Causality & Counterfactuals – Role in IoT Digital Twin

Session Abstract:

This talk presents (1) causality, (2) its role in IoT, (3) algorithms for causal structure and causal factor estimation, (4) how to use causal graph simulation for counterfactual experiments, (5) what is a digital twin and (6) why causal graph is an ideal data-driven digital twin.


PG Madhavan
Advisor at

Dr. PG Madhavan has extensive background in IoT, Machine Learning, Digital Twin and Wireless technologies in roles such as Chief IoT Officer, Chief Acceleration Officer, IoT startup Founder, . . . IoT Product Manager at large corporations (Rockwell Automation, GE Aviation, NEC, . . .) and small firms (multiple startups and two own startups).

After obtaining his Ph.D. in Electrical and Computer Engineering from McMaster University, Canada, and Masters in Biomedical Engineering from IIT, Madras, Dr. Madhavan pursued original research in Random Field Theory and Computational Neuroscience as a professor at the University of Michigan, Ann Arbor, and Waterloo University, Canada, among others. His next career in corporate technology saw him assume product leadership roles at Microsoft, Bell Labs, Rockwell Automation, GE Aviation and lastly at NEC. PG has founded and was CEO at 2 startups (and CTO at 2 others) leading all aspects of startup life.

Currently, he champions digital twins as the seat of AI/ML for IoT applications with an emphasis on Causality.

Session Tags

Government, Enterprise, Small / Medium Enterprise, OEM

IoT, Causality, Simulation, Digitaltwin, Fencegraph

VP / Director, Technical


Manufacturing, Telecom, Industrials, Healthcare, Government / Public Sector, Automotive

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