Apoorv Mathur

Apoorv Mathur

Product Manager
Siemens Grid Software

Bio

Apoorv Mathur leads product management for Next Generation Siemens Grid Software in North America, aiming to help utilities navigate the challenges of achieving a clean energy future and speed to power for AI.

At Siemens, Apoorv leads the development of Gridscale X DER and LV Insights, combining next-generation, data-driven AI/ML software and cloud scalability with established Siemens grid simulation and power flow capabilities. This software aims to help utilities integrate renewables, DERs, EVs, and data center loads into the grid while ensuring power reliability and affordability.

Apoorv has built expertise in the areas of Energy markets, optimization, cloud, AI and ML software strategy and product development across utilities (Tata Power, PSEG), power exchanges (Power Exchange of India), and technology companies (such as Amazon, AWS and Siemens) over a period of 20 years. He holds a Master of Business Administration from INSEAD, a Master of Science in Operations Research from North Carolina State University and a Bachelor of Technology in Engineering from IIT Delhi.

Decision Intelligence in Power Systems - combining OR, Analytics and AI to balance complex real-time electricity supply chains at scale

Decision intelligence brings together data, models, and algorithms to support timely and reliable goal-based decisions under real‑world constraints. Few domains illustrate this challenge more clearly than electric power systems—among the largest and most complex engineered systems ever built.

Today’s electricity grid is undergoing a fundamental shift. Traditional centralized optimization is giving way to highly distributed, self‑optimizing operations driven by renewable generation, distributed energy resources (DERs), and increasingly volatile supply and demand. Grid operators must continuously balance a real‑time electricity supply chain, making millions of high‑stakes decisions under tight latency, accuracy, and reliability requirements.

In this talk, we present a systems‑level view of how decision intelligence is applied in large‑scale power system operations. We show how forecasting, simulation, optimization, machine learning, and AI are combined to model grid behavior, anticipate uncertainty, and recommend actionable decisions—often within seconds.

We demonstrate how trade‑offs between accuracy, robustness, interpretability, and computational speed shape a real‑world solution design. We illustrate these ideas using examples from modern grid operations software, including Siemens Gridscale X, which supports operational decision‑making for power systems at scale.

We conclude by highlighting research and implementation challenges—such as integrating advanced AI with optimization, managing uncertainty, and ensuring user trust—and discuss what it takes to translate state‑of‑the‑art analytics into dependable, real‑time decision support in mission‑critical systems.

Essential / Professional / Leadership