seminars
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Aligning Machine Learning with Society
Machine Learning (ML) systems are increasingly integrated into society, but challenges arise when human incentives and expectations are overlooked. In this talk, I will present frameworks for aligning ML with society, focusing on strategic classification and personalization in decision making. Strategic classification models scenarios where individuals, aware of the deployed classifier, manipulate their observable attributes… Continue Reading Aligning Machine Learning with Society
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Aligning Machine Learning with Society
Abstract: Machine Learning (ML) systems are increasingly integrated into society, but challenges arise when human incentives and expectations are overlooked. In this talk, I will present frameworks for aligning ML with society, focusing on strategic classification and personalization in decision-making. Strategic classification models scenarios where individuals, aware of the deployed classifier, manipulate their observable attributes… Continue Reading Aligning Machine Learning with Society
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Robust and Actionable ML via Causality
Abstract: Artificial Intelligence is increasingly deployed in high-stakes fields such as healthcare, where two critical challenges emerge: models must generalize to real-world variations and their predictions must be actionable for decision-makers. The generalization challenge arises when AI is applied to data that differs from its training set, a phenomenon known as distribution shift. The actionability challenge… Continue Reading Robust and Actionable ML via Causality
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Robust and Actionable ML via Causality
Abstract: Artificial Intelligence is increasingly deployed in high-stakes fields such as healthcare, where two critical challenges emerge: models must generalize to real-world variations and their predictions must be actionable for decision-makers. The generalization challenge arises when AI is applied to data that differs from its training set, a phenomenon known as distribution shift. The actionability challenge… Continue Reading Robust and Actionable ML via Causality
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Optimizing Dynamic Systems: From Effective and Equitable Distribution to Coordinated Two-Stage Order Fulfillment
Abstract: Dynamic decision-making under uncertainty is a central challenge in several domains such as logistics, warehousing, and production systems. This talk introduces hybrid operations research (OR) and machine learning (ML) methodologies designed to optimize stochastic dynamic combinatorial problems. The first part of the talk focuses on making real-time routing and resource allocation decisions, ensuring effective and equitable distribution in uncertain… Continue Reading Optimizing Dynamic Systems: From Effective and Equitable Distribution to Coordinated Two-Stage Order Fulfillment
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Algorithms for Structured Simple Bilevel Problems
Abstract: Simple convex bilevel optimization problems, in which we seek to minimize an (outer) objective function over a feasible set, which itself is the set of minimizers of another (inner) function. Such problems can be found in the machine learning and signal processing applications. In this work, we address the case where both outer and… Continue Reading Algorithms for Structured Simple Bilevel Problems
labs
tracks
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Data Science
In an era where information is created at a dizzying pace and changes constantly and decisions require the creation of in-depth analysis, the ability to make sense of large quantities of data is a necessary and sought-after power. A master’s degree in Data Science offers tools and knowledge that will enable you to face the great challenges of the 21st century in all areas of life: medicine, social media, finance, urban planning, smart cities and more. Continue Reading Data Science
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Information Management Engineering
Ongoing developments in information technologies are enabling the creation of information systems in a variety of fields, with an ever-increasing scale and sophistication. At the same time, users’ demands from information systems are also growing. Information system engineers are required to develop applications and products whose complexity and intricacy are constantly increasing. These systems utilize the latest technologies such as communication and distributed systems, command and control using artificial intelligence, data organization and retrieval, organizational resource management systems, e-commerce systems, integrated hardware and software systems and decision support systems. Continue Reading Information Management Engineering
