All Seminars

Prioritizing Computation and Analyst Resources in Large-scale Data Analytics

Perception and Decision-Making Systems for Human-Robot Teaming in Safety-Critical Environments

Introduction to Red-Black Tree

AI for Population Health: Melding Data and Algorithms on Networks

Wireless Systems that See the Invisible with Machine Learning: Through-Wall Vision, Emotion Recognition, and Health Monitoring

Faculty Candidate Talk: Wei Hu

Defining and Ensuring Algorithmic Fairness in Artificial Intelligence

Faculty Candidate: Riad Wahby

Diversity and Fairness in Data Summarization Algorithms

Toward Broad and Deep Language Processing for Intelligent Systems

Sample-Efficient Nonconvex Optimization Algorithms for Machine Learning

Faculty Candidate: Fraser Brown

Bridging Learning and Decision Making

Learning Through Interaction in Cooperative Multi-Agent Systems

Prophet and Secretary Online Algorithms for Matching in General Graphs

Tight Bounds for Adversarially Robust Streams and Sliding Windows via Difference Estimators

Deterministic Mincut in Almost-Linear Time

Fooling Constant-Depth Threshold Circuits

Improved Analysis of Higher Order Random Walks

New algorithms and lower bounds for all-pairs max flow

Introduction to Cache Organization

Accidental Research: Scalable Algorithms for Graph Automorphism and Canonical Labeling

I Am Error: How Math Can Automatically Fix Mistakes

Approximating the Diameter of a Graph

Fast algorithms for linear programs and bipartite matching via new data structures and interior-point methods

Hash Tables Lecture

New Analysis of the Factor Refinement Algorithm with Applications

Explainability and Interpretability through Interaction

Impartial selection, additive approximation guarantees, and priors

Pursuing Health and Inclusion Through Sociotechnical Systems

Bridging Continuous and Discrete Optimization through the Lens of Approximation

Objectively Measure Developers’ Cognitive Activities: Code, Biases, and Brains

Mobile Health Approaches to Precision Medicine

Machine Learning and Causality: Building Efficient, Reliable Models for Decision-Making

Networks Capable of Change

AI & Accessibility: Ethical Considerations

A Unified and Fine-Grained Approach for Light Spanners

Towards General Purpose Specialization