Debashish Panda

• Designed and deployed multi-agent AI systems (LangChain CrewAI) to automate complex procurement and enterprise workflows through intelligent task decomposition and coordination.
• Integrated RPA with GenAI/LLMs to build an insurance document processing system that ingests, classifies, and extracts data from policies, claims, and forms — enabling faster, error-free operations and reducing manual effort.
• Developed scalable RAG pipelines using FAISS and Pinecone to retrieve information from structured and semi-structured datasets with high accuracy.
• Fine-tuned and prompt-engineered LLMs (OpenAI, Claude, open-source) for copilots, automated research agents, and advanced summarization tools.
• Built secure, containerized deployments with Docker, GitHub Actions, and AWS, while managing the full MLOps lifecycle (model versioning, drift monitoring, feedback loops, rollback) using MLflow.
• Partnered with cross-functional teams to convert abstract business requirements into production-ready automation pipelines, including chatbots, competitor analysis systems, and intelligent assistants.

Technical Expertise: Multi-Agent AI (LangChain CrewAI), RAG (FAISS, Pinecone), LLM Fine-tuning & Prompt Engineering (OpenAI), RPA (UiPath), Intelligent Document Processing, MLOps (MLflow), Cloud & DevOps (AWS, Docker, GitHub Actions), Python (Pandas, NumPy, Spacy Scikit-learn).

• Automated production data collection and reporting using RPA and advanced data analysis frameworks, improving accuracy and reducing manual effort.
• Analyzed production datasets (machine temperature, vibration, energy consumption, torque, pressure, material composition, insulation resistance, and surface quality) to identify performance trends and support predictive maintenance.
• Leveraged UiPath Document Understanding to extract data from engineering drawings, invoices, and test reports, enabling seamless integration into production and ERP systems.
• Implemented business process automation frameworks, combining RPA with Python (Pandas, NumPy, Scikit-learn) to streamline data flows and optimize reporting cycles.
• Managed end-to-end delivery using Jira — created user stories, assigned tasks, tracked progress, and ensured timely release of automation solutions.

Technical Expertise: UiPath, UiPath Document Understanding, Python (Pandas, NumPy, Scikit-learn), LINQ, Jira, Business Process Automation Frameworks, End-to-End RPA Development.

• Implemented 5 unattended automation projects using UiPath RE Framework, streamlining high-volume processes like onboarding report generation, CRM data management, payroll, and attendance tracking.
• Built intelligent document processing bots with UiPath Document Understanding and AI-based image classification to extract data from invoices and automate file handling across 20+ applications.
• Gathered requirements and authored PDDs/SDDs for automation projects, including automated content grading and student registration, while leading client discussions and knowledge transfer sessions.
• Performed testing, monitoring, and troubleshooting of automation flows, resolving performance issues and managing robot provisioning/execution via UiPath Orchestrator.
• Applied data analysis and ML model training for classification and decision-making within automation pipelines using UiPath AI Center and integrated ML components.

Technical Expertise: UiPath, RE Framework, Document Understanding, AI Center, Orchestrator, Action Center, Image Classification (AI), ML Model Training, Python (Pandas, NumPy), Business Process Automation, PDD, SDD, End-to-End RPA Development.

Created Physics and electrical Solutions for various books,
helped students through video and presentations.
Knowledge on writing math expressions using Latex codes.
Technical Expertise: Astrophysics, Advanced Math

• Automated production tracking and machine performance reporting using Python, reducing manual monitoring and improving efficiency.
• Partnered with R&D to optimize machine cycle times, enhancing production throughput.
• Analyzed sensor data (temperature, vibration, cycle times) using Python & MATLAB to detect anomalies and improve quality control.
• Applied Machine Learning models (Logistic Regression, Decision Trees) to predict defects in automobile components, reducing rejection rates.
• Built predictive maintenance pipelines by processing large production datasets, preventing downtime.
• Automated repetitive shop-floor tasks using UiPath RPA, cutting manual effort.

Technical Expertise: Python, SQL, MATLAB, UiPath, Machine Learning, Predictive Analytics, AI-driven Quality Assurance, RPA Automation, Data Preprocessing.