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πŸš€ Bhavani Shankar Ajith

AI/ML Engineer Β· Software Engineer β€” MS Data Science, Stony Brook University '26

About Me

  • I build AI and ML systems that actually run β€” retrieval and agent pipelines, models with calibrated uncertainty, and the data platforms underneath them.
  • Backend engineer by training, so the models ship: FastAPI/Spring Boot services, Postgres and vector stores, Docker, CI, and integration tests around the whole thing.
  • Shipped production enrollment APIs and database workflows powering ARBenefits portal processes for 184K+ covered employees, cutting enrollment processing time by 40%.
  • MS in Data Science from Stony Brook University. Project work spans LLM/RAG systems, reinforcement learning, experimentation and forecasting, and cloud data pipelines.

Skill stack

ML / AI ML skills

Systems & Platform Platform skills

Also comfortable with: RAG/LLM tooling (Qdrant, ChromaDB, Ollama, sentence-transformers), experimentation and causal analysis (power, bootstrap CIs, guardrail metrics), DuckDB/BigQuery analytics engineering, Pandas/NumPy workflows, Testcontainers-backed integration testing.


Projects β€” showcase

One flagship from each of the four areas I work in.

PaperTrail Project
PaperTrail
Research-paper assistant that connects methods and concepts across papers β€” search by ideas, not keywords.
πŸ”— Repo
AI & LLM Systems Β· RAG, Knowledge Graphs
Geometry Dash RL Project
Geometry Dash RL
DQN vs PPO vs genetic algorithms, trained in a 4000Γ—-real-time headless sim and evaluated in the real game.
πŸ”— Repo
ML & Modeling Β· RL, PyTorch
A/B Experiment Analysis Project
A/B Experiment Analysis
Pre-registered power analysis through guardrails, segment lifts and a ship/hold decision β€” validated against known ground truth.
πŸ”— Repo
Data Science Β· Experimentation, Inference
SMB Growth Intelligence Project
SMB Growth Intelligence
GA4 events β†’ layered ETL β†’ point-in-time feature store β†’ propensity model β†’ data-quality engine. Local DuckDB, portable to BigQuery.
πŸ”— Repo
Data & Platform Β· Analytics Engineering

More projects

Area Project What it does
AI & LLM Systems intelligent-doc-rag Self-hosted RAG over your documents β€” Spring Boot, Qdrant, Ollama. Grounded answers with enforced citations and multi-tenant vector isolation.
AI & LLM Systems forensic-llm-wiki-obsidian Markdown-first forensic investigation wiki that compiles raw evidence into evolving hypotheses, contradictions and reports.
ML & Modeling Robust Image Classification MC-Dropout uncertainty with a "tri-gate" abstention policy β€” entropy and mutual information calibrated on SVHN for out-of-distribution rejection.
Data Science forecasting-baselines Leakage-safe walk-forward benchmark of naive/MA/Ridge/XGBoost/LSTM on real market data. Reports the honest result: the random walk is not beaten.
Data & Platform devops-platform-lab Terraform + Kubernetes + Helm + GitHub Actions CI/CD with Prometheus/Grafana observability on a local kind cluster.
Data & Platform MarketPulse Β· Uber Analytics Β· Azure E2E Streaming and batch pipelines across Kafka, GCP/BigQuery/Looker, and Azure Data Factory/Databricks/Synapse.

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