I design transparent, data-driven systems that connect analytical precision with human-centered understanding, from research prototypes to production ML.
Bridging classical machine learning, generative AI, and cloud-native systems to deliver explainable, production-ready intelligence.
Regression • Classification • Clustering • Feature Engineering • Explainability • Optimization
LLMs • RAG • LangChain • Hugging Face • Prompt Engineering • Multi-Agent Systems
Azure ML • GCP • Docker • CI/CD • Deployment • API Integration • DevOps Pipelines
PySpark • SQL • ETL Pipelines • Power BI • Tableau • Matplotlib • Plotly
Red-teaming • Bias Analysis • Fairness Metrics • Explainability • Responsible AI
AI Ethics • Computational Neuroscience • Healthcare AI • Journal & Conference Papers
Open to research collaborations, applied ML, and data science roles.