How Auxiliary Information Can Help Your Missing Data Problem

Jerry Reiter, Duke University

Neuro-symbolic Learning for Bilevel Planning

Tom Silver, Massachusetts Institute of Technology

Data Augmentation MCMC for Bayesian Inference from Privatized Data

Nianqiao Ju, Purdue University

Realisations of Posets and Tameness

Francesca Tombari, KTH Royal Institute of Technology

Change-point Detection: Computation and Statistical Inference

Xianyang Zhang, Texas A&M University

Robust Mendelian Randomization in the Presence of Many Weak Instruments and Widespread Horizontal Pleiotropy

Ting Ye, University of Washington

Sufficient Reductions in Regression with Mixed Predictors

Efstathia Bura, Vienna University of Technology

Spectral Telescope: Convergence Rate Bounds for Random- Scan Gibbs Samplers Based on a Hierarchical Structure

Qian Qin, University of Minnesota

Learning-Based Robot Control from Vision: Formal Guarantees and Fundamental Limits

Anirudha Majumdar, Princeton University

Counter Examples for Stochastic Gradient Descent

Vivak Patel, University of Wisconsin, Madison

Copula-based Approaches by Analyzing non-Gaussian Spatial Data

Judy Wang, George Washington University

Searching for Truth through Data

Edsel Pena, University of South Carolina

A Modelling Framework for Regression with Collinearity

Takeaki Kariya, Nagoya University of Commerce and Business School, Japan

Hybrid Robotics and Implicit Learning

Michael Posa, MEAM, University of Pennsylvania

Estimating Means of Bounded Random Variables by Betting

Aaditya Ramdas, Carnegie Mellon University

A Robust, Differentially Private Randomized Experiment for Evaluating Online Educational Programs with Sensitive Student Data

Hyunseung Kang, University of Wisconsin, Madison

Order-of-addition Experiments: Design and Analysis

Dennis Lin, Purdue University

Explaining the Decisions of AI Systems

Adnan Darwiche, University of California, Los Angeles

Instance Dependent Sample Complexity Bounds for Interactive Learning

Kevin Jamieson, University of Washington

Predictability, Stability, and Causality with a Case Study to Find Genetic Drivers of a Heart Disease

Bin Yu, University of California, Berkeley

Stationary Optimal Transport with Applications to Graph Alignment

Andrew Nobel, University of North Carolina, Chapel Hill

Repro Sampling Method for Statistical Inference of High Dimensional Linear Models

Peng Wang, University of Cincinnati

Statistical Methods for Harmonizing Multi-scanner Neuroimaging

Russell Shinohara, University of Pennsylvania

Statistical Inference for High-dimensional Block-wise Missing Data

Fei Xue, Purdue University

Motion Planning Advancements and Applications in Computational Biology: An Algebraic Topology Perspective

Chinwe Ekenna, The State University of New York

SAT-Hub: Smart and Accessible Transportation Hub for Assistive Navigation and Facility Management

Zhigang Zhu, The City College and Graduate Center / CUNY

Locality in Computation

Ronitt Rubinfeld, Massachusetts Institute of Technology

Attractors of Nonsmooth and Multivalued Dynamical Systems

Cameron Thieme, DIMACS

Robotic Rearrangement - Two Talks by DIMACS TRIPODS Students

Kai Gao, Rutgers University

Rui Wang, Rutgers University

Co-evolution of Opinion and Social Tie Dynamics Towards Structural Balance

Haotian Wang, Rutgers University

Change-point Detection for COVID-19 Time Series via Self-normalization

Xiaofeng Shao, University of Illinois, Urbana-Champaign

Combinatorial Description of Global Dynamics (an approach to solve ODE)

Ewerton Rocha Vieira, Rutgers University

Learning Sign Language with AI Driven Grammar Checking

YingLi Tian, City University of New York

Ethics Washing in AI

Moshe Vardi, Rice University

Integrated Inference Analyses to Dissect Tumor Mutational Profiles

Hossein Khiabanian, Cancer Institute of New Jersey

Throwing a Sofa Through the Window

Dan Halperin, Tel-Aviv University

Artificial Intelligence for Wildlife Conservation: AI and Humans Combating Extinction Together

Tanya Berger-Wolf, Ohio State University

Long Duration Autonomy With Applications to Persistent Environmental Monitoring

Magnus Egerstedt, Georgia Institute of Technology

Auditing and Controlling Algorithmic Bias

Vivek Singh, Rutgers University

Using Satellite Imagery and Deep Learning to Target Aid in Data-sparse Contexts

Woojin Jung, Rutgers University

Mechanism Design and Data Science

Jason Hartline, Northwestern University

Learning Interaction Laws in Particle- and Agent-based Systems

Mauro Maggioni, Johns Hopkins University

Interpretability vs. Explainability in Machine Learning

Cynthia Rudin, Duke University

Algorithmic Fairness

Vivek Singh, Rutgers University

From Optimization Algorithms to Dynamical Systems and Back

Rene Vidal, Johns Hopkins University

Cooperation in Humans and Machines

Patrick Shafto, Rutgers University