Faculty Candidate Seminar

Name: Data Structures Meet Circuits and Cryptography
Start: 2020-01-09T10:30:00-05:00
End: 2020-01-09T11:30:00-05:00
Location: 3725 Beyster Building

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Artificial Intelligence for Geometry Processing

Defining and Ensuring Algorithmic Fairness in Artificial Intelligence

Opening the Black Box: Towards Theoretical Understanding of Deep Learning

Fair and Reliable Machine Learning for High-Stakes Applications: Approaches Using Information Theory

Physically Interactive Intelligence — A path towards autonomous embodied agents

Developing and Deploying Gallium Nitride Magnetometers for Harsh Environments

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

AI for Population Health: Melding Data and Algorithms on Networks

Introduction to Red-Black Tree

Leveraging Dataset Structure for Neural Network Prediction

Reliable Machine Learning in Feedback Systems

Prioritizing Computation and Analyst Resources in Large-scale Data Analytics

Learning Through Interaction in Cooperative Multi-Agent Systems

Introduction to Cache Organization

I Am Error: How Math Can Automatically Fix Mistakes

Hash Tables Lecture

Towards Structured-Infused and Disentangled Representation Learning

New Compilation Techniques for Reconfigurable Analog Devices

Cross-Layering in Future Wireless Networks: From Compact Full-duplex Radios to City-Scale Experimentation

Small-Data Learning in Big Cyber Physical Systems

Language Grounding with Robots

Large-Scale Optimization and Nonconvexity: From Deep Learning to Energy Markets

Harnessing Examples for Learning at Scale

Bending Fuzzers to One’s Own Will

Learning from Societal Data: Theory and Practice

Learning Spoken Language Through Vision

Auditing Outsourced Services

Rethinking Operating System and Hardware Abstractions for Good and Evil

Canceled: Scalability and Methods of Deep Learning from an Optimization Viewpoint

Designing Collective Behavior in Robotic Swarms

Connecting Blockchains to the Real World

Towards Scalable Algorithms for Distributed Optimization and Learning

Automating Failure Diagnosis for Distributed Systems

Foundations of Optimizable Gradual Typing

Learning from Societal Data: Theory and Practice

Learning Low-complexity Models from the Data – Geometry, Optimization, and Applications

Analyzing Programs in the Era of Software 2.0

Better Foundations for Secure Software: Minimize Trust and Verify It

Brain-Inspired Architecture for Efficient Learning and Robust Computing

Progressive Automated Formal Verification of Hardware and Software Systems

Algorithmic Paradigms for Dynamic Graphs

Scalability and Methods of Deep Learning from an Optimization Viewpoint

The Value Alignment Problem in Artificial Intelligence

Machine Learning for Accelerating Scientific Discovery

Towards Scalable and Reliable Architectures for Quantum Computing Platforms

Human-AI Systems for Visual Information Access

New Approaches to Real-Time Robotic Mapping and Information Gathering

Efficient Machine Learning via Data Summarization

Breaking and Building End-to-End Encrypted Systems

Control Hijacking I

Binary Search Trees for Sentiment Analysis

Introduction to Hashing and Hash Tables

Abstraction in Reinforcement Learning

Improving Team Performance and Dynamics within Human-Robot Teams

Knowledge Is Power: Sensing The Physical World Around Devices

Intro to RISC-V Assembly

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