[Yaseen Khalil]|Computational Modeler & ML Systems Architect

> Conceptual AI agent gateway. Unified system interactions for Slack, Google Workspace, Square, and Sentry APIs.

> Efficiency-Fidelity benchmark comparing Semi-Tensor Product (STP) algebraic linearization (exact logic preservation) vs multivariate least-squares regression (scalable dynamics) for cancer signaling circuits. Implementing both linearizations against stochastic Boolean networks with pyMaBoSS, starting from gene-expression driven circuits to evaluate behavior under drug-like perturbations. Developing intervention scoring approaches, transitioning from rule-curated Boolean subnets (~50-200 nodes) toward larger PPI graph structures.

> Production-style Airflow 3 pipeline ingests partitioned Levin vehicle telemetry, normalizes fields into a canonical schema, and generates curated daily rollups. Enforced idempotent loads (safe reruns/backfills via unique event keys), dynamic task mapping for date-range backfills, and run-level artifacts for operational visibility. Data contract validations: schema/type/range checks (timestamp parseability, non-null vehicle IDs, plausible bounds for speed/RPM/temp) with quality stats per partition.

> End-to-end vehicle health neural network using bi-directional LSTM with attention; improved anomaly detection accuracy from 40-60% to 87-95% through iterative retraining on 30K+ telemetry points every 10 minutes. Three-tier anomaly detection: LSTM for sequential insights, DBSCAN for geographic hotspot clustering; 33% increase in predictive reliability across simulated fleets. FastAPI microservices on Railway with Supabase integration.