Vijay Keswani, Duke University.   The expanding capabilities of AI come with a surge in the reports of societal and personal harms related to its use. Examples range from systemic biases in AI decision-aid tools in healthcare and policing to stereotype propagation in AI-based search and translation tools. Technical research on mitigating such harms forward… Read More »How Do We Involve People in AI Decision-Making? Towards Effective Participatory AI Designs

Swati Gupta, MIT. When someone is denied a job, offered a different price for the same goods or services, or declined a loan, intent to discriminate is often not the case. The decision system applies the same data and rules to all and yet has a disproportionate effect on various groups. The causes of such… Read More »New Algorithmic Challenges for Ethical Decision-Making

Chandrajit Bajaj, UT Austin Reinforcement learning (RL) with continuous state and action spaces is arguably one the most challenging problems within the field of machine learning.  Most current learning methods focus on integral identities such as value (Q) functions to derive an optimal strategy for the learning agent. In this talk we present the dual… Read More »Global Search and Discovery with Differential Policy Optimization

Deepak Bansal, Microsoft Abstract: Customer networks have grown, mostly organically, large and complex in cloud environments like Azure. Customers are often afraid to make changes and find it hard to diagnose when things go wrong. In this talk, I am going to share how Microsoft is using LLMs to simplify network operations at scale in… Read More »Leveraging LLMs for Networking & Security in Cloud Environments

Vijay V. Vazirani , University of California, Irvine. It is well known that the proof of some prominent results in mathematics took a very long time --- decades and even centuries. The first proof of the Micali-Vazirani (MV) algorithm, for finding a maximum cardinality matching in general graphs, was recently completed --- over four decades… Read More »A Theory of Alternating Paths and Blossoms, from the Perspective of Minimum Length

Rajeev Barua, University of Maryland. The battle between cyber attackers and attack detection teams is an arms race that is not letting up. Attackers constantly devise new ways of exploiting system vulnerabilities, and new methods to hide from detection. In response, detection teams have responded with new technologies to detect attacks. This talk will overview… Read More »Cybersecurity: Why its hard, solutions, and careers