Neuro-Symbolic-Causal AI - Project Chimera | 🌌 An open research project exploring formal verification of AI agent decisions, combining symbolic reasoning, causal inference, and runtime policy enforcement.
Cusal Inference applied to timeseries, uses an event database to generate a timeseries of the outcome given a sliding window containing events. Useful to add causal outcomes of events into multivariate timeseries forecasting models.
DeepEcon: Your one-stop Python package for econometric algorithms.
DoWhy/EconML toolkit for visualizing causal paths and estimating treatment effects
A complete end-to-end AI experimentation & causal inference project using A/B testing, X-Learner, CATE estimation, and uplift segmentation on 1.5M+ synthetic SaaS behavioral records. Includes statistical analysis, causal ML workflow, uplift modeling, feature importance, and business-ready insights for AI feature rollout & monetization.
Internship Project on Causal Inference (The causal effect of multi-level treatment of intervention using observational data).
Causal analysis to predict factors affecting employee resignation using the Causal Inference method on company datasets.
Causal inference project using the MineThatData E-Mail Analytics dataset. Implements logistic regression and DRLearner to estimate the causal effect of marketing emails on customer conversion. Includes CATE/ATE estimation, hypothesis testing and bootstrapping.
estimate CATE and deploy uplift‑based targeting models that replace or augment traditional A/B testing.
Causal ML pipeline for e-commerce dynamic pricing — Double Machine Learning for unbiased price elasticity, LightGBM demand forecasting (MAPE=0.418, R²=0.055), and a FastAPI pricing service delivering +30% revenue lift across 49,677 SKUs from 32M+ transactions.
Causal inference analysis of ICU beta-blocker treatment effects using propensity matching, IPW, doubly robust estimation, Double ML, and Causal Forest on eICU data
Causal analysis framework using Double Machine Learning to quantitatively isolate the effect of model size on deep learning performance while controlling for confounders such as dataset size, training time, and hyperparameters.
Business strategy simulation dashboard using A/B testing and Causal Inference
Deprecated — merged into insurance-causal
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