About Workshop
A 3-day hands-on workshop on applying AI and optimization to sustainability challenges — automate Scope 1-3 carbon accounting, model circular material flows, and generate optimal decarbonization strategies. Combines core concepts with guided Colab labs using industry-standard open-source tools.
Aim
To build practical skills in using machine learning and optimization algorithms to measure, model, and reduce carbon footprints across supply chains and industrial systems.
What Participants Will Learn
- Automate Scope 1, 2, and 3 GHG emissions tracking with ML
- Predict missing emission factors and forecast dynamic carbon intensity
- Model circular supply chains using graph-based Material Flow Analysis
- Apply ML for waste sorting, decomposition, and end-of-life routing
- Quantify Material Circularity Indicators and embodied carbon savings
- Build multi-objective optimization models for net-zero roadmaps
- Apply reinforcement learning to industrial energy efficiency
Structure
📅 Day 1: AI-Driven Carbon Accounting & Life Cycle Assessment (LCA)
Core Objective: Automate Scope 1-3 emissions tracking and Life Cycle Assessment using machine learning.- Machine learning for automated Scope 1, 2, and 3 GHG emissions mapping
- Predicting missing supply chain emission factors with regression models
- Dynamic carbon intensity forecasting based on real-time grid data
📅 Day 2: Predictive Material Flow Analysis & Circular Economy Design
Core Objective: Model closed-loop recycling networks and track resource flows using graph algorithms.- Graph-based Material Flow Analysis (MFA) to track raw and waste material lifecycles
- Machine learning for waste sorting, material decomposition, and end-of-life routing
- Quantifying Material Circularity Indicators (MCI) and embodied carbon savings
📅 Day 3: Generative System Optimization & Decarbonization Roadmaps
Core Objective: Generate optimal net-zero strategy pathways using multi-objective optimization algorithms.- Multi-objective optimization balancing operational cost, resource depletion, and carbon ROI
- Reinforcement learning for industrial energy efficiency and byproduct exchange
- Automated scenario analysis for climate risk reporting and ESG compliance
Important Dates
Registration Ends
4:30 PM
Workshop Dates
2026-08-14
5:30 PM
5:30 PM
What You Will Gain
Outcomes
Participants will be able to:
- Build a Python pipeline to track live compute emissions and run Scope 3 LCA models
- Map circular supply chains and calculate circularity scores using NetworkX
- Build a Pyomo optimization model for lowest-cost decarbonization strategy
- Generate automated scenario analyses for ESG/climate risk reporting
- Walk away with reusable Colab notebooks for carbon and circularity modeling
Who Should Attend
- Sustainability/ESG analysts and consultants
- Supply chain and operations professionals
- Data scientists/ML engineers entering climate tech
- Environmental engineers and LCA practitioners
- Corporate sustainability and net-zero strategy teams