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ASSET Seminar: Building Safe Autonomous Systems, Rahul Mangharam (University of Pennsylvania)

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

ABSTRACT: Balancing performance and safety are crucial to deploying autonomous vehicles in multi-agent environments. In particular, autonomous racing is a domain that penalizes safe but conservative policies, highlighting the need for robust, adaptive strategies. Current approaches either make simplifying assumptions about other agents or lack robust mechanisms for online adaptation. In this talk we will […]

A Celebration of the Life of Dr. Max Mintz

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

The CIS Department and GRASP Lab invite you to please join us on Thursday, November 17th, at 3:30pm as we celebrate the life and legacy of Dr. Max Mintz, Professor of Computer and Information Science. Max joined Penn as an assistant professor of Systems Engineering (now part of ESE) in 1974. He changed his primary […]

CIS Grace Hopper Lecture: “Data Privacy is Important, But It’s Not Enough”

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

Our current data ecosystem leaves individuals, groups, and society vulnerable to a wide range of harms, ranging from privacy violations to subversion of autonomy to discrimination to erosion of trust in institutions. In this talk, I'll discuss the Data Co-ops Project, a multi-institution, multi-disciplinary effort I co-lead with Kobbi Nissim. The Project seeks to organize our understanding of […]

ASSET Seminar: Scallop: A Language for Neuro-Symbolic Programming, Mayur Naik (University of Pennsylvania)

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

ABSTRACT: Neurosymbolic learning is an emerging paradigm which, at its core, combines the otherwise complementary worlds of classical algorithms and deep learning; in doing so, it ushers in more accurate, interpretable, and domain-aware solutions for today’s most complex machine learning challenges.  I will begin by reviewing the various fundamentals, such as algorithmic supervision, symbolic reasoning, […]

CIS Seminar: ” Exploring the role of scientific machine learning in electric power system decarbonization”

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

Electric power systems lie at the heart of efforts to mitigate and adapt to the effects of climate change.  Mitigation requires shifting electricity generation away from carbon-emitting technologies toward zero carbon sources such as wind and solar generation, and converting energy end uses like transportation and space conditioning to use that electricity.  Adaptation requires designing […]

ASSET Seminar: ML for Causal Inference, Konrad Kording, University of Pennsylvania

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

ABSTRACT Machine learning traditionally does not get at causality and causality research traditionally treats machine learning as a dangerous set of highly biased estimators. In my talk I will talk about our lab’s efforts to use machine learning as a component of more traditional quasi-experimental techniques. I will also discuss meta-learning approaches to causal inference, […]

ASSET Seminar: Domain Adaptation Under Causally Structured Distribution Shifts, Zachary Lipton (Carnegie Mellon University)

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

Presentation Abstract: Faced with unlabeled data in deployment that is sampled from a different distribution than that which generated the training data, all bets are off. Moreover, while numerous heuristics have been proposed for this vague setting, it remains unclear when any among them are applicable. One way to render these problems identifiable is to […]

ASSET Seminar: What makes learning to control easy or hard?, Nikolai Matni (University of Pennsylvania)

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

Presentation Abstract: Designing autonomous systems that are simultaneously high-performing, adaptive, and provably safe remains an open problem.  In this talk, we will argue that in order to meet this goal, new theoretical and algorithmic tools are needed that blend the stability, robustness, and safety guarantees of robust control with the flexibility, adaptability, and performance of […]

ASSET Seminar: The marriage of logic and learning: will it be a happily ever after?, Jyotirmoy Deshmukh (University of Southern California)

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

Presentation Abstract: Huge strides have made in the widespread adoption of autonomous and human-in-the-loop cyber-physical systems (CPS), partly fueled by dramatic improvements in learning-based techniques. An important aspect of such CPS applications is that they are safety-critical: any undesirable behavior by such systems can cause serious harm to human lives or property. The formal methods […]

CIS Seminar: “Proofs, Cryptography and Quantum Information”

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

Many cryptographic protocols will be rendered insecure if sufficiently powerful quantum computers are built. While this remains at least a few decades away, there is another, more immediate, problem: many widely-used security analysis techniques rely on properties of classical information that do not hold in the quantum setting, rendering the security of many schemes unclear […]