OMKAR SACHIN BINDU

Highly skilled data analyst with expertise in Python, Java, SQL, and MySQL. Proficient in Microsoft Excel and Word, Power BI, and database management. Demonstrated ability in data cleaning, data visualisation, ETL processes, and exploratory data analysis using Pandas and NumPy. Adept at transforming complex datasets into actionable insights to drive business decisions. Career goal: to leverage analytical skills to contribute to innovative data-driven solutions.

• Mastering Data Structures & Algorithms using C and C++
• Key Skills: C++ C
• Omkar Bindu
• Key Skills: java , oop,dsa

Music, Reading, Watching Movies

• Mastering Data Structures & Algorithms using C and C++, C++, C
• Omkar Bindu, java, oop, dsa

• Date of birth: 04 Jun, 2004
• Gender: Male
• Marital status: Single

• Music
• Reading
• Watching Movies

Tech: Python, Deep Learning, ANN, GAN, YOLOv8, SHAP/LIME, Flask/FastAPI, MongoDB, React Native, Multilingual NLP

• Designed an end-to-end precision agriculture system derived from a conference research paper.
• Implemented GAN-based synthetic data generation for missing satellite/drone imagery.
• Built ANN yield-prediction models and YOLO pipelines for pest/disease detection.
• Integrated Explainable AI (SHAP/LIME) to provide transparency for farmers.
• Developed a mobile-first multilingual interface using React Native.
• Architected cloud-ready backend services using Flask/FastAPI and MongoDB.
• Analysed security threats (data poisoning, adversarial attacks) and mitigation strategies.
• Performed comparative evaluation across ANN, GAN, and YOLO models.

GitHub: github.com/omkarbindu/TopupLoan

• Built an end-to-end machine-learning system to predict customer top-up loan eligibility and amount.
• Performed exploratory data analysis and correlation studies to understand financial risk drivers.
• Engineered domain-specific features such as EMI-to-income ratio, repayment rate, loan-to-income ratio, monthly savings, and interest burden.
• Trained and tuned a Random Forest regressor achieving R² = 0.98 on test data.
• Implemented train–test splitting, regression metrics, and performance visualization.
• Serialized trained models using Joblib for production inference.
• Developed a Streamlit web interface with real-time prediction forms, sliders, and validation logic.
• Implemented consistent preprocessing and one-hot encoding during inference.
• Deployed the application publicly for interactive user testing

GitHub: github.com/omkarbindu/chat-bot

• Built a Retrieval-Augmented Generation system for querying uploaded PDF documents.
• Implemented parsing, chunking, embedding, and vector storage pipelines.
• Integrated semantic search to retrieve relevant document sections.
• Returned grounded answers with citations to original PDF pages.
• Engineered prompts to reduce hallucinations and improve reliability.
• Built a Streamlit UI for interactive document analysis.

• Developed a console-based hotel management application using Core Java and JDBC.
• Implemented secure login/logout and role-based workflows.
• Built modules for rooms, employees, and bookings.
• Designed normalized database schemas and enforced constraints.
• Implemented transactional CRUD operations.
• Applied OOP principles for modular system design.

• Built a machine-learning pipeline for early diabetes risk prediction.
• Cleaned and preprocessed clinical datasets and handled missing values.
• Applied feature scaling and normalization.
• Evaluated models using train–test split and cross-validation.

GitHub: github.com/omkarbindu/IPL-WINNING-TEAM-PREDICTION

• Predicted IPL match outcomes using historical performance data.
• Performed data cleaning and exploratory analysis.
• Engineered basic match-condition features.
• Evaluated performance using accuracy metrics.

prof.Sunayana Sutar, prof.Ashwini Dhumal, mr.Omkar Bindu, mr.Ankur Bhandare,mr. Yuvraj Ghare, mr.Pranav Takawale.
“Next-Gen Precision Farming Using Multimodal AI and Geospatial Intelligence.”
Submitted to International Conference on Advancement in Science, Engineering & Management (ICSEM) 2026.