research areas
Causal Inference & Discovery
Causal Inference & Discovery
Causal Inference & Discovery
- Causal Models-Using graphical models (DAGs)to map causality.
- Instrumental Variables(IV)-Estimating causal effects in non-randomized settings.
- Difference-in-Differences(DiD)-Evaluating policy impacts over time.
Intervention Experiments
Causal Inference & Discovery
Causal Inference & Discovery
- Randomized Controlled Trials(RCTs) - Gold standard for causal testing.
- A /B Tesing & Multi-Armed Bandits- Optimization in Business & AI.
- Reinforcement Learning (RL) for Causality-AI agents learning from interventions.
research areas
Counterfactual & Predictive Simulations
Counterfactual & Predictive Simulations
Counterfactual & Predictive Simulations
- AI-Driven Counterfactual Models - Testing alternative decision paths.
- Policy Scenario Simulations - Evaluating economic or healthcare policies before implementation.
Optimization & Decision Intelligence
Counterfactual & Predictive Simulations
Counterfactual & Predictive Simulations
- Bayesian Optimization for Decision-Making - Adaptive learning for optimal strategies.
- Automated Experimentation Systems - AI-Driven self-optimizing decision frameworks.