Smart Cities: Event Series
About
The DSI Smart Cities Center will convene a series of programs focused on the future of urban systems and the data science and AI-driven technologies shaping them. The center supports research that addresses the challenges of aging infrastructure while advancing innovations in smart grids, intelligent transportation systems, and networked sensing technologies that enable real-time monitoring and decision-making.
Through its event programming, the center will bring together researchers exploring how AI, machine learning, and emerging digital infrastructure can improve the resilience, efficiency, and sustainability of dense urban environments. Topics will span predictive maintenance, mobility optimization, energy distribution, urban analytics, and the evolving role of intelligent systems in shaping everyday city life.
Upcoming Event
Date: Tuesday, February 17, 2026 (12:00 PM – 1:00 PM)
Yinhai Wang, Thomas and Marilyn Nielsen Endowed Professor in Engineering, Director of PacTrans and STAR Lab, University of Washington
Talk information coming soon
Event Archive
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The Smart Cities Research Center hosted a delegation from Japan’s Ministry of Land, Infrastructure, Transport and Tourism (MLIT), along with representatives from the Mitsubishi Research Institute and International Access Corporation, for a research exchange on next-generation urban transportation technologies. The visit highlighted Columbia’s work on hybrid digital twins and the COSMOS testbed, while the delegation shared perspectives on related projects underway in Japan.
Columbia Presentations:
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- Remarks: Helen H. Lu, Professor of Biomedical Engineering; Professor of Dental and Craniofacial Engineering (in Dental Medicine); Senior Vice Dean of Faculty Affairs and Advancement
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- Remarks: Garud Iyengar, Avanessians Director of the Data Science Institute; Professor of Industrial Engineering and Operations Research
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- AI-Powered Urban Transportation Digital Twin: Xuan Sharon Di, Associate Professor of Civil Engineering and Engineering Mechanics; Co-Chair of Smart Cities Research Center
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- Center for Smart Street Scapes (CS3): Andrew Smyth, Professor of Civil Engineering and Engineering Mechanics
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- Learning the Earth with Artificial Intelligence and Physics (LEAP) Center: Tian Zheng, Professor of Statistics; Co-Chair of the Education Working Group; Deputy Director, Chief Convergence Officer & Education Director, LEAP
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Date of Talk: Thursday, December 4, 2025
Speaker: George Pechlivanoglou, Director General, Eunice Energy Group; and CEO and President, Joltie
Abstract: Europe’s energy transition has outpaced its digital transition. As renewable penetration rises and grid inertia vanishes, traditional models of forecasting and control collapse under the weight of nonlinear complexity. The European energy market, an intricate, data-rich ecosystem of zonal prices, balancing mechanisms, and infrastructural constraints, demands better data analytics.
This lecture presents a new frontier: the creation of a secure, full-scale digital twin of the European power system, capable of modeling the network itself. By unifying market dynamics with physics-based models of substations, transmission lines, and generation assets, the digital twin reconstructs and simulates the grid’s hidden state in near real time. This model extends beyond energy forecasting toward predictive energy economics and provides a framework to model not only how the grid behaves, but how it will behave under stress.
Modern grids face not only physical instability from renewables but systemic threats from cyberattacks, cascading failures, and coordinated disruptions. Within the digital twin, artificial damage simulations, including cyber-physical intrusion scenarios, enable testing of defense mechanisms, recovery strategies, and autonomous response models. By integrating telemetry, behavioral anomaly detection, and threat intelligence into the energy models, we can prototype techniques with broad applicability across the EU.
Eunice Energy Group provides a unique empirical base for this study by acting as an operational and asset-level data across the Mediterranean’s most dynamic and vulnerable systems. Greece stands as a living laboratory ideal for this type of study: a semi-isolated grid, high in renewable volatility, where resilience and cybersecurity are operational necessities.
The challenge to the data science community is to design the intelligence layer of Europe’s next-generation energy infrastructure through analysis and integration of modalities that have never been combined before with far-reaching individual benefit. Through causal inference, graph neural networks, hybrid AI–physics modeling, and adversarial resilience simulation, data previously restricted to an energy company’s internal frameworks can be unique opportunities for data scientists interested in green energy and climate change.