Master's in Computer Science graduate from University of Ottawa specializing in AI/ML, Data Analytics, and Data Engineering. Building intelligent systems that deliver actionable business intelligence and drive strategic growth.
Passionate about leveraging artificial intelligence and data science to create impactful solutions
Hi! I'm Pranav Pawar, a recent graduate with a Master's in Computer Science from the University of Ottawa (CGPA: 3.9/4.0) and a Bachelor's in Computer Engineering with Honors in Data Science (CGPA: 9.13/10). With over 2 years of hands-on experience, I specialize in AI/ML engineering and data analytics.
I recently worked as an AI Researcher at the University of Ottawa, I've led the development of a real-time fish behavior prediction system using CNNs and computer vision, improving detection accuracy by 25%. My work leverages GPU-accelerated CUDA to optimize model training time by 40%.
I'm skilled in integrating complex datasets, designing performance-driven KPIs, and developing interactive dashboards using tools like Power BI, Python, SQL, and AWS. My experience spans across healthcare, logistics, automotive, and academic research sectors. I'm passionate about building scalable data pipelines and deploying AI models that drive measurable business value.
A comprehensive toolkit for building intelligent, data-driven solutions
A showcase of my AI/ML and data science projects
Built a multi-agent AI system with a LangGraph supervisor that classifies queries and routes them to specialized SQL, RAG, Hybrid, or General agents. Features a hallucination-proof citation verification layer that cross-validates every source before displaying it. Includes a Gradio UI, ChromaDB vector store, MCP server for external integrations, and a full PDF ingestion pipeline.
Built production vision-language pipeline orchestrating BLIP-2, YOLOv8, and Claude for automated product descriptions, achieving 10x cost reduction ($0.007/image), 4.2/5 quality, 89% detection accuracy, and 2s processing with FastAPI backend.
Architected production RAG system processing multi-format documents with intelligent semantic chunking and OpenAI embeddings, achieving 85%+ answer accuracy and 90%+ retrieval precision with sub-3-second latency.
Investigated 100K banking and insurance records using SQL, Power BI, and DAX to build a KPI-driven fraud monitoring dashboard, reducing investigation turnaround time by 40%.
Launched a Python and Power BI dashboard analyzing 55,500+ hospital records, improving operational efficiency and clinical decision-making by 30% through actionable insights.
Developed a machine learning system that accurately predicts dyslexia achieving 91% accuracy. Worked with ophthalmologists and dyslexia doctors to validate findings.
Engineered a scalable forecasting pipeline using Airflow, PySpark, MLflow, and Docker to orchestrate ETL, model training, and deployment, improving accuracy by 20%.
Executed market basket analysis on 3 million transactions using Python and the Apriori algorithm, surfacing 25 actionable product bundles to boost cross-sell potential.
Analyzed over 100K+ records on Google Cloud of employee movements and HVAC sensor data using BigQuery, Data Studio, and GIS, detecting anomalies that drove a 20% decrease in operational inefficiencies.
Assembled a Spark-based ETL pipeline and Looker dashboards across 150 hospitals, enabling centralized reporting on staff, supplies, and patient load; reduced manual reporting time by 60%.
Engineered a cloud-native data pipeline using Azure Data Factory, Synapse, and Databricks to process 50K F1 lap records, reducing telemetry analysis time by 35% for circuit-level race optimization.
My professional journey in AI, data science, and engineering
Leading development of real-time fish behavior prediction system using CNNs and computer vision, improving detection accuracy by 25%. Leveraging GPU-accelerated CUDA to reduce model training time by 40%. Built custom tracking algorithm achieving 98% fish identification accuracy.
Automated test case and requirement analysis by building Python scripts to process 1,200+ test cases, saving 10+ hours/week. Developed real-time reporting dashboards achieving 78% faster analysis and boosting test coverage by 92%.
CGPA: 3.9/4.0 | Teaching Assistant for 1 year 8 months | Winner at Design Day 2024 | Focused on AI/ML, Deep Learning, and Data Science applications.
Developed and deployed ML models for IoT-based healthcare applications achieving 92% accuracy and reducing false positives by 30%. Built secure RESTful APIs and automated data pipelines, enhancing processing efficiency by 60%.
Automated relay inventory management using Python, reducing manual errors by 50%. Executed 800+ relay tests, identifying and resolving key system issues to ensure optimal performance.
CGPA: 9.13/10 | Head of the Department of Computer Science | Specialized in Data Science, Machine Learning, and Computer Vision.
Interested in collaborating? Let's discuss your next AI/ML project