KDD2019: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Author Index


Ma, Biyu (Alibaba Group)
	Applied Data Science Track~ Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation

Ma, Chao (Baidu Inc.)
	Applied Data Science Track~ DuerQuiz: A Personalized Question Recommender System for Intelligent Job Interview

Ma, Chen (McGill University)
	Research Track~ Hierarchical Gating Networks for Sequential Recommendation

Ma, Fenglong (University at Buffalo)
	Tutorial~ Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching

Ma, Haiping (iFLYTEK CO., LTD & State Key Laboratory of Cognitive Intelligence)
	Research Track~ Exploiting Cognitive Structure for Adaptive Learning

Ma, Hanchao (Washington State University)
	Research Track~ Attribute-Driven Backbone Discovery

Ma, Jianxin (Tsinghua University)
	Research Track~ AutoNE: Hyperparameter Optimization for Massive Network Embedding

Ma, Liang (IBM Research)
	Research Track~ Efficient Global String Kernel with Random Features: Beyond Counting Substructures

Ma, Shaoping (Tsinghua University)
	Research Track~ Investigating Cognitive Effects in Session-level Search User Satisfaction

Ma, Xiaoyang (Tencent)
	Applied Data Science Track~ Large-scale User Visits Understanding and Forecasting with Deep Spatial-Temporal Tensor Factorization Framework

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Ma, Yao (Michigan State University)
	Research Track~ Graph Convolutional Networks with EigenPooling

Ma, Yintai (Northwestern University)
	Applied Data Science Track~ A Deep Value-network Based Approach for Multi-Driver Order Dispatching

Ma, Zhi-Ming (Academy of Mathematics and Systems Science, CAS)
	Research Track~ Off-policy Learning for Multiple Loggers

Maas, Paige (Facebook)
	Applied Data Science Invited Talk~ Facebook Disaster Maps: Aggregate Insights for Crisis Response & Recovery

Mackey, Lester (Microsoft Research New England)
	Applied Data Science Track~ Improving Subseasonal Forecasting in the Western U.S. with Machine Learning

Mahdian, Mohammad (Google Research)
	Research Track~ Clustering without Over-Representation

Mahoney, Michael W. (University of California, Berkeley)
	Tutorial~ Statistical Mechanics Methods for Discovering Knowledge from Modern Production Quality Neural Networks

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Maji, Subhransu (University of Massachusetts, Amherst)
	Applied Data Science Track~ DeepRoof: A Data-driven Approach For Solar Potential Estimation Using Rooftop Imagery

Maljkovic, Vera (Eli Lilly and Company)
	Applied Data Science Track~ Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams

Malreddy, Siddarth (Facebook Inc.)
	Applied Data Science Track~ MSURU: Large Scale E-commerce Image Classification With Weakly Supervised Search Data

Mangravite, Lara (Sage Bionetworks)
	Research Track~ A Permutation Approach to Assess Confounding in Machine Learning Applications for Digital Health

Maniu, Silviu (LRI, Université Paris-Sud)
	Tutorial~ Adaptive Influence Maximization

Mao, Jiaxin (Tsinghua University)
	Research Track~ Investigating Cognitive Effects in Session-level Search User Satisfaction

Mao, Yizhi (Verizon Media)
	Applied Data Science Track~ Predicting Different Types of Conversions with Multi-Task Learning in Online Advertising

Marinsek, Nikki (Evidation Health, Inc.)
	Applied Data Science Track~ Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams

Markowitz, Dale (Google Research)
	Research Track~ Contextual Fact Ranking and Its Applications in Table Synthesis and Compression

Marla, Lavanya (University of Illinois at Urbana-Champaign)
	Applied Data Science Track~ Dynamic Pricing for Airline Ancillaries with Customer Context

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Martin, Charles H. (Calculation Consulting)
	Tutorial~ Statistical Mechanics Methods for Discovering Knowledge from Modern Production Quality Neural Networks

Martin, Susan (Georgetown University)
	Applied Data Science Track~ Blending Noisy Social Media Signals with Traditional Movement Variables to Predict Forced Migration

Marx, Alexander (Max Planck Institute for Informatics)
	Research Track~ Identifiability of Cause and Effect using Regularized Regression

Mary, Jérémie (Criteo AI Lab)
	Research Track~ Tensorized Determinantal Point Processes for Recommendation

Mascolo, Cecilia (University of Cambridge)
	Applied Data Science Track~ Sequence Multi-task Learning to Forecast Mental Wellbeing from Sparse Self-reported Data
	Applied Data Science Track~ Topic-Enhanced Memory Networks for Personalised Point-of-Interest Recommendation

Masson, Véronique (Universite Rennes, Inria, CNRS, IRISA)
	Applied Data Science Track~ Towards Sustainable Dairy Management - A Machine Learning Enhanced Method for Estrus Detection

Matantsev, Ivan (Microsoft)
	Applied Data Science Track~ Machine Learning at Microsoft with ML.NET

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Matsubara, Yasuko (Osaka University)
	Research Track~ Dynamic Modeling and Forecasting of Time-evolving Data Streams

Matsushima, Shin (University of Tokyo)
	Research Track~ Scaling Multinomial Logistic Regression via Hybrid Parallelism

Matusevych, Sergiy (Microsoft)
	Applied Data Science Track~ Machine Learning at Microsoft with ML.NET

Mavridis, Themistoklis (Booking.com)
	Applied Data Science Track~ 151 Successful Machine Learning Models: 6 Lessons Learned at Booking.com

Maystre, Lucas (Spotify)
	Research Track~ Pairwise Comparisons with Flexible Time-Dynamics

McCallum, Andrew (University of Massachusetts, Amherst)
	Research Track~ Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space
	Research Track~ Paper Matching with Local Fairness Constraints
	Research Track~ Scalable Hierarchical Clustering with Tree Grafting

Meng, Changping (Purdue University)
	Research Track~ HATS: A Hierarchical Sequence-Attention Framework for Inductive Set-of-Sets Embeddings

Meng, Chenlin (Stanford University)
	Applied Data Science Track~ Predicting Economic Development using Geolocated Wikipedia Articles

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Meng, Qingxin (Rutgers-The State University of New Jersey)
	Research Track~ A Hierarchical Career-Path-Aware Neural Network for Job Mobility Prediction

Meng, Yiping (AI Labs, Didi Chuxing)
	Research Track~ Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation

Metzler, Donald (Google Inc.)
	Applied Data Science Track~ Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search

Miao, Shuo (Baidu Inc.)
	Applied Data Science Track~ MOBIUS: Towards the Next Generation of Query-Ad Matching in Baidu's Sponsored Search

Miller, Andrew (Google Research)
	Applied Data Science Track~ Hard to Park? Estimating Parking Difficulty at Scale

Ming, Yao (Hong Kong University of Science and Technology)
	Research Track~ Interpretable and Steerable Sequence Learning via Prototypes

Mirrokni, Vahab (Google Research)
	Applied Data Science Track~ Randomized Experimental Design via Geographic Clustering

Mishra, Bamdev (Microsoft India)
	Applied Data Science Track~ Detection of Review Abuse via Semi-Supervised Binary Multi-Target Tensor Decomposition

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Mishra, Shaunak (Yahoo Research)
	Applied Data Science Track~ Understanding Consumer Journey using Attention based Recurrent Neural Networks

Mitchell, Margaret (Google)
	Tutorial~ Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned

Mithal, Varun (LinkedIn)
	Tutorial~ Explainable AI in Industry

Mitrovic, Slobodan (Massachusetts Institute of Technology)
	Research Track~ Adversarially Robust Submodular Maximization under Knapsack Constraints

Mo, Songsong (Wuhan Univeristy & RMIT University)
	Research Track~ Optimizing Impression Counts for Outdoor Advertising

Moghtaderi, Azadeh (Ancestry)
	Applied Data Science Track~ Ranking in Genealogy: Search Results Fusion at Ancestry

Mohan, Vijai (Amazon)
	Applied Data Science Track~ Semantic Product Search

Mohler, Georege (Indiana University Purdue University Indianapolis)
	Applied Data Science Track~ Investigate Transitions into Drug Addiction through Text Mining of Reddit Data

Molchanov, Alexander (Yandex)
	Applied Data Science Track~ Precipitation Nowcasting with Satellite Imagery

Monath, Nicholas (University of Massachusetts, Amherst)
	Research Track~ Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space
	Research Track~ Scalable Hierarchical Clustering with Tree Grafting

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Moosavi, Sobhan (The Ohio State University)
	Applied Data Science Track~ Short and Long-term Pattern Discovery Over Large-Scale Geo-Spatiotemporal Data

Moosavinasab, Soheil (Abigail Wexner Research Institute at Nationwide Children’s Hospital)
	Research Track~ SurfCon: Synonym Discovery on Privacy-Aware Clinical Data

Moradi, Shahab (Microsoft)
	Applied Data Science Track~ Machine Learning at Microsoft with ML.NET

Mottin, Davide (Aarhus University)
	Research Track~ Figuring out the User in a Few Steps: Bayesian Multifidelity Active Search with Cokriging

Mountney, Peter (Siemens Healthineers)
	Research Track~ Training and Meta-Training Binary Neural Networks with Quantum Computing

Mrowca, Artur (BMW Group)
	Applied Data Science Track~ Context by Proxy: Identifying Contextual Anomalies Using an Output Proxy

Mueen, Abdullah (University of New Mexico)
z	Applied Data Science Track~ Structured Noise Detection: Application on Well Test Pressure Derivative Data

Müller, Emmanuel (University of Bonn)
	Research Track~ Figuring out the User in a Few Steps: Bayesian Multifidelity Active Search with Cokriging

Müller, Richard (German Meteorological Service)
	Applied Data Science Track~ The Error is the Feature: How to Forecast Lightning using a Model Prediction Error

Murata, Hiroshi (The University of Tokyo)
	Applied Data Science Track~ Glaucoma Progression Prediction Using Retinal Thickness via Latent Space Linear Regression

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Nadarajah, Selvaprabu (University of Illinois at Chicago)
	Applied Data Science Track~ SMOILE: A Shopper Marketing Optimization and Inverse Learning Engine

Najmi, Amir (Google Research)
	Applied Data Science Track~ Randomized Experimental Design via Geographic Clustering

Najork, Marc (Google)
	Applied Data Science Track~ TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank

Nandi, Arnab (The Ohio State University)
	Applied Data Science Track~ Short and Long-term Pattern Discovery Over Large-Scale Geo-Spatiotemporal Data

Nassif, Houssam (Amazon)
	Applied Data Science Track~ Seeker: Real-Time Interactive Search

Natsev, Apostol (Paul) (Google Research)
	Applied Data Science Track~ Large-Scale Training Framework for Video Annotation

Nazirov, Gani (Microsoft)
	Applied Data Science Track~ Machine Learning at Microsoft with ML.NET

Nemani, Ramakrishna (Nasa Ames Research Center)
	Applied Data Science Invited Talk~ Earth Observations from a New Generation of Geostationary Satellites

Neville, Jennifer (Purdue University)
	Research Track~ HATS: A Hierarchical Sequence-Attention Framework for Inductive Set-of-Sets Embeddings

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Newendorp, Brandon (Apple Inc)
	Applied Data Science Track~ Raise to Speak: An Accurate, Low-power Detector for Activating Voice Assistants on Smartwatches

Ng, Andrew (Stanford University)
	Applied Data Science Track~ Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning

Ng, Kenney (IBM T. J. Watson Research Center)
	Research Track~ PerDREP: Personalized Drug Effectiveness Prediction from Longitudinal Observational Data

Nguyen, Quoc Viet Hung (Griffith University)
	Research Track~ Enhancing Collaborative Filtering with Generative Augmentation

Nie, Feiping (School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University)
	Research Track~ K-Multiple-Means: A Multiple-Means Clustering Method with Specified K Clusters

Nieto, Heri (Apple Inc)
	Applied Data Science Track~ Raise to Speak: An Accurate, Low-power Detector for Activating Voice Assistants on Smartwatches

Nigam, Priyanka (Amazon)
	Applied Data Science Track~ Semantic Product Search

Niitani, Yusuke (Preferred Networks, Inc.)
	Applied Data Science Track~ Chainer: A Deep Learning Framework for Accelerating the Research Cycle

Ning, Kunpeng (Nanjing University of Aeronautics and Astronautics)
	Research Track~ Tackle Balancing Constraint for Incremental Semi-Supervised Support Vector Learning

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Ning, Wei (Alibaba Group)
	Applied Data Science Track~ IntentGC: A Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation

Ning, Wei (Alibaba Group)
	Applied Data Science Track~ Personalized Attraction Enhanced Sponsored Search with Multi-task Learning

Ning, Yue (Stevens Institute of Technology)
	Research Track~ Learning Dynamic Context Graphs for Predicting Social Events
	Tutorial~ Spatio-temporal Event Forecasting and Precursor Identification

Nishioka, Itaru (NEC Corporation)
	Applied Data Science Track~ TV Advertisement Scheduling by Learning Expert Intentions

Nissim, Nir (Ben-Gurion University)
	Applied Data Science Track~ Temporal Probabilistic Profiles for Sepsis Prediction in the ICU

Niu, Chenhao (Tsinghua University)
	Applied Data Science Track~ Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network

Niu, Di (University of Alberta)
	Applied Data Science Track~ A Deep Generative Approach to Search Extrapolation and Recommendation
	Applied Data Science Track~ A User-Centered Concept Mining System for Query and Document Understanding at Tencent
	Applied Data Science Track~ FDML: A Collaborative Machine Learning Framework for Distributed Features

Nosakhare, Ehimwenma (Massachusetts Institute of Technology)
	Applied Data Science Track~ Probabilistic Latent Variable Modeling for Assessing Behavioral Influences on Well-Being

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Noskov, Mikhail (Aspen Technology)
	Applied Data Science Track~ Online Amnestic DTW to allow Real-Time Golden Batch Monitoring

Obukhov, Mikhail (LinkedIn)
	Applied Data Science Track~ Social Skill Validation at LinkedIn

Ochiai, Keiichi (NTT DOCOMO, INC.)
	Applied Data Science Track~ Real-time On-Device Troubleshooting Recommendation for Smartphones

Ogawa, Toru (Preferred Networks, Inc.)
	Applied Data Science Track~ Chainer: A Deep Learning Framework for Accelerating the Research Cycle

Oh, Min-hwan (Columbia University)
	Research Track~ Sequential Anomaly Detection using Inverse Reinforcement Learning

Ohta, Takeru (Preferred Networks, Inc.)
	Applied Data Science Track~ Optuna: A Next-generation Hyperparameter Optimization Framework

Oikarinen, Emilia (University of Helsinki)
	Research Track~ Significance of Patterns in Data Visualisations

Okawa, Maya (NTT Corporation)
	Research Track~ Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information

Okoshi, Tadashi (Keio University)
	Applied Data Science Track~ Real-World Product Deployment of Adaptive Push Notification Scheduling on Smartphones

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Okuta, Ryosuke (Preferred Networks, Inc.)
	Applied Data Science Track~ Chainer: A Deep Learning Framework for Accelerating the Research Cycle

Omberg, Larsson (Sage Bionetworks)
	Research Track~ A Permutation Approach to Assess Confounding in Machine Learning Applications for Digital Health

Omhover, Jeff (Microsoft Corporation)
	Applied Data Science Track~ Diagnosing Sample Ratio Mismatch in Online Controlled Experiments: A Taxonomy and Rules of Thumb for Practitioners

Orenstein, Paulo (Stanford University)
	Applied Data Science Track~ Improving Subseasonal Forecasting in the Western U.S. with Machine Learning

Ormont, Justin (Microsoft)
	Applied Data Science Track~ Machine Learning at Microsoft with ML.NET

Oshri, Gal (Microsoft)
	Applied Data Science Track~ Machine Learning at Microsoft with ML.NET

Ostmo, Susan (Oregon Health & Science University)
	Applied Data Science Track~ A Severity Score for Retinopathy of Prematurity

Otwell, Ken (Otwell Research)
	Applied Data Science Track~ Dynamic Pricing for Airline Ancillaries with Customer Context

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Ou, Jiafan (Pinterest)
	Applied Data Science Track~ Finding Users Who Act Alike: Transfer Learning for Expanding Advertiser Audiences

Ou, Wenwu (Alibaba Group)
	Research Track~ Exact-K Recommendation via Maximal Clique Optimization

Ouyang, Kun (National University of Singapore & SAP Machine Learning Applications)
	Applied Data Science Track~ UrbanFM: Inferring Fine-Grained Urban Flows

Ouyang, Wentao (Alibaba Group)
	Applied Data Science Track~ Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction

Ovcharenko, Sergey (Yandex)
	Applied Data Science Track~ Precipitation Nowcasting with Satellite Imagery

Paek, Tim (Apple Inc)
	Applied Data Science Track~ Raise to Speak: An Accurate, Low-power Detector for Activating Voice Assistants on Smartwatches

Pagnoni, Artidoro (Microsoft)
	Applied Data Science Track~ Machine Learning at Microsoft with ML.NET

Pakiman, Parshan (University of Illinois at Chicago)
	Applied Data Science Track~ SMOILE: A Shopper Marketing Optimization and Inverse Learning Engine

Palsson, Bernhard O. (University of California, San Diego)
	Applied Data Science Track~ Estimating Cellular Goals from High-Dimensional Biological Data

Pan, Haojie (Hong Kong University of Science and Technology)
	Research Track~ Beyond Personalization: Social Content Recommendation for Creator Equality and Consumer Satisfaction

Pan, Junwei (Verizon Media)
	Applied Data Science Track~ Predicting Different Types of Conversions with Multi-Task Learning in Online Advertising

Pan, Lujia (Noah's Ark Lab, Huawei Technologies)
	Research Track~ Predicting Path Failure In Time-Evolving Graphs

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Pan, Xudong (Fudan University)
	Research Track~ Modeling Extreme Events in Time Series Prediction

Pan, Yi (JD.com)
	Applied Data Science Track~ Multi-Horizon Time Series Forecasting with Temporal Attention Learning

Pan, Zheyi (Shanghai Jiaotong University)
	Research Track~ Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning
	Applied Data Science Track~ TrajGuard: A Comprehensive Trajectory Copyright Protection Scheme

Pandey, Ritika (Indiana University Purdue University Indianapolis)
	Applied Data Science Track~ Investigate Transitions into Drug Addiction through Text Mining of Reddit Data

Pang, Guansong (University of Adelaide)
	Research Track~ Deep Anomaly Detection with Deviation Networks

Papapetrou, Panagiotis (Stockholm University)
	Tutorial~ Mining and Model Understanding on Medical Data

Paramonov, Kirill (Google)
	Research Track~ Estimating Graphlet Statistics via Lifting

Park, Dong Huk (Pinterest & University of California, Berkeley)
	Applied Data Science Track~ Learning a Unified Embedding for Visual Search at Pinterest

Park, Namyong (Carnegie Mellon University & Amazon)
	Research Track~ Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks

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Park, Noseong (George Mason University)
	Applied Data Science Track~ Using Twitter to Predict When Vulnerabilities will be Exploited

Park, Sungkyu (Korea Advanced Institute of Science and Technology)
	Applied Data Science Track~ Learning Sleep Quality from Daily Logs

Parmar, Jignesh (Microsoft)
	Applied Data Science Track~ Machine Learning at Microsoft with ML.NET

Parthasarathy, Srinivasan (The Ohio State University)
	Applied Data Science Track~ Short and Long-term Pattern Discovery Over Large-Scale Geo-Spatiotemporal Data

Pasumarthi, Rama Kumar (Google)
	Applied Data Science Track~ TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank

Pei, Dan (Tsinghua University)
	Applied Data Science Track~ Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network

Pei, Jian (Simon Fraser University and JD.com)
	Research Track~ AutoNE: Hyperparameter Optimization for Massive Network Embedding
	Research Track~ Conditional Random Field Enhanced Graph Convolutional Neural Networks
	Research Track~ ProGAN: Network Embedding via Proximity Generative Adversarial Network
	Research Track~ Tackle Balancing Constraint for Incremental Semi-Supervised Support Vector Learning
	Applied Data Science Track~ Multi-Horizon Time Series Forecasting with Temporal Attention Learning
	Tutorial~ Learning From Networks: Algorithms, Theory, and Applications

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Pelechrinis, Konstantinos (University of Pittsburgh)
	Applied Data Science Track~ DeepHoops: Evaluating Micro-Actions in Basketball Using Deep Feature Representations of Spatio-Temporal Data

Pellegrina, Leonardo (Università di Padova)
	Research Track~ SPuManTE: Significant Pattern Mining with Unconditional Testing
	Tutorial~ Hypothesis Testing and Statistically-sound Pattern Mining

Peng, Fanzhang (Beihang University)
	Research Track~ Empowering A* Search Algorithms with Neural Networks for Personalized Route Recommendation

Peng, Xi (University of Delaware)
	Research Track~ Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding

Perel, Sagi (Google Brain)
	Applied Data Science Track~ A Generalized Framework for Population Based Training

Perrin, Nicolas (Verizon Media)
	Applied Data Science Track~ Recurrent Neural Networks for Stochastic Control in Real-Time Bidding

Perumal, Thanneer M. (Sage Bionetworks)
	Research Track~ A Permutation Approach to Assess Confounding in Machine Learning Applications for Digital Health

Pfadler, Andreas (Alibaba Group)
	Applied Data Science Track~ POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion

Pfeifer, Jan (Google)
	Applied Data Science Track~ TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank

Pfeiffer, Karl (Atmospheric and Environmental Research)
	Applied Data Science Track~ Improving Subseasonal Forecasting in the Western U.S. with Machine Learning

Pham, Thai T. (Amazon)
	Applied Data Science Track~ Seeker: Real-Time Interactive Search

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Phillips, Cynthia (California Institute of Technology)
	Applied Data Science Track~ Enabling Onboard Detection of Events of Scientific Interest for the Europa Clipper Spacecraft

Pi, Qi (Alibaba Group)
	Applied Data Science Track~ Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction

Piat, Sebastien (Siemens Healthineers)
	Research Track~ Training and Meta-Training Binary Neural Networks with Quantum Computing

Picard, Rosalind (Massachusetts Institute of Technology)
	Applied Data Science Track~ Probabilistic Latent Variable Modeling for Assessing Behavioral Influences on Well-Being

Pierce, Lucas (Snap Inc.)
	Applied Data Science Track~ Characterizing and Forecasting User Engagement with In-App Action Graph: A Case Study of Snapchat

Plantevit, Marc (University of Lyon)
	Research Track~ Contrastive Antichains in Hierarchies

Pouget-Abadie, Jean (Google Research)
	Applied Data Science Track~ Randomized Experimental Design via Geographic Clustering

Prakash, B. Aditya (Virginia Tech)
	Research Track~ EpiDeep: Exploiting Embeddings for Epidemic Forecasting

Pratap, Abhishek (Sage Bionetworks)
	Research Track~ A Permutation Approach to Assess Confounding in Machine Learning Applications for Digital Health

Pugh, Melissa (Eli Lilly and Company)
	Applied Data Science Track~ Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams

Puolamäki, Kai (University of Helsinki)
	Research Track~ Significance of Patterns in Data Visualisations

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Qi, Yiyan (Xi'an Jiaotong University)
	Research Track~ A Memory-Efficient Sketch Method for Estimating High Similarities in Streaming Sets

Qian, Hai (Google)
	Applied Data Science Track~ Fairness in Recommendation Ranking through Pairwise Comparisons

Qian, Qi (Alibaba Group)
	Applied Data Science Track~ Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement

Qin, Bing (Harbin Institute of Technology)
	Research Track~ The Role of "Condition": A Novel Scientific Knowledge Graph Representation and Construction Model

Qin, Chuan (University of Science and Technology of China & Baidu Inc.)
	Applied Data Science Track~ DuerQuiz: A Personalized Question Recommender System for Intelligent Job Interview

Qin, Jiarui (Shanghai Jiao Tong University)
	Research Track~ Deep Landscape Forecasting for Real-time Bidding Advertising

Qin, Shouke (Baidu, Inc.)
	Applied Data Science Track~ AiAds: Automated and Intelligent Advertising System for Sponsored Search

Qin, Tao (Microsoft)
	Research Track~ Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding

Qin, Wen (Microsoft Corporation)
	Applied Data Science Track~ Diagnosing Sample Ratio Mismatch in Online Controlled Experiments: A Taxonomy and Rules of Thumb for Practitioners

Qin, Zhen (Google Inc.)
	Applied Data Science Track~ Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search

Qin, Zhiwei (AI Labs, Didi Chuxing)
	Research Track~ Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation
	Applied Data Science Track~ A Deep Value-network Based Approach for Multi-Driver Order Dispatching
	Tutorial~ Deep Reinforcement Learning with Applications in Transportation

Qiu, Guang (Alibaba Group)
	Applied Data Science Track~ IntentGC: A Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation
	Applied Data Science Track~ Personalized Attraction Enhanced Sponsored Search with Multi-task Learning

Qiu, Minghui (Alibaba Group & Zhejiang University)
	Research Track~ A Minimax Game for Instance based Selective Transfer Learning

Qu, Huamin (Hong Kong University of Science and Technology)
	Research Track~ Interpretable and Steerable Sequence Learning via Prototypes

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Quoc Viet Hung, Nguyen (Griffith University)
	Research Track~ Streaming Session-based Recommendation

Rajaram, Vijay (Twitter)
	Applied Data Science Track~ Real-time Event Detection on Social Data Streams

Ram, Parikshit (IBM Research AI)
	Research Track~ Revisiting kd-tree for Nearest Neighbor Search

Ramakrishnan, Jagdish (Walmart Labs)
	Applied Data Science Track~ Anomaly Detection for an E-commerce Pricing System

Ramakrishnan, Naren (Virginia Tech)
	Research Track~ EpiDeep: Exploiting Embeddings for Epidemic Forecasting

Ramamohanarao, Kotagiri (University of Melbourne)
	Research Track~ Improving the Quality of Explanations with Local Embedding Perturbations

Raman, Parameswaran (University of California Santa Cruz)
	Research Track~ Scaling Multinomial Logistic Regression via Hybrid Parallelism

Raman, Sethu (Apple Inc)
	Applied Data Science Track~ Raise to Speak: An Accurate, Low-power Detector for Activating Voice Assistants on Smartwatches

Ramanathan, Prashant (Airbnb Inc.)
	Applied Data Science Track~ Applying Deep Learning to Airbnb Search

Ramdas, Aaditya (Carnegie Mellon University)
	Tutorial~ Foundations of Large-Scale Sequential Experimentation

Ramnath, Rajiv (The Ohio State University)
	Applied Data Science Track~ Short and Long-term Pattern Discovery Over Large-Scale Geo-Spatiotemporal Data

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Ranganathan, Jairam (KeepTruckin)
	Applied Data Science Invited Talk~ Spinning the AI Pinwheel

Rangwala, Huzefa (George Mason University)
	Research Track~ Learning Dynamic Context Graphs for Predicting Social Events
	Tutorial~ Spatio-temporal Event Forecasting and Precursor Identification
	Tutorial~ Tutorial: Are You My Neighbor? Bringing Order to Neighbor Computing Problems.

Rao, Anup (Adobe Research)
	Research Track~ Latent Network Summarization: Bridging Network Embedding and Summarization

Rao, Vinay (Google Brain)
	Research Track~ Assessing The Factual Accuracy of Generated Text

Rashed, Ahmed (University of Hildesheim)
	Research Track~ Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings

Rawat, Bhanu Pratap Singh (University of Massachusetts, Amherst)
	Applied Data Science Track~ Naranjo Question Answering using End-to-End Multi-task Learning Model

Rekatsinas, Theodoros (University of Wisconsin-Madison)
	Tutorial~ Data Integration and Machine Learning: A Natural Synergy

Ren, Elizabeth (ETH Zürich)
	Applied Data Science Track~ Context by Proxy: Identifying Contextual Anomalies Using an Output Proxy

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Ren, Hansheng (Microsoft)
	Applied Data Science Track~ Time-Series Anomaly Detection Service at Microsoft

Ren, Kan (Shanghai Jiao Tong University)
	Research Track~ Deep Landscape Forecasting for Real-time Bidding Advertising

Ren, Liu (Bosch Research North America)
	Research Track~ Interpretable and Steerable Sequence Learning via Prototypes

Ren, Xiang (University of Southern California)
	Research Track~ AtSNE: Efficient and Robust Visualization on GPU through Hierarchical Optimization
	Applied Data Science Track~ Characterizing and Forecasting User Engagement with In-App Action Graph: A Case Study of Snapchat

Rentfrow, Jason (University of Cambridge)
	Applied Data Science Track~ Sequence Multi-task Learning to Forecast Mental Wellbeing from Sparse Self-reported Data

Ribeiro, Bruno (Purdue University)
	Research Track~ HATS: A Hierarchical Sequence-Attention Framework for Inductive Set-of-Sets Embeddings

Riondato, Matteo (Amherst College)
	Research Track~ SPuManTE: Significant Pattern Mining with Unconditional Testing
	Tutorial~ Hypothesis Testing and Statistically-sound Pattern Mining

Rizzo, Stefano Giovanni (Qatar Computing Research Institute)
	Research Track~ Time Critic Policy Gradient Methods for Traffic Signal Control in Complex and Congested Scenarios

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Robardet, Céline (University of Lyon)
	Research Track~ Contrastive Antichains in Hierarchies

Rolnick, David (University of Pennsylvania)
	Applied Data Science Track~ Randomized Experimental Design via Geographic Clustering

Rosales, Rómer (Linkedin)
	Applied Data Science Invited Talk~ Product Ecosystem Optimization at LinkedIn

Rosenberg, Charles (Pinterest)
	Applied Data Science Track~ Learning a Unified Embedding for Visual Search at Pinterest

Rosenblum, David S. (National University of Singapore)
	Applied Data Science Track~ UrbanFM: Inferring Fine-Grained Urban Flows

Rossi, Ryan A. (Adobe Research)
	Research Track~ Latent Network Summarization: Bridging Network Embedding and Summarization

Rosso, Paolo (University of Fribourg)
	Research Track~ NodeSketch: Highly-Efficient Graph Embeddings via Recursive Sketching

Roy, Nirmalya (University of Maryland Baltimore County)
	Applied Data Science Track~ Active Deep Learning for Activity Recognition with Context Aware Annotator Selection

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Roy, Prabhat (Microsoft)
	Applied Data Science Track~ Machine Learning at Microsoft with ML.NET

Rozenshtein, Polina (Nordea Data Science Lab)
	Tutorial~ Mining Temporal Networks

Ruan, Sijie (Xidian University & JD Intelligent Cities Research)
	Applied Data Science Track~ UrbanFM: Inferring Fine-Grained Urban Flows

Rudenko, Irina (Yandex)
	Applied Data Science Track~ Precipitation Nowcasting with Satellite Imagery

Rudin, Cynthia (Duke University)
	Keynote Talk~ Do Simpler Models Exist and How Can We Find Them?

Ruiz, Alfonso Lobos (University of California, Berkeley)
	Applied Data Science Track~ Predicting Different Types of Conversions with Multi-Task Learning in Online Advertising

Rundensteiner, Elke (Worcester Polytechnic Institute)
	Research Track~ Adaptive-Halting Policy Network for Early Classification

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Sabharwal, Aakash (Etsy)
	Applied Data Science Track~ Understanding the Role of Style in E-commerce Shopping

Safavi, Tara (University of Michigan Ann Arbor)
	Applied Data Science Track~ Smart Roles: Inferring Professional Roles in Email Networks

Saha, Barna (University of Massachusetts, Amherst)
	Research Track~ Paper Matching with Local Fairness Constraints

Sahoo, Doyen (Singapore Management University)
	Applied Data Science Track~ FoodAI: Food Image Recognition via Deep Learning for Smart Food Logging

Sainju, Arpan Man (University of Alabama)
	Research Track~ Hidden Markov Contour Tree: A Spatial Structured Model for Hydrological Applications

Saito, Shunta (Preferred Networks, Inc.)
	Applied Data Science Track~ Chainer: A Deep Learning Framework for Accelerating the Research Cycle

Sakuma, Jun (University of Tsukuba & RIKEN Center for Advanced Intelligence Project)
	Applied Data Science Track~ Seasonal-adjustment Based Feature Selection Method for Predicting Epidemic with Large-scale Search Engine Logs

Sakurai, Yasushi (Osaka University)
	Research Track~ Dynamic Modeling and Forecasting of Time-evolving Data Streams

Salakhutdinov, Ruslan (Apple)
	Applied Data Science Invited Talk~ Integrating Domain-Knowledge into Deep Learning

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Saleh, Mohammad (Google Brain)
	Research Track~ Assessing The Factual Accuracy of Generated Text

Samavatian, Mohammad Hossein (The Ohio State University)
	Applied Data Science Track~ Short and Long-term Pattern Discovery Over Large-Scale Geo-Spatiotemporal Data

Sano, Shotaro (Preferred Networks, Inc.)
	Applied Data Science Track~ Optuna: A Next-generation Hyperparameter Optimization Framework

Sarawagi, Sunita (IIT Bombay)
	Research Track~ Streaming Adaptation of Deep Forecasting Models using Adaptive Recurrent Units

Satyanarayan, Arvind (Massachusetts Institute of Technology)
	Research Track~ Sherlock: A Deep Learning Approach to Semantic Data Type Detection

Saunders, Michael A. (Stanford University)
	Applied Data Science Track~ Estimating Cellular Goals from High-Dimensional Biological Data

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Savchenko, Maxim (Sberbank AI Lab)
	Applied Data Science Track~ E.T.-RNN: Applying Deep Learning to Credit Loan Applications

Savvides, Rafael (University of Helsinki)
	Research Track~ Significance of Patterns in Data Visualisations

Sawaf, Hassan (Amazon Web Services)
	Applied Data Science Invited Talk~ Applications of AI/ML in Established and New Industries

Schaub, Michael T. (Massachusetts Institute of Technology & University of Oxford)
	Research Track~ Graph-based Semi-Supervised & Active Learning for Edge Flows

Schmidt-Thieme, Lars (University of Hildesheim)
	Research Track~ Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings

Schön, Christian (Saarland Informatics Campus)
	Applied Data Science Track~ The Error is the Feature: How to Forecast Lightning using a Model Prediction Error

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Schulze, Jan-Philipp (BMW Group & Fraunhofer AISEC)
	Applied Data Science Track~ Context by Proxy: Identifying Contextual Anomalies Using an Output Proxy

Scully, Shawn (Apple Inc)
	Applied Data Science Track~ Raise to Speak: An Accurate, Low-power Detector for Activating Voice Assistants on Smartwatches

Segarra, Santiago (Rice University)
	Research Track~ Graph-based Semi-Supervised & Active Learning for Edge Flows

Segev, Idan (Hebrew University of Jerusalem)
	Research Track~ Discovering Unexpected Local Nonlinear Interactions in Scientific Black-box Models

Sekhon, Jasjeet (University of California, Berkeley)
	Applied Data Science Track~ Shrinkage Estimators in Online Experiments

Seki, Yoshifumi (Gunosy Inc.)
	Applied Data Science Track~ Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creatives

Sekimoto, Yoshihide (University of Tokyo)
	Applied Data Science Track~ Predicting Evacuation Decisions using Representations of Individuals' Pre-Disaster Web Search Behavior

Sen, Cansu (Worcester Polytechnic Institute)
	Research Track~ Adaptive-Halting Policy Network for Early Classification

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Senkawa, Kohei (NTT DOCOMO, INC.)
	Applied Data Science Track~ Real-time On-Device Troubleshooting Recommendation for Smartphones

Servia-Rodriguez, Sandra (University of Cambridge)
	Applied Data Science Track~ Sequence Multi-task Learning to Forecast Mental Wellbeing from Sparse Self-reported Data

Severini, Simone (University College London)
	Research Track~ Training and Meta-Training Binary Neural Networks with Quantum Computing

Shaabani, Elham (Walmart Labs)
	Applied Data Science Track~ Anomaly Detection for an E-commerce Pricing System

Shah, Neil (Snap Inc.)
	Research Track~ Modeling Dwell Time Engagement on Visual Multimedia

Shahaf, Dafna (Hebrew University of Jerusalem)
	Research Track~ Discovering Unexpected Local Nonlinear Interactions in Scientific Black-box Models

Shahar, Avi (Tech Yahoo)
	Applied Data Science Track~ Carousel Ads Optimization in Yahoo Gemini Native

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Shahar, Yuval (Ben-Gurion University)
	Applied Data Science Track~ Temporal Probabilistic Profiles for Sepsis Prediction in the ICU

Shang, Jingbo (University of Illinois Urbana-Champaign)
	Tutorial~ Constructing and Mining Heterogeneous Information Networks from Massive Text

Shang, Shuo (University of Electronic Science and Technology of China & Inception Institute of Artificial Intelligence)
	Research Track~ Effective and Efficient Reuse of Past Travel Behavior for Route Recommendation

Shang, Shuo (University of Electronic Science and Technology of China & Inception Institute of Artificial Intelligence)
	Research Track~ GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization

Shang, Wenjie (Nanjing University)
	Research Track~ Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation

Shao, Bin (Microsoft Research)
	Applied Data Science Track~ OAG: Toward Linking Large-scale Heterogeneous Entity Graphs

Shao, Ling (Inception Institute of Artificial Intelligence)
	Research Track~ Effective and Efficient Reuse of Past Travel Behavior for Route Recommendation

Sharma, Amit (Microsoft Research India)
	Applied Data Science Track~ Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data

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Sharpnack, James (University of California, Davis)
	Research Track~ Estimating Graphlet Statistics via Lifting

Sheehan, Evan (Stanford University)
	Applied Data Science Track~ Predicting Economic Development using Geolocated Wikipedia Articles

Sheetrit, Eitam (Ben-Gurion University)
	Applied Data Science Track~ Temporal Probabilistic Profiles for Sepsis Prediction in the ICU

Shemetov, Dmitry (University of California, Davis)
	Research Track~ Estimating Graphlet Statistics via Lifting

Shen, Chunhua (University of Adelaide)
	Research Track~ Deep Anomaly Detection with Deviation Networks

Shen, Dan (Koubei, Alibaba Group)
	Applied Data Science Track~ Infer Implicit Contexts in Real-time Online-to-Offline Recommendation

Shen, Jiaming (University of Illinois Urbana-Champaign)
	Tutorial~ Constructing and Mining Heterogeneous Information Networks from Massive Text

Shen, Jie (Eli Lilly and Company)
	Applied Data Science Track~ Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams

Shen, Yanyan (Shanghai Jiao Tong University)
	Research Track~ Incorporating Interpretability into Latent Factor Models via Fast Influence Analysis
	Research Track~ Relation Extraction via Domain-aware Transfer Learning

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Shen, Yichen (Samsung Strategy and Innovation Center)
	Applied Data Science Track~ Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning

Shen, Yilin (Samsung Research America)
	Research Track~ An Visual Dialog Augmented Interactive Recommender System

Shenoy, Prashant (University of Massachusetts, Amherst)
	Applied Data Science Track~ DeepRoof: A Data-driven Approach For Solar Potential Estimation Using Rooftop Imagery

Shi, Chuan (Beijing University of Posts and Telecommunications)
	Research Track~ Adversarial Learning on Heterogeneous Information Networks
	Applied Data Science Track~ Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation

Shi, Feng (Koubei, Alibaba Group)
	Applied Data Science Track~ Infer Implicit Contexts in Real-time Online-to-Offline Recommendation

Shi, Hongzhi (Tsinghua University)
	Research Track~ State-Sharing Sparse Hidden Markov Models for Personalized Sequences

Shi, Jun (LinkedIn)
	Tutorial~ Deep Natural Language Processing for Search and Recommender Systems

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Shi, Xiaolin (Snap Inc.)
	Applied Data Science Track~ Characterizing and Forecasting User Engagement with In-App Action Graph: A Case Study of Snapchat

Shi, Xiaolin (Snap Inc.)
	Tutorial~ Challenges, Best Practices and Pitfalls in Evaluating Results of Online Controlled Experiments

Shibasaki, Ryosuke (The University of Tokyo)
	Applied Data Science Track~ DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big Events

Shimizu, Toru (Yahoo Japan Corporation)
	Applied Data Science Track~ Predicting Evacuation Decisions using Representations of Individuals' Pre-Disaster Web Search Behavior

Shin, Kijung (Korea Advanced Institute of Science and Technology)
	Research Track~ Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach

Shin, Youjin (The State University of New York (SUNY Korea))
	Applied Data Science Track~ Detecting Anomalies in Space using Multivariate Convolutional LSTM with Mixtures of Probabilistic PCA

Shingavi, Ankit (Amazon)
	Applied Data Science Track~ Semantic Product Search

Shmatikov, Vitaly (Cornell Tech)
	Research Track~ Auditing Data Provenance in Text-Generation Models

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Shu, Kai (Arizona State University)
	Research Track~ dEFEND: Explainable Fake News Detection
	Tutorial~ Fake News Research: Theories, Detection Strategies, and Open Problems

Shukla, Naman (University of Illinois at Urbana-Champaign)
	Applied Data Science Track~ Dynamic Pricing for Airline Ancillaries with Customer Context

Si, Si (Google Research)
	Research Track~ Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks

Sicilia, Anthony (University of Pittsburgh)
	Applied Data Science Track~ DeepHoops: Evaluating Micro-Actions in Basketball Using Deep Feature Representations of Spatio-Temporal Data

Siddiqui, Mohammad Zeeshan (Microsoft)
	Applied Data Science Track~ Machine Learning at Microsoft with ML.NET

Signorini, Alessio (Evidation Health, Inc.)
	Applied Data Science Track~ Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams

Silva, Daniel (Google Research)
	Research Track~ Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space

Singer, Assaf (Tech Yahoo)
	Applied Data Science Track~ Carousel Ads Optimization in Yahoo Gemini Native

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Singh, Ambuj K. (University of California, Santa Barbara)
	Research Track~ Fighting Opinion Control in Social Networks via Link Recommendation

Singh, Lisa (Georgetown University)
	Applied Data Science Track~ Blending Noisy Social Media Signals with Traditional Movement Variables to Predict Forced Migration

Sinha, Kaushik (Wichita State University)
	Research Track~ Revisiting kd-tree for Nearest Neighbor Search

Skiena, Steven (Stony Brook University)
	Applied Data Science Track~ MediaRank: Computational Ranking of Online News Sources
	Applied Data Science Track~ The Secret Lives of Names? Name Embeddings from Social Media

Snider, Lindsay (Trove AI)
	Applied Data Science Track~ Smart Roles: Inferring Professional Roles in Email Networks

Snyder, Benjamin (Microsoft Semantic Machines)
	Applied Data Science Track~ Seeker: Real-Time Interactive Search

Sohn, Timothy (Google)
	Applied Data Science Track~ Gmail Smart Compose: Real-Time Assisted Writing

Solarz, Eric (University of Michigan)
	Research Track~ GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data

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Solomentsev, Dmitry (Yandex)
	Applied Data Science Track~ Precipitation Nowcasting with Satellite Imagery

Somekh, Oren (Yahoo Research)
	Applied Data Science Track~ Carousel Ads Optimization in Yahoo Gemini Native

Song, Chaoming (University of Miami)
	Research Track~ Uncovering Pattern Formation of Information Flow

Song, Congzheng (Cornell University)
	Research Track~ Auditing Data Provenance in Text-Generation Models

Song, Dawn (University of California, Berkeley)
	Applied Data Science Track~ Characterizing and Detecting Malicious Accounts in Privacy-Centric Mobile Social Networks: A Case Study

Song, Dongjin (NEC Laboratories America, Inc.)
	Research Track~ Heterogeneous Graph Neural Network
	Research Track~ Multi-task Recurrent Neural Networks and Higher-order Markov Random Fields for Stock Price Movement Prediction: Multi-task RNN and Higer-order MRFs for Stock Price Classification

Song, Han Hee (Apple Inc.)
	Applied Data Science Track~ Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams

Song, Hengjie (South China University of Technology)
	Applied Data Science Track~ AKUPM: Attention-Enhanced Knowledge-Aware User Preference Model for Recommendation

Song, Jiaxing (Tsinghua University)
	Applied Data Science Track~ Reinforcement Learning to Optimize Long-term User Engagement in Recommender Systems

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Song, Le (Georgia Institute of Technology)
	Tutorial~ Learning From Networks: Algorithms, Theory, and Applications

Song, Qingquan (Texas A&M University)
	Research Track~ Coupled Variational Recurrent Collaborative Filtering
	Research Track~ Graph Recurrent Networks With Attributed Random Walks
	Applied Data Science Track~ Auto-Keras: An Efficient Neural Architecture Search System

Song, Xiaomin (Alibaba Group)
	Applied Data Science Track~ Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement

Song, Xiaoya (The University of Tokyo & Harbin Institute of Technology)
	Applied Data Science Track~ DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big Events

Song, Xin (Baidu Talent Intelligence Center, Baidu Inc.)
	Research Track~ The Impact of Person-Organization Fit on Talent Management: A Structure-Aware Convolutional Neural Network Approach

Song, Xuan (The University of Tokyo & National Institute of Advanced Industrial Science and Technology)
	Applied Data Science Track~ DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big Events

Song, Yang (Boss Zhipin NLP Center)
	Research Track~ Interview Choice Reveals Your Preference on the Market: To Improve Job-Resume Matching through Profiling Memories

Song, Yangqiu (Hong Kong University of Science and Technology)
	Research Track~ Beyond Personalization: Social Content Recommendation for Creator Equality and Consumer Satisfaction

Song, Yiwei (Amazon)
	Applied Data Science Track~ Semantic Product Search

Soska, Kyle (Carnegie Mellon University)
	Applied Data Science Track~ Adversarial Matching of Dark Net Market Vendor Accounts

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Sow, Daby (IBM T. J. Watson Research Center)
	Research Track~ PerDREP: Personalized Drug Effectiveness Prediction from Longitudinal Observational Data

Spathis, Dimitris (University of Cambridge)
	Applied Data Science Track~ Sequence Multi-task Learning to Forecast Mental Wellbeing from Sparse Self-reported Data

Spiliopoulou, Myra (Otto-von-Guericke-University Magdeburg)
	Tutorial~ Mining and Model Understanding on Medical Data

Spyra, Ola (DeepMind)
	Applied Data Science Track~ A Generalized Framework for Population Based Training

Sridhar, Krishna (Apple Inc)
	Applied Data Science Track~ Raise to Speak: An Accurate, Low-power Detector for Activating Voice Assistants on Smartwatches

Sridhar, Sumati (University of North Carolina at Chapel Hill)
	Applied Data Science Track~ Investigate Transitions into Drug Addiction through Text Mining of Reddit Data

Srinivasan, Sriram (University of California Santa Cruz)
	Research Track~ Scaling Multinomial Logistic Regression via Hybrid Parallelism

Sripada, Chandra (University of Michigan)
	Research Track~ GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data

Srivastava, Ashok (Intuit Inc)
	Applied Data Science Invited Talk~ AI for Small Businesses and Consumers: Applications and Innovations

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Srivastava, Megha (Stanford University)
	Applied Data Science Track~ Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning

Su, Jiao (The Chinese University of Hong Kong)
	Research Track~ Predicting Path Failure In Time-Evolving Graphs

Su, Wen (Tencent Inc)
	Research Track~ MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network

Su, Ya (Tsinghua University)
	Applied Data Science Track~ Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network

Su, Yu (iFLYTEK CO., LTD. & State Key Laboratory of Cognitive Intelligence)
	Research Track~ QuesNet: A Unified Representation for Heterogeneous Test Questions

Subrahmanian, V.S. (Dartmouth College)
	Applied Data Science Track~ Using Twitter to Predict When Vulnerabilities will be Exploited

Sühr, Tom (Max Planck Institute for Software Systems)
	Applied Data Science Track~ Two-Sided Fairness for Repeated Matchings in Two-Sided Markets: A Case Study of a Ride-Hailing Platform

Sun, Aixin (Nanyang Technological University)
	Applied Data Science Track~ Community Detection on Large Complex Attribute Network

Sun, Daren (Baidu, Inc.)
	Applied Data Science Track~ AiAds: Automated and Intelligent Advertising System for Sponsored Search

Sun, Fei (Alibaba Group)
	Research Track~ Exact-K Recommendation via Maximal Clique Optimization
	Applied Data Science Track~ POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion

Sun, Funing (Tencent Inc.)
	Research Track~ State-Sharing Sparse Hidden Markov Models for Personalized Sequences

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Sun, Huan (The Ohio State University)
	Research Track~ Riker: Mining Rich Keyword Representations for Interpretable Product Question Answering
	Research Track~ SurfCon: Synonym Discovery on Privacy-Aware Clinical Data

Sun, Jimeng (Georgia Institute of Technology)
	Tutorial~ Data Mining Methods for Drug Discovery and Development

Sun, Leilei (Beihang University)
	Research Track~ Co-Prediction of Multiple Transportation Demands Based on Deep Spatio-Temporal Neural Network
	Research Track~ Multiple Relational Attention Network for Multi-task Learning

Sun, Liang (Alibaba Group)
	Applied Data Science Track~ Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement

Sun, Mingming (Baidu Inc.)
	Applied Data Science Track~ MOBIUS: Towards the Next Generation of Query-Ad Matching in Baidu's Sponsored Search

Sun, Wei (Beijing University of Posts and Telecommunications)
	Applied Data Science Track~ Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network

Sun, Ying (Institute of Computing Technology, CAS, Baidu Talent Intelligence Center, Baidu Inc., University of Chinese Academy of Sciences)
	Research Track~ The Impact of Person-Organization Fit on Talent Management: A Structure-Aware Convolutional Neural Network Approach

Sun, Yizhou (University of California Los Angeles)
	Research Track~ Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts

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Sun, Yu (Indeed)
	Applied Data Science Track~ Predicting Different Types of Conversions with Multi-Task Learning in Online Advertising

Sundaresan, Neel (Microsoft)
	Applied Data Science Track~ Pythia: AI-assisted Code Completion System
	Applied Data Science Invited Talk~ From Code to Data: AI at Scale for Developer Productivity

Sunga, Marc (Eli Lilly and Company)
	Applied Data Science Track~ Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams

Sustik, Mátyás A. (Walmart Labs)
	Applied Data Science Track~ Anomaly Detection for an E-commerce Pricing System

Suzuki, Satomi (ExxonMobil Upstream Integrated Solutions)
	Applied Data Science Track~ Structured Noise Detection: Application on Well Test Pressure Derivative Data

Suzuki, Shuji (Preferred Networks, Inc.)
	Applied Data Science Track~ Chainer: A Deep Learning Framework for Accelerating the Research Cycle

Suzuki, Yasuhisa (NEC Corporation)
	Applied Data Science Track~ TV Advertisement Scheduling by Learning Expert Intentions

Svyatkovskiy, Alexey (Microsoft)
	Applied Data Science Track~ Pythia: AI-assisted Code Completion System

Swami, Ananthram (US Army Research Laboratory)
	Research Track~ Heterogeneous Graph Neural Network

Szolovits, Peter (Massachusetts Institute of Technology)
	Applied Data Science Track~ Unsupervised Clinical Language Translation