Faculty Candidate Seminars

Intro to RISC-V Assembly

Knowledge Is Power: Sensing The Physical World Around Devices

Improving Team Performance and Dynamics within Human-Robot Teams

Abstraction in Reinforcement Learning

Control Hijacking I

Faculty Candidate: Paul Grubbs

Faculty Candidate Seminar: Baharan Mirzasoleiman

Stable Matchings

Distributive Justice for Machine Learning: An Interdisciplinary Perspective on Defining, Measuring, and Remedying Algorithmic Unfairness

Foundations of Intelligent Systems with (Deep) Function Approximators

Sketching Graphs and Matrices

On Sunflowers and Its Friends in Computer Science and Mathematics

Data Structures Meet Circuits and Cryptography

Semantic Foundations for Live Programming Environments

Solving Hard Problems Automatically

Computational Wireless Sensing at Scale

Designing Robust Defenses for Modern Payment Systems

Web Automation for Everyone: From PBD to PBX

Protecting Privacy by Splitting Trust

Towards a Unified Theory of Approximate Optimization

Overcoming the Deep Learning Power Wall with Principled Unsafe Optimization

From Barriers to Bridges: Designing Infrastructures for Help in Online Programming Communities

Democratizing Domain-Specific Accelerators for Next-Generation Computing

Caches: Beyond the Pipeline

Towards Embodied Visual Intelligence

Solving Linear Equations

Context-Driven Implicit Interactions

Using JavaScript and Canvas to Create an Interactive Website (And the Accessibility Issues that May Arise)

Investigating Network Interference at Global Scale

Human-Centric Machine Learning: Enabling Machine Learning for High-Stakes Decision-Making

Beyond Inheritance: The Composition Pattern for Real-Time Visualization, Simulation, and Game Development

Interactive Systems for Code and Data Demography