Deterministic and Stochastic Dynamic Programs for optimization of Supply Chain

Creating Supply & Demand during tough times of lockdown caused by COVID-19

A spare engine placement generator based on a Finite-Horizon Markov Decision Process

Multi-model time-series forecasting with Bayesian Optimisation (Optuna TPE): SARIMA, Random Forest, XGBoost, LightGBM, Prophet, LSTM, and QuantileML probabilistic forecasts behind a unified ModelSpec protocol. Walk-forward validated; supports monthly, weekly, daily, and hourly data.

Stochastic model to predict event probability and forecast store demand using Python

Product demand cannibalization model for new product launch impact

GenAI demand planner v2 with multimodal data fusion

Demand shaping through pricing and promotion optimization

Top-down demand disaggregation from aggregate forecast to SKU-location level

Demand forecasting models for supply chain and inventory planning

Supply chain scenario planning tool with what-if analysis capabilities

Warehouse wave planning order release

Demand orchestration platform unifying S&OP with execution

AI demand sensing tower with multi-horizon planning

Forecasting weekly product demand using ARIMA, SARIMAX, and regression models. Built with Microsoft Fabric Lakehouse architecture to improve stock management and minimize stockouts.

Near-term demand sensing ML external signals

Multi-method demand forecasting toolkit using ARIMA, Prophet, LSTM, and XGBoost for supply chain planning with automated model selection and accuracy benchmarking

End-to-end supply chain analysis using SQL and Excel — uncovering delivery performance, fulfilment efficiency, product profitability and order priority insights across 2,500 orders.

AI demand orchestrator for unified demand planning across channels

The complete guide to demand forecasting - from moving averages to transformers