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ASSET Seminar: “Efficient and Targeted COVID-19 Border Testing Via Reinforcement Learning” (Hamsa Bastani, Penn)

Levine 307 3330 Walnut Street, Philadelphia, PA, United States

ABSTRACT:  Throughout the COVID-19 pandemic, countries relied on a variety of ad-hoc border control protocols to allow for non-essential travel while safeguarding public health: from quarantining all travellers to restricting entry from select nations based on population-level epidemiological metrics such as cases, deaths or testing positivity rates. Here we report the design and performance of […]

ASSET Seminar: “The Road to Explainable AI v2.0” (Eric Wong, Penn)

Levine 307 3330 Walnut Street, Philadelphia, PA, United States

ABSTRACT: "A.I. has an explainability crisis"---Fortune Magazine. If you ask an ML researcher about explainability, you'll find that there are a large number of interpretability methods with no clear consensus on what to use. In fact, it isn't clear what many of these explanations even mean, let alone how they can be used. I will […]

ASSET Seminar: “Safety through Agility – Safe and Performant Control for Learning-Enabled Autonomous Systems” (Mangharam, Penn)

Levine 307 3330 Walnut Street, Philadelphia, PA, United States

ABSTRACT: We present three approaches to combine formal methods, control theory, and machine learning for safe and performant autonomous systems.  Safe control for learning-enabled systems: We present our recent progress on how to learn safe adaptive behavior for highly interactive multi-agent systems. We will introduce how to quantify the uncertainty of closed-loop control systems using […]

ASSET Seminar: “Getting Computers to Do What We Want: Programming Meets Machine Learning” (Michael Littman, Brown University)

Raisler Lounge (Room 225), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

ABSTRACT: It is immensely empowering to delegate information processing and automation work to machines and have them carry out difficult tasks on our behalf. But programming computers is hard. The traditional approach to this problem is to try to fix people: They should work harder to learn to code. In this talk, I argue that […]

ASSET/IBI Symposium on Trustworthy AI for Health Care

Glandt Forum, Singh Center for Nanotechnology 3205 Walnut Street, Philadelphia, PA, United States

Organizers: Rajeev Alur (Penn Engineering), John Holmes (PSOM), Insup Lee (Penn Engineering), Qi Long (PSOM), Marylyn Richie (PSOM) Event Description: Artificial intelligence and machine learning promise to revolutionize nearly every field, sifting through massive amounts of data to find insights that humans would miss, making faster and more accurate decisions and predictions as a result. Applying […]

ASSET Seminar: “Towards Code-Aware Code Models” (Baishakhi Ray, Columbia University)

Levine 307 3330 Walnut Street, Philadelphia, PA, United States

ABSTRACT: The past decade has seen unprecedented growth in Software Engineering— developers spend enormous time and effort to create new products. With such enormous growth comes the responsibility of producing and maintaining quality and robust software. In this talk, I will discuss how AI can help develop quality products in different stages of the software […]

ASSET Seminar: “Lifelong Learning for Autonomous Systems: Progress and Challenges” (Eric Eaton, Penn)

Levine 307 3330 Walnut Street, Philadelphia, PA, United States

ABSTRACT:  Research in lifelong or continual machine learning has advanced rapidly over the past few years, primarily focusing on enabling learned models to acquire new tasks over time while avoiding catastrophic forgetting of previous tasks. However, autonomous systems still lack the ability to rapidly learn new generalizable skills by building upon and continually refining their […]

ASSET Seminar: “Towards a Design Flow for Verified AI-Based Autonomy” (Sajit A. Seshia, University of California, Berkeley)

Levine 307 3330 Walnut Street, Philadelphia, PA, United States

ABSTRACT: Verified artificial intelligence (AI) is the goal of designing AI-based systems that have strong, ideally provable, assurances of correctness with respect to formally specified requirements. This talk will review the main challenges to achieving Verified AI, and the initial progress the research community has made towards this goal. A particular focus will be on […]

CIS Seminar: “Modeling Atoms to Address Our Climate Crisis”

Wu and Chen Auditorium (Room 101), Levine Hall 3330 Walnut Street, Philadelphia, PA, United States

Climate change is a societal and political problem whose impact could be mitigated by technology. Underlying many of its technical challenges is a surprisingly simple yet challenging problem; modeling the interaction of atoms. In this talk, we motivate the problem and provide insights into how this opens up new intriguing directions for machine learning and […]

ASSET Seminar: “Copyright, Machine Learning Research, and the Generative-AI Supply Chain” (A. Feder Cooper, Cornell University)

Levine 307 3330 Walnut Street, Philadelphia, PA, United States

ABSTRACT: “Does generative AI infringe copyright?” is an urgent question. It is also a difficult question, for two reasons. First, “generative AI” is not just one product from one company. It is a catch-all name for a massive ecosystem of loosely related technologies. These systems behave differently and raise different legal issues. Second, copyright law […]