I am an AI/ML and data science professional with experience across machine learning, deep learning, Generative AI, data analytics, data engineering, cloud platforms, and automation.
My work and portfolio include predictive modeling, NLP, computer vision, forecasting, anomaly detection, RAG systems, AI agents, real-time data pipelines, and analytics workflows. I enjoy building practical AI and data solutions that transform complex information into reliable models, intelligent applications, and useful business insights.
Primary focus: AI/ML Engineering • Data Science • Applied AI • Generative AI
- Build machine learning and deep learning solutions for forecasting, classification, NLP, anomaly detection, and computer vision
- Develop Generative AI, RAG, and agentic applications using LangChain, LangGraph, embeddings, and vector databases
- Prepare, analyze, and validate structured and unstructured data for modeling and decision support
- Design predictive workflows using Python, SQL, Scikit-learn, PyTorch, TensorFlow, and XGBoost
- Build data pipelines using Airflow, Spark, Kafka, cloud services, and analytics databases
- Communicate model results through dashboards, reports, explainability methods, and practical recommendations
| Area | Summary |
|---|---|
| AI/ML Engineering | Built machine learning, deep learning, NLP, computer vision, forecasting, and optimization solutions |
| Data Science | Worked with data preparation, feature engineering, statistical analysis, model evaluation, and predictive analytics |
| Generative AI | Developed RAG systems, semantic-search applications, agentic workflows, and AI-assisted automation |
| Data Engineering | Built ETL pipelines, streaming workflows, orchestration systems, and analytics-ready data platforms |
| Cloud & MLOps | Worked with cloud platforms, Docker, model deployment, workflow automation, monitoring, and scalable processing |
| Analytics | Created dashboards, reports, SQL analyses, and decision-support outputs for practical use cases |
End-to-end Formula 1 analytics and race prediction platform using PostgreSQL, dbt, XGBoost, Airflow, Docker, and BI dashboards.
PythonSQLPostgreSQLdbtAirflowXGBoostDockerBI
Real-time streaming pipeline using Kafka, Spark Structured Streaming, MongoDB, Docker, and Python to process IoT air-quality data and generate low-latency alerts.
KafkaSpark Structured StreamingMongoDBPythonDockerBig Data
Production-style analytics warehouse using Python ETL, PostgreSQL, star schema modeling, SQL analytics, and Tableau dashboards.
PythonPostgreSQLETLData WarehouseStar SchemaTableau
Applied AI system combining Temporal Fusion Transformer forecasting and PPO reinforcement learning for demand prediction and pricing optimization.
PyTorchTime-Series ForecastingTFTPPOReinforcement Learning
Full-stack document intelligence platform using FastAPI, React, vector search, embeddings, and RAG for semantic document Q&A.
FastAPIReactRAGVector SearchEmbeddingsSemantic Search
PostgreSQL optimization project using indexing, partitioning, EXPLAIN ANALYZE, Docker, and SQL tuning, achieving up to 96% query performance improvement.
PostgreSQLSQL OptimizationIndexingPartitioningDocker
| Project | What It Demonstrates | Stack |
|---|---|---|
| rag-document-intelligence-platform | Document intelligence and RAG | FastAPI, React, Vector Search |
| agentic-research-workflow-platform | Multi-agent research orchestration | LangGraph, FastAPI, React, Ollama |
| context-aware-browser-assistant | Privacy-first browser AI assistant | React, TypeScript, Chrome Extension, Ollama |
| multimodal-audio-generation-platform | Text-to-audio generation optimization | AudioLDM, CLAP, PyTorch |
| autonomous-ai-code-repair-platform | AI-powered code repair and validation | LangGraph, Docker, GitHub API, pytest |
| Project | What It Demonstrates | Stack |
|---|---|---|
| ai-retail-demand-forecasting-dynamic-pricing | Forecasting and decision optimization | TFT, PPO, PyTorch |
| ecg-anomaly-detection-vae | Unsupervised anomaly detection | VAE, PyTorch, ROC-AUC, t-SNE |
| sign-language-recognition-cnn | Computer vision classification | CNN, PyTorch |
| fake-news-detection-ml | NLP text classification | TF-IDF, SVM, Logistic Regression |
| obesity-classification-ml | Traditional ML classification | SVM, Decision Tree, Random Forest |
| advertising-campaign-analysis | A/B testing and regression analysis | R, Statistics, Regression |
| mental-health-risk-prediction-system | ML risk-screening API workflow | XGBoost, Flask, Docker, Scikit-learn |
| ai-generated-text-detection-system | NLP-based AI text detection | BERT Embeddings, Streamlit, Similarity Scoring |
| Project | What It Demonstrates | Stack |
|---|---|---|
| formula1-predictive-analytics-platform | Predictive analytics pipeline and BI workflow | PostgreSQL, dbt, XGBoost, Airflow, Docker |
| real-time-iot-air-quality-pipeline | Real-time streaming and IoT analytics | Kafka, Spark, MongoDB, Docker |
| movielens-data-warehouse | Data warehousing and dimensional modeling | Python, PostgreSQL, SQL, Tableau |
| streamflix-db-performance-optimization | SQL tuning and database optimization | PostgreSQL, Indexing, Partitioning, Docker |
| hadoop-ecommerce-analytics | Distributed batch analytics | Hadoop, HDFS, YARN, MRJob, Python |
| fleet-telemetry-mongodb-platform | NoSQL IoT data modeling | MongoDB, Aggregation, Indexing |
| fleet-telemetry-cassandra-platform | Distributed NoSQL design | Cassandra, CQL, Docker |
| multi-region-fleet-iot-database-architecture | Multi-region distributed database architecture | CockroachDB, Docker, Python, SQL |
| Project | What It Demonstrates | Stack |
|---|---|---|
| air-pollution-life-expectancy-analysis | Public-health analytics and storytelling | Tableau, EDA, Global Health Data |
| advertising-campaign-analysis | Marketing analytics and experimentation | R, A/B Testing, Regression |
| movielens-data-warehouse | BI dashboarding on warehouse data | Tableau, SQL, PostgreSQL |
- M.S. in Artificial Intelligence and Business Analytics — University of South Florida
- Professional background across AI, machine learning, data science, analytics, automation, and cloud-based workflows
- Portfolio experience spanning predictive modeling, deep learning, Generative AI, RAG, data engineering, and intelligent systems
AI/ML EngineeringData ScienceApplied AIGenerative AIMachine LearningData Engineering