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Events for 2019

Office of Tech Transfer (OTT) – Office Hours

Office of Tech Transfer (OTT)

Coding Theory in the Big Data Era

Mahdi Cheraghchi, Assistant Professor, Imperial College London

Dissertation Defense

Computational Linguistic Models for Personal Values and Human Activities

Teachable Cognitive Systems

Chris MacLellan, Research Scientist, Soar Technology, Inc.

Faculty Candidate Seminar

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

Colleen van Lent, Lecturer IV, University of Michigan School of Information

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

Claire Cardie, Professor, Cornell University

Faculty Candidate Seminar

Context-Driven Implicit Interactions

Gierad Laput, Ph.D. Candidate, Carnegie Mellon University

Computational Modeling in Human-Computer Interaction

Nikola Banovic, Assistant Professor, University of Michigan

Bloomberg Resume Review Workshop

Faculty Candidate Seminar

Solving Linear Equations

Rasmus Kyng, Postdoc, Harvard University

On the Quantitative Hardness of the Closest Vector Problem

Huck Bennett, Postdoctoral Researcher, Northwestern University

Computer Vision Seminar

Image Synthesis for Self-Supervised Visual Representation Learning

Richard Zhang, Research Scientist, Adobe Research

Systems Seminar – CSE

Model-driven network management

Anees Shaikh, Google, Network Infrastructure Team

Fast Enterprises Interview Prep

Google PhD Workshop (for PhD students only)

Faculty Candidate Seminar

Towards Embodied Visual Intelligence

Dinesh Jayaraman, Postdoc, University of California, Berkeley

Office of Tech Transfer (OTT) – Office Hours

Office of Tech Transfer (OTT)

Faculty Candidate Seminar

Caches: Beyond the Pipeline

Jon Beaumont, Ph.D. Candidate, University of Michigan

Faculty Candidate Seminar

Democratizing Domain-Specific Accelerators for Next-Generation Computing

Sophia Shao, Senior Research Scientist, NVIDIA Research

Computer Vision Seminar

Rethinking the relationship between data and robotics

Lerrel Pinto, PhD Candidate, Carnegie Mellon University

Faculty Candidate Seminar

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

Denae Ford, Ph.D. Candidate, North Carolina State University

Faculty Candidate Seminar

Overcoming the Deep Learning Power Wall with Principled Unsafe Optimization

Brandon Reagen, Research Scientist, Facebook

Dissertation Defense

Locality of Distributed Graph Problems

Revisionist Simulations: A New Technique for Proving Space Lower Bounds

Leqi (Jimmy) Zhu, University of Toronto

Faculty Candidate Seminar

Towards a Unified Theory of Approximate Optimization

Euiwoong Lee, Postdoc, New York University

Faculty Candidate Seminar

Protecting Privacy by Splitting Trust

Henry Corrigan-Gibbs, Ph.D. Candidate, Stanford University

Faculty Candidate Seminar

Web Automation for Everyone: From PBD to PBX

Sarah Chasins, Ph.D. Candidate, University of California, Berkeley

Security Seminar

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

Matrix Completion in Network Analysis

Ji Zhu, Department of Statistics University of Michigan

Office of Tech Transfer (OTT) – Office Hours

Office of Tech Transfer (OTT)

Systems Seminar – CSE

Scaling database systems to high-performance computers

Spyros Blanas, Assistant Professor, CSE, The Ohio State University

Towards Generalization and Efficiency in Reinforcement Learning

Wen Sun, Ph.D. Candidate, Carnegie Mellon University

Dissertation Defense

Cross-Layer System Design for Autonomous Driving

Infusing Structure into Machine Learning Algorithms

Animashree Anandkumar, PhD, Professor, Computing + Mathematical Sciences, California Institute of Technology

Faculty Candidate Seminar

Designing Robust Defenses for Modern Payment Systems

Nolen Scaife, Research Assistant, University of Florida

Dissertation Defense

Preventing Capability Abuse through Systematic Analysis of Exposed Interfaces

Understanding and Improving Deep Neural Networks

Jeff Clune, Associate Professor and Senior Research Manager, University of Wyoming and Uber AI Labs

Scalable Bayesian Inference With Hamilton Monte Carlo

Michael Betancourt, PhD, Principal Research Scientist, Symplectomorphic, LLC

Faculty Candidate Seminar

Computational Wireless Sensing at Scale

Rajalakshmi Nandakumar, Ph.D. Candidate, University of Washington

Efficient Training and Inference in Deep Learning

Ji Liu , Assistant Professor, University of Rochester

Less Metrics, More Rando: (Net) Art as Software Research

Ben Grosser, Assistant Professor of New Media, University of Illinois at Urbana-Champaign

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

Fisher Yu, Postdoc, University of California, Berkeley

Office of Tech Transfer (OTT) – Office Hours

Office of Tech Transfer (OTT)

Dissertation Defense

Classical Computation in the Quantum World

The Role of Context in Natural Language Processing

Soujanya Poria, Postdoc, School of Computer Science & Engineering, NTU, Singapore

Dissertation Defense

High Availability Localization and Mapping

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

Alex Leow, MD, PhD, Associate Professor, Departments of Psychiatry, Bioengineering, and Computer Science University of Illinois at Chicago

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

Elizabeth Murnane, Postdoc, Stanford University

Michigan Quantum Science and Technology Workshop

Learning Hierarchical Control Programs

Roy Fox, Postdoc, University of California, Berkeley

Faculty Candidate Seminar

Solving Hard Problems Automatically

Marijn Heule, Research Assistant Professor, University of Texas at Austin

Research Poster Session

Data Science at The New York Times

Chris Wiggins, PhD, Associate Professor, Columbia University

research as Career Panel

Why Do Neural Networks Learn?

Behnam Neyshabur, Postdoc, New York University

Systems Seminar – CSE

Supercharge analytics over large IoT data: an OS approach

Felix Xiaozhu Lin, Assistant Professor, Purdue University

Distinguished Lecture

Physics, Machine Learning, and Networks

Cris Moore, Professor, Santa Fe Institute

Faculty Candidate Seminar

Semantic Foundations for Live Programming Environments

Cyrus Omar, Postdoc, University of Chicago

Computer Engineering Seminar

System and Architecture Design for Safe and Reliable Smart Applications

Jishen Zhao, Assistant Professor, University of California, San Diego

CSE Bring Your Child to Work Day

Dissertation Defense

Design of Sequential Stochastic Computing Systems

Dissertation Defense

Dynamics and Social Networks

NABD 2019 (Not Another Big Data Conference)

Dissertation Defense

Requirements Testing and Verification for Smart Systems through Systematic Software Analysis

Dissertation Defense

Reducing Redundant Computation and Data in Non-deterministic Systems by Exploiting the Computation-data Duality

Efficient Algorithms for Learning Combinatorial Structures from Limited Data

Asish Ghoshal, PhD graduate, Purdue University

Precision Health Symposium

Dissertation Defense

Its Data All the Way Down: Exploring the Relationship Between Machine Learning and Data Management

Michael Anderson

Dissertation Defense

Building and Querying Structured Knowledge Sources from Natural Language Text

Dissertation Defense

Towards a More Predictable Database System

Dr. Hava Siegelmann's visit

Hava Siegelmann, Program Manager, I2O office, DARPA

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

Mark Robinson, PhD, Associate Professor of Statistical Genomics Institute of Molecular Sciences, University ofn Zurich

Dissertation Defense

Rethinking Context Management of Data Parallel Processors in an Era of Irregular Computing

Jonathan Beaumont

Dissertation Defense

Energy Efficient Algorithms in Low-Energy Wireless Sensor Networks

Dissertation Defense

Designing and Evaluating Physical Adversarial Attacks and Defenses for Machine Learning Algorithms

Dissertation Defense

Addressing Variability in Speech when Recognizing Emotion and Mood In-the-Wild

Dissertation Defense

Efficient Deep Neural Network Computation on Processors

New PhD Student Meeting

Led by Professor John Hayes

Dissertation Defense

Demographic-Aware Natural Language Processing

Aparna Garimella

Dissertation Defense

Learning Hierarchical Compositional Task Definitions through Online Situated Interactive Language Instruction

New MS Student Meeting

Led by Professor Quentin Stout

Dissertation Defense

Multimodal Character Representation for Visual Story Understanding

Expander Decompositions: Fast Algorithms and Applications

Thatchaphol Saranurak, Research Assistant Professor, TTI-Chicago

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

Elyas Sabeti, PhD, MIDAS Fellow, University of Michigan

The Strength of Long-Range Ties

Patrick Park PhD, MIDAS Fellow

Getting an NSF GRF

Assistant Professor David Fouhey

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

Jun Li, Professor of Human Genetics, University of Michigan

Game Playing Meets Game Theory: Strategic Learning from Simulated Play

Michael P. Wellman, Professor, Computer Science and Engineering, University of Michigan

Systems Seminar – CSE

Feedback-Driven Processors

Joseph Devietti, Assistant Professor, Department of Computer & Information Science at the University of Pennsylvania

Friday Night AI – AI, Personalized Technology, and Mental Health When

Prof. Emily Mower Provost and Prof. Melvin Mcinnis

Rackham Faculty Allies Speaker Series

Rackham Faculty Allies Speaker Series: Nina Mishra

Nina Mishra, Principal Scientist, Amazon

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

Erin O’Brein Kaleba, MPH Director, Data Office for Clinic and Translational Research; Cinzia Villanucci Smothers, M. Bioethics Project Manager

Computing CARES

Panel + Dinner: How to Become an EECS IA

Computational exercises of creative language

Carlo Strapparava, Senior Researcher, Fondazione Bruno Kessler – Istituto per la ricerca scientifica e Tecnologica

Alumni | Distinguished Lecture | Women in Computing

Detection structure and patterns in big biomedical data

Smita Krishnaswamy

EECS Homecoming Luncheon

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

Rich Caruana, Senior Principal Researcher, Microsoft Research

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

Venkatesan Guruswami, Professor, Carnegie Mellon University

PCS Framework, Interpretable Machine Learning, and Deep Neural Networks

Bin Yu, PHD, Chancellor’s Professor, Electrical Engineering and Computer Science University of California, Berkeley

Parallelizing Greedy for Submodular Set Function Maximization

Kent Quanrud, Asst. Professor, Purdue University

Other Event | Symposium

Michigan AI Symposium – “AI for Society”

Prof. Doina Precup, McGill University, MILA, DeepMind

Algorithms for Coping with Intractability and Uncertainty

Nikhil Bansal, Professor, Eindhoven University of Technology

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

David Dunson, PhD , Arts & Sciences Distinguished Professor of Statistical Science & Mathematics, Duke University

Computing CARES

Panel + Dinner: Engineering Opportunities Abroad

Distinguished Lecture | Women in Computing

AI for Intelligent Financial Services: Examples and Discussion

Manuela Veloso, Managing Director, Head of AI Research, J. P. Morgan

Interactive Systems Seminar

Managing Stress: The Needs of Autistic Adults in Video Calling

Andy Begel, Senior Researcher, Ability Group, Microsoft Research

Dissertation Defense

Estimation of Information Measures and Applications in Machine Learning

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

Pei Wang, PhD – Icahn School of Medicine, Mount Sinai, Professor, Department of Genetics and Geomic Sciences

Cup Emptying Games and I/O Scheduling

Michael A. Bender , Professor, Stony Brook University

Dissertation Defense

Thermal and QoS-Aware Embedded Systems

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

John E. Laird, John L. Tishman Professor of Engineering, University of Michigan

Towards building Internet of Vehicles

Dr. Fan Bai, Lab Group Manager, Electrical & Control Systems Lab., Research & Development and Planning, General Motors Corporation

Computer Engineering Seminar

Getting Computer Systems Ready for Visual Computing in Ten Years

Yuhao Zhu, Assistant Professor of Computer Science, University of Rochester

16th Annual CSE Graduate Honors Competition

16th Annual CSE Graduate Honors Competition Finalists

Rackham Faculty Allies Speaker Series

Rackham Faculty Allies Speaker Series: Mohammad Irfan

Mohammad Irfan, Assistant Professor of Digital & Computational Studies and Computer Science, Bowdoin College

Joint Models for Social, Behavioral and Textual Information

Dan Goldwasser, Assistant Professor in Computer Science, Purdue University

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

Systems Seminar – CSE

Addressing challenges in real-time perception processing for automated driving

Dr. Shige Wang, Staff Researcher, GM Global R&D

Computer Engineering Seminar

A Graph-Based Dataflow Architecture for Executing Neural Networks

Dave Fick, CTO and founder, Mythic

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

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

An Adaptive Step Toward the Multiphase Conjecture

Omri Weinstein, Asst. Professor, Columbia University

Using deep-learning methods to predict cancer patient survival

Lana Garmire, Associate Professor of Computational Medicine and Bioinformatics, University of Michigan Medical School

How Powerful Are Graph Neural Networks?

Jure Leskovec, Associate Professor, Stanford University

Computing CARES

Team Dynamics Workshop + Dinner

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

Gerald Quon, Assistant Professor, University of California

From Recognition to Reasoning

Justin Johnson, Assistant Professor, Computer Science and Engineering, University of Michigan

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

Huck Bennett, Postdoctoral Researcher, University of Michigan

Friday Night AI – Teaching Robots through Natural Interactions

Prof. John Laird and Prof. Joyce Chai, U-M CSE

Bias in Search and Recommenders Systems

Ricardo Baeza-Yates, CTO, NTENT Director, Data Science Programs,, Northeastern University, Silicon Valley Campus

Off-policy Estimation in Reinforcement Learning

Bo Dai, Research Scientist, Google Brain

Building Multi-Language Tools

Jimmy Koppel, Ph. D. candidate, Massachusetts Institute of Technology

Dissertation Defense

Enabling Usable and Performant Trusted Execution

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

Arthur Spirling, Deputy Director,, Center for Data Science, New York University

Giving Blueday 12.03.19

Dissertation Defense

Runtime Systems for Persistent Memories

Dissertation Defense

Towards Seamless Human-Mobility Interaction

Computer Engineering Seminar

Principled Secure Processor Design

Chris Fletcher, Assistant Professor in Computer Science, University of Illinois at Urbana-Champaign

The Complexity of Finding S-factors in Regular Graphs

Sanjana Kolisetty and Linh Le, University of Michigan

Dissertation Defense

Using Sensor Redundancy in Vehicles and Smartphones for Driving Security and Safety

Arunkumaar Ganesan

Dissertation Defense

Thwarting Advanced Code-reuse Attacks

Misiker Tadesse Aga

Computing CARES

Study Session + Dinner

Computer Games Showcase

Other Event | Student Event

EECS 545 Machine Learning Poster Session

Rackham Faculty Allies Speaker Series

Supporting Efforts to Broaden Participation in Computer Science

Jeff Forbes, Program Director, National Science Foundation

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