- LLMs & Tools: OpenAI, Anthropic, DeepSeek, AWS Bedrock, Ollama , Langchain, Langsmith, LangGraph
- Machine Learning & Tools : PyTorch, TensorFlow, Keras, Hugging Face Transformers, NLTK, SpaCy
- Frontend - Next.js
- Backend - Python, TypeScript
- Storage - Postgres, DyanamoDB, GraphDB, IPFS, S3
- Containerization: Docker, Kubernetes
- Cloud Computing - AWS
- Software Development & Version Control - REST, GraphQL, Git, GitHub, Jenkins, GitLab CI
My research interests
Service and leadership in EU funded projects
- Currently assigned to Zero-Swarm , MEDUSA and ReArctive Interreg