All Seminars

Supporting Efforts to Broaden Participation in Computer Science

The Complexity of Finding S-factors in Regular Graphs

Principled Secure Processor Design

Word Embeddings: What Works, What Doesn’t, and How to Tell the Difference for Applied Research

Building Multi-Language Tools

Bias in Search and Recommenders Systems

Fine-grained hardness of CVP(P)— Everything that we can prove (and nothing else)

From Recognition to Reasoning

Quantifying Cell Type-Specific Changes in Transcriptional State and Gene Co-Regulation Across Multiple Datasets Using SCRANA-SEQ

How Powerful Are Graph Neural Networks?

Using deep-learning methods to predict cancer patient survival

An Adaptive Step Toward the Multiphase Conjecture

A Graph-Based Dataflow Architecture for Executing Neural Networks

Addressing challenges in real-time perception processing for automated driving

MIDAS 2019 Annual Symposium – Embracing the Challenge: Data Science for the Next Ten Years

Joint Models for Social, Behavioral and Textual Information

Rackham Faculty Allies Speaker Series: Mohammad Irfan

Getting Computer Systems Ready for Visual Computing in Ten Years

Towards building Internet of Vehicles

Toward Human-Like AI: Cognitive Architecture, Common Model of Cognition & Interactive Task Learning

Cup Emptying Games and I/O Scheduling

Constructing Tumor-Specific Gene Regulatory Networks Based on Samples with Tumor Purity Heterogeneity

Managing Stress: The Needs of Autistic Adults in Video Calling

AI for Intelligent Financial Services: Examples and Discussion

Learning & Exploiting Low-Dimensional Structure in High-Dimentional Data

Algorithms for Coping with Intractability and Uncertainty

Michigan AI Symposium – “AI for Society”

Parallelizing Greedy for Submodular Set Function Maximization

PCS Framework, Interpretable Machine Learning, and Deep Neural Networks

The polymorphic gateway between structure and algorithms: Constraint Satisfaction and Beyond

Friends Don’t Let Friends Deploy Black-Box Models: The Importance of Intelligibility in Machine Learning for HealthCare

EECS Homecoming Luncheon

Detection structure and patterns in big biomedical data

Computational exercises of creative language

Are you a researcher looking for genetic and clinic data? Do you need assistance in data analysis?

Rackham Faculty Allies Speaker Series: Nina Mishra

Feedback-Driven Processors

Game Playing Meets Game Theory: Strategic Learning from Simulated Play

Benchmarking at Scale: Comparing Analysis Workflows for Single-Cell Genomic Data

Predictive Analytics in Healthcare: From Anomaly Detection to Development of Clinical Decision Systems

The Strength of Long-Range Ties

Expander Decompositions: Fast Algorithms and Applications

statistical Methods for Flexible Differential Analysis of Cross-Sample Single-Cell RNA-Seq Datasets

Efficient Algorithms for Learning Combinatorial Structures from Limited Data

System and Architecture Design for Safe and Reliable Smart Applications

Semantic Foundations for Live Programming Environments

Supercharge analytics over large IoT data: an OS approach

Why Do Neural Networks Learn?

Data Science at The New York Times

Solving Hard Problems Automatically

Learning Hierarchical Control Programs

Bridging Data, Design, and Domain Knowledge to Build Human-Centered Systems that Support Wellbeing

Making Connections: Data Science Approaches to Understanding Mood and Cognition in the Modern Er

The Role of Context in Natural Language Processing

Towards Human-Level Recognition via Contextual, Dynamic, and Predictive Representations

Efficient Training and Inference in Deep Learning

Computational Wireless Sensing at Scale

Scalable Bayesian Inference With Hamilton Monte Carlo

Understanding and Improving Deep Neural Networks

Designing Robust Defenses for Modern Payment Systems

Infusing Structure into Machine Learning Algorithms

Towards Generalization and Efficiency in Reinforcement Learning

Scaling database systems to high-performance computers

Matrix Completion in Network Analysis

Seven Things: Frank Zappa, T. Coraghasen Boyle, and Twenty-one Years in Security

Web Automation for Everyone: From PBD to PBX

Protecting Privacy by Splitting Trust

Towards a Unified Theory of Approximate Optimization

Revisionist Simulations: A New Technique for Proving Space Lower Bounds

Overcoming the Deep Learning Power Wall with Principled Unsafe Optimization

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

Rethinking the relationship between data and robotics

Democratizing Domain-Specific Accelerators for Next-Generation Computing

Caches: Beyond the Pipeline

Towards Embodied Visual Intelligence

Model-driven network management

Image Synthesis for Self-Supervised Visual Representation Learning

On the Quantitative Hardness of the Closest Vector Problem

Solving Linear Equations

Computational Modeling in Human-Computer Interaction

Context-Driven Implicit Interactions

Information Extraction from Online Text — from Opinions to Arguments to Persuasion

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

Teachable Cognitive Systems

Coding Theory in the Big Data Era