This seminar will explore the relationships between simulation modeling and causal modeling, focusing on the potential of these two research fields to enrich each other. From a simulation point of view, causal models could provide methods for enabling new kinds of tractable probabilistic reasoning about models, for learning models directly from data, and for learning high-level abstractions of a detailed mechanistic model.

This seminar will explore the relationships between simulation modeling and causal modeling, focusing on the potential of these two research fields to enrich each other. From a simulation point of view, causal models could provide methods for enabling new kinds of tractable probabilistic reasoning about models, for learning models directly from data, and for learning high-level abstractions of a detailed mechanistic model.

The deployment of foundation models in resource-constrained mobile and wearable devices presents unique challenges and opportunities, particularly in health and wearable sensing applications. This advanced seminar explores the cutting-edge intersection of large AI models, embedded systems, and digital health, with a focus on real-world applications in wearable and mobile biosignal sensing platforms.

The deployment of foundation models in resource-constrained mobile and wearable devices presents unique challenges and opportunities, particularly in health and wearable sensing applications. This advanced seminar explores the cutting-edge intersection of large AI models, embedded systems, and digital health, with a focus on real-world applications in wearable and mobile biosignal sensing platforms.

Artificial Intelligence will radically change education. Through machine learning, data mining, analytics, robotics, and user models, AI will replace false learning boundaries (e.g., learning places, time, level of study); personalize learning; make learning instantly available to everyone; connect learners with partners; provide multi-media; and augment human learning ability. This seminar examines recent work in explanatory and tutoring systems, presents theories about digital teaching and learning, and describes how to deliver personalized teaching in online systems.

This course is designed to provide computer scientists with a comprehensive introduction to the field of computational biology. The course will cover the application of computational techniques to modern research challenges in biology, discussing both foundational algorithms and newly introduced methods. The necessary background on biology will be provided in order to contextualize the methods.

This course will focus on modern machine learning approaches to learn from human demonstrations, preferences, feedback, and other multimodal signals, with the goal of aligning agent goals and behaviors with human values and desires. For the purposes of both safety and practicality, it is increasingly important for AI systems to be well-aligned with human users as their capabilities improve and they are deployed more frequently in real-world settings.

Computer science has played a pivotal role in developing innovative technologies to monitor patients' health conditions beyond the traditional laboratory or clinical environments. The development of clinically valid digital biomarkers can enable a wide range of applications, including the implementation of targeted behavioral interventions to drive substantial improvements in health-related outcomes, monitoring the progress of individuals undergoing interventions, and assessing the efficacy of emerging therapeutic interventions as an endpoint.

This course will provide an introduction to fundamental principles underlying quantum communication, including quantum repeaters, entanglement, and other tools needed for the implementation of distributed quantum protocols. Topics include: basics of quantum computation and information; modeling and coping with noise in quantum systems; entanglement generation schemes; quantum Internet and its applications. Meets with and is identical to 590QC, with the exception that students will carry out a research project involving a simulation of a quantum network.

This course provides an in-depth examination of the issues in system security, and assumes prior knowledge of operating system concepts. We will start with learning the classic approaches to security attacks and defenses from the perspective of a single host system. Topics include access control, information flow control, system auditing, privilege separation, security policies, host-based intrusion detection etc.