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AI-Powered Life Cycle Assessment Dashboards is an interdisciplinary international workshop that combines environmental sustainability, data science, and machine learning to create intelligent dashboards for life cycle-based analysis.
Participants will learn the fundamentals of LCA methodology, explore environmental impact datasets (ecoinvent, OpenLCA), and build dashboards powered by AI/ML models to automate material flow assessments, carbon footprint predictions, waste mapping, and more. Using tools such as Python, Streamlit, Power BI, Tableau, and scikit-learn, the workshop provides a hands-on experience in creating responsive, scalable, and actionable LCA visualizations.
To equip participants with the technical and analytical skills needed to design and deploy AI-enhanced Life Cycle Assessment (LCA) dashboards, enabling data-driven sustainability insights across product systems, industrial processes, and environmental management.
Bridge sustainability science and intelligent analytics
Train participants to build digital decision-making tools for green innovation
Enable prediction and visualization of environmental impact across a productβs lifecycle
Promote data transparency and traceability in sustainability reporting
Inspire innovation in smart tools for circular economy planning
PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.
Professional Certification Program
Introduction to LCA: Purpose and Global Relevance
Phases of LCA: Goal & Scope, Inventory, Impact Assessment, Interpretation
Standards and frameworks: ISO 14040/44, GHG Protocol
Types of LCA: Attributional vs. Consequential
Environmental impact categories: GWP, eutrophication, toxicity, etc.
Data collection challenges and quality indicators
Overview of LCA software tools: OpenLCA, SimaPro, Brightway2
Role of AI/ML in improving LCA workflows
Predictive modeling for life cycle inventory (LCI) data gaps
Clustering and classification for material/process grouping
AI-assisted scenario analysis and sensitivity checks
Feature engineering from supply chain and sensor data
Case examples: AI-enabled rapid LCA for products (e.g., packaging, electronics)
Ethical and interpretability considerations for AI in environmental decision-making
Introduction to data dashboards: role in decision-making and reporting
Tools overview: Power BI, Tableau, Dash (Plotly), Streamlit
Connecting LCA datasets to visualization tools (CSV, APIs, JSON formats)
Designing interactive dashboards: filters, metrics, maps
Custom KPIs: carbon footprint, water usage, toxicity index
Automating LCA reports using AI and dashboard frameworks
Hands-on case: Building a real-time AI-powered LCA dashboard prototype
Sustainability professionals and environmental consultants
Engineers and product designers in manufacturing, energy, and construction
AI/ML practitioners interested in sustainability applications
Researchers in environmental science, LCA, and circular economy
Data analysts and ESG officers
02/02/2026
IST 04: 00 PM
02/02/2026 β 02/04/2026
IST 05:30 PM
Gain working knowledge of LCA frameworks and best practices
Automate LCA workflows using AI and ML
Design dashboards for environmental performance monitoring
Translate complex data into clear, actionable sustainability metrics
Receive international certification in AI-enabled LCA systems
βΉ2499 | $70
βΉ3498 | $80
βΉ4499 | $90
βΉ6499 | $110
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