Faculty Candidate Seminars

Faster, smarter, and greener systems for data-center scale AI

Learning to Generate Data by Estimating Gradients of the Data Distribution

Beyond ISAs: Striking a Balance between Generality and Specialization for AI/ML

Unleashing the Potential of In-Network Computing

Towards a Foundation for Reinforcement Learning

Machine Learning Powered Query Optimization

Optimizing CPU Efficiency and Tail Latency in Datacenters

Formal Verification of a Concurrent File System

Efficient and Accurate Systems for Querying Unstructured Data

Putting Your Database on Autopilot: Self-driving Database Management Systems

Translating AI to Impact: Uncertainty and Human-agent Interactions in Multi-agent Systems for Public Health and Conservation

From Specialists to Generalists: Inductive Biases of Deep Learning for Higher Level Cognition

Grounding Language by Seeing, Hearing, and Interacting

Consistency and Performance in Distributed Storage Systems

Towards Scalable Representation Learning for Visual Recognition

Verifiable Machine Learning for Security

Co-designing Distributed Systems and Storage Stacks for Improved Reliability

Processor Microarchitecture Security

The Complexity of Near-Term Quantum Computers

Learning to address novel situations through human-robot collaboration

Empowering People to Have Secure and Private Interactions with Digital Technologies

Introduction to Data Science

Matching in Evolving Environments

Architecting Emerging Quantum Technologies

Advancing Sound Accessibility

Theoretical Foundations for Emerging Multiprocessor Hardware

Quantum Computation and Cryptography: a changing landscape

Computing Using Time

Teaching Faculty Candidate Seminar: Gerald Soosai Raj

Teaching Faculty Candidate Seminar–Gina Bai

Teaching Faculty Candidate Seminar–Elba Garza