Neil Shah - RankMe

215 papers A* 51A 23B 7C 2Misc 3Journal 99Unranked 30

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	CLARIS: Clear and Intelligible Speech from Whispered and Dysarthric Voices. CHI Neil Shah, Yash Sonkar, Shirish Subhash Karande, Vineet Gandhi
2026	J	`jnl`	FlexRec: Adapting LLM-based Recommenders for Flexible Needs via Reinforcement Learning. CoRR Yijun Pan, Weikang Qiu, Qiyao Ma, Mingxuan Ju, Tong Zhao, Neil Shah, Rex Ying
2026	J	`jnl`	MemRec: Collaborative Memory-Augmented Agentic Recommender System. CoRR Weixin Chen, Yuhan Zhao, Jingyuan Huang, Zihe Ye, Clark Mingxuan Ju, Tong Zhao, Neil Shah, Li Chen, Yongfeng Zhang
2026	J	`jnl`	Plain Transformers are Surprisingly Powerful Link Predictors. CoRR Quang Truong, Yu Song, Donald Loveland, Mingxuan Ju, Tong Zhao, Neil Shah, Jiliang Tang
2026	A	`conf`	Sequential Data Augmentation for Generative Recommendation. WSDM Geon Lee, Bhuvesh Kumar, Mingxuan Ju, Tong Zhao, Kijung Shin, Neil Shah, Liam Collins
2026	A	`conf`	Third Workshop on Generative AI for Recommender Systems and Personalization. WSDM Narges Tabari, Aniket Deshmukh, Wang-Cheng Kang, Julian J. McAuley, James Caverlee, Neil Shah, George Karypis
2026	J	`jnl`	Threshold Differential Attention for Sink-Free, Ultra-Sparse, and Non-Dispersive Language Modeling. CoRR Xingyue Huang, Xueying Ding, Mingxuan Ju, Yozen Liu, Neil Shah, Tong Zhao
2025	J	`jnl`	A Pre-training Framework for Relational Data with Information-theoretic Principles. CoRR Quang Truong, Zhikai Chen, Mingxuan Ju, Tong Zhao, Neil Shah, Jiliang Tang
2025	J	`jnl`	Beyond Unimodal Boundaries: Generative Recommendation with Multimodal Semantics. CoRR Jing Zhu, Mingxuan Ju, Yozen Liu, Danai Koutra, Neil Shah, Tong Zhao
2025	J	`jnl`	Exploiting ID-Text Complementarity via Ensembling for Sequential Recommendation. CoRR Liam Collins, Bhuvesh Kumar, Clark Mingxuan Ju, Tong Zhao, Donald Loveland, Leonardo Neves, Neil Shah
2025	—	`conf`	FedKDD 2025: The 2025 International Joint Workshop on Federated Learning for Data Mining and Graph Analytics. KDD (2) Carl Yang, Guancheng Wan, Zhuangdi Zhu, Zheng Xu, Junyuan Hong, Nathalie Baracaldo, Neil Shah, Salman Avestimehr, Jiayu Zhou
2025	A	`conf`	Generative Recommendation with Semantic IDs: A Practitioner's Handbook. CIKM Clark Mingxuan Ju, Liam Collins, Leonardo Neves, Bhuvesh Kumar, Louis Yufeng Wang, Tong Zhao, Neil Shah
2025	J	`jnl`	Generative Recommendation with Semantic IDs: A Practitioner's Handbook. CoRR Clark Mingxuan Ju, Liam Collins, Leonardo Neves, Bhuvesh Kumar, Louis Yufeng Wang, Tong Zhao, Neil Shah
2025	—	`conf`	GiGL: Large-Scale Graph Neural Networks at Snapchat. KDD (2) Tong Zhao, Yozen Liu, Matthew Kolodner, Kyle Montemayor, Elham Ghazizadeh, Ankit Batra, Zihao Fan, Xiaobin Gao, Xuan Guo, Jiwen Ren, Serim Park, Peicheng Yu, Jun Yu, Shubham Vij, Neil Shah
2025	J	`jnl`	GiGL: Large-Scale Graph Neural Networks at Snapchat. CoRR Tong Zhao, Yozen Liu, Matthew Kolodner, Kyle Montemayor, Elham Ghazizadeh, Ankit Batra, Zihao Fan, Xiaobin Gao, Xuan Guo, Jiwen Ren, Serim Park, Peicheng Yu, Jun Yu, Shubham Vij, Neil Shah
2025	A*	`conf`	GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems. WWW Xinyi Wu, Donald Loveland, Runjin Chen, Yozen Liu, Xin Chen, Leonardo Neves, Ali Jadbabaie, Mingxuan Ju, Neil Shah, Tong Zhao
2025	A*	`conf`	Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks. ICML Rui Xue, Tong Zhao, Neil Shah, Xiaorui Liu
2025	J	`jnl`	Heuristic Methods are Good Teachers to Distill MLPs for Graph Link Prediction. CoRR Zongyue Qin, Shichang Zhang, Mingxuan Ju, Tong Zhao, Neil Shah, Yizhou Sun
2025	J	`jnl`	Hierarchical Token Prepending: Enhancing Information Flow in Decoder-based LLM Embeddings. CoRR Xueying Ding, Xingyue Huang, Mingxuan Ju, Liam Collins, Yozen Liu, Leman Akoglu, Neil Shah, Tong Zhao
2025	—	`conf`	Improving Out-of-Vocabulary Hashing in Recommendation Systems. WWW (Companion Volume) William Shiao, Mingxuan Ju, Zhichun Guo, Xin Chen, Evangelos E. Papalexakis, Tong Zhao, Neil Shah, Yozen Liu
2025	A*	`conf`	Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning. ICML Ngoc Bui, Menglin Yang, Runjin Chen, Leonardo Neves, Mingxuan Ju, Rex Ying, Neil Shah, Tong Zhao
2025	J	`jnl`	Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning. CoRR Ngoc Bui, Menglin Yang, Runjin Chen, Leonardo Neves, Mingxuan Ju, Rex Ying, Neil Shah, Tong Zhao
2025	A*	`conf`	Learning Universal User Representations Leveraging Cross-domain User Intent at Snapchat. SIGIR Clark Mingxuan Ju, Leonardo Neves, Bhuvesh Kumar, Liam Collins, Tong Zhao, Yuwei Qiu, Qing Dou, Yang Zhou, Sohail Nizam, Rengim Aykan Ozturk, Yvette Liu, Sen Yang, Manish Malik, Neil Shah
2025	J	`jnl`	Learning Universal User Representations Leveraging Cross-domain User Intent at Snapchat. CoRR Clark Mingxuan Ju, Leonardo Neves, Bhuvesh Kumar, Liam Collins, Tong Zhao, Yuwei Qiu, Qing Dou, Yang Zhou, Sohail Nizam, Rengim Ozturk, Yvette Liu, Sen Yang, Manish Malik, Neil Shah
2025	A	`conf`	MI4Rec: Pretrained Language Model based Cold-Start Recommendation with Meta-Item Embeddings. CIKM Zaiyi Zheng, Yaochen Zhu, Haochen Liu, Mingxuan Ju, Tong Zhao, Neil Shah, Jundong Li
2025	J	`jnl`	Masked Diffusion for Generative Recommendation. CoRR Kulin Shah, Bhuvesh Kumar, Neil Shah, Liam Collins
2025	A*	`conf`	Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning. CVPR Jing Zhu, Yuhang Zhou, Shengyi Qian, Zhongmou He, Tong Zhao, Neil Shah, Danai Koutra
2025	A	`conf`	NAM-to-Speech Conversion with Multitask-Enhanced Autoregressive Models. INTERSPEECH Neil Shah, Shirish Karande, Vineet Gandhi
2025	J	`jnl`	Node Duplication Improves Cold-start Link Prediction. Trans. Mach. Learn. Res. Zhichun Guo, Tong Zhao, Yozen Liu, Kaiwen Dong, William Shiao, Mingxuan Ju, Neil Shah, Nitesh V. Chawla
2025	—	`conf`	On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective. KDD (2) Donald Loveland, Mingxuan Ju, Tong Zhao, Neil Shah, Danai Koutra
2025	J	`jnl`	On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective. CoRR Donald Loveland, Mingxuan Ju, Tong Zhao, Neil Shah, Danai Koutra
2025	J	`jnl`	Retrieval-Augmented Generation with Graphs (GraphRAG). CoRR Haoyu Han, Yu Wang, Harry Shomer, Kai Guo, Jiayuan Ding, Yongjia Lei, Mahantesh Halappanavar, Ryan A. Rossi, Subhabrata Mukherjee, Xianfeng Tang, Qi He, Zhigang Hua, Bo Long, Tong Zhao, Neil Shah, Amin Javari, Yinglong Xia, Jiliang Tang
2025	—	`conf`	Revisiting Self-attention for Cross-domain Sequential Recommendation. KDD (2) Clark Mingxuan Ju, Leonardo Neves, Bhuvesh Kumar, Liam Collins, Tong Zhao, Yuwei Qiu, Qing Dou, Sohail Nizam, Sen Yang, Neil Shah
2025	J	`jnl`	Revisiting Self-attention for Cross-domain Sequential Recommendation. CoRR Clark Mingxuan Ju, Leonardo Neves, Bhuvesh Kumar, Liam Collins, Tong Zhao, Yuwei Qiu, Qing Dou, Sohail Nizam, Sen Yang, Neil Shah
2025	J	`jnl`	SEESAW: Do Graph Neural Networks Improve Node Representation Learning for All? J. Data-centric Mach. Learn. Res. Yushun Dong, William Shiao, Yozen Liu, Jundong Li, Neil Shah, Tong Zhao
2025	—	`conf`	Second Workshop on Generative AI for Recommender Systems and Personalization. KDD (2) Narges Tabari, Aniket Deshmukh, Wang-Cheng Kang, Julian J. McAuley, James Caverlee, Neil Shah, George Karypis
2025	J	`jnl`	Sequential Data Augmentation for Generative Recommendation. CoRR Geon Lee, Bhuvesh Kumar, Clark Mingxuan Ju, Tong Zhao, Kijung Shin, Neil Shah, Liam Collins
2025	—	`conf`	Training Industry-scale GNNs with GiGL. KDD (2) Yozen Liu, Tong Zhao, Matthew Kolodner, Kyle Montemayor, Shubham Vij, Neil Shah
2025	J	`jnl`	Understanding Generative Recommendation with Semantic IDs from a Model-scaling View. CoRR Jingzhe Liu, Liam Collins, Jiliang Tang, Tong Zhao, Neil Shah, Clark Mingxuan Ju
2025	A*	`conf`	Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank. WWW Donald Loveland, Xinyi Wu, Tong Zhao, Danai Koutra, Neil Shah, Mingxuan Ju
2025	B	`conf`	VirtualGCN - Enhancing Graph Collaborative Filtering with Virtual Interactions. IEEE Big Data Patrick Soga, Yushun Dong, Yaochen Zhu, Jundong Li, Tong Zhao, Neil Shah
2024	A*	`conf`	A Topological Perspective on Demystifying GNN-Based Link Prediction Performance. ICLR Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng, Neil Shah, Tyler Derr
2024	J	`jnl`	Enhancing Item Tokenization for Generative Recommendation through Self-Improvement. CoRR Runjin Chen, Mingxuan Ju, Ngoc Bui, Dimosthenis Antypas, Stanley Cai, Xiaopeng Wu, Leonardo Neves, Zhangyang Wang, Neil Shah, Tong Zhao
2024	—	`conf`	Explainability and Hate Speech: Structured Explanations Make Social Media Moderators Faster. ACL (Short Papers) Agostina Calabrese, Leonardo Neves, Neil Shah, Maarten W. Bos, Björn Ross, Mirella Lapata, Francesco Barbieri
2024	J	`jnl`	Explainability and Hate Speech: Structured Explanations Make Social Media Moderators Faster. CoRR Agostina Calabrese, Leonardo Neves, Neil Shah, Maarten W. Bos, Björn Ross, Mirella Lapata, Francesco Barbieri
2024	A*	`conf`	FedKDD: International Joint Workshop on Federated Learning for Data Mining and Graph Analytics. KDD Junyuan Hong, Carl Yang, Zhuangdi Zhu, Zheng Xu, Nathalie Baracaldo, Neil Shah, Salman Avestimehr, Jiayu Zhou
2024	J	`jnl`	Graph Foundation Models. CoRR Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang
2024	J	`jnl`	GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems. CoRR Xinyi Wu, Donald Loveland, Runjin Chen, Yozen Liu, Xin Chen, Leonardo Neves, Ali Jadbabaie, Clark Mingxuan Ju, Neil Shah, Tong Zhao
2024	J	`jnl`	Guest Editorial: Special Issue on Graph Learning. IEEE Trans. Neural Networks Learn. Syst. Feng Xia, Renaud Lambiotte, Neil Shah, Hanghang Tong, Irwin King
2024	J	`jnl`	HARec: Hyperbolic Graph-LLM Alignment for Exploration and Exploitation in Recommender Systems. CoRR Qiyao Ma, Menglin Yang, Mingxuan Ju, Tong Zhao, Neil Shah, Rex Ying
2024	J	`jnl`	Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks. CoRR Rui Xue, Tong Zhao, Neil Shah, Xiaorui Liu
2024	A*	`conf`	How Does Message Passing Improve Collaborative Filtering? NeurIPS Mingxuan Ju, William Shiao, Zhichun Guo, Yanfang Ye, Yozen Liu, Neil Shah, Tong Zhao
2024	J	`jnl`	How Does Message Passing Improve Collaborative Filtering? CoRR Mingxuan Ju, William Shiao, Zhichun Guo, Yanfang Ye, Yozen Liu, Neil Shah, Tong Zhao
2024	J	`jnl`	Hybrid-DAOs: Enhancing Governance, Scalability, and Compliance in Decentralized Systems. CoRR Neil Shah
2024	A*	`conf`	Improving Embedding-Based Retrieval in Friend Recommendation with ANN Query Expansion. SIGIR Pau Perng-Hwa Kung, Zihao Fan, Tong Zhao, Yozen Liu, Zhixin Lai, Jiahui Shi, Yan Wu, Jun Yu, Neil Shah, Ganesh Venkataraman
2024	J	`jnl`	Improving Out-of-Vocabulary Handling in Recommendation Systems. CoRR William Shiao, Mingxuan Ju, Zhichun Guo, Xin Chen, Evangelos E. Papalexakis, Tong Zhao, Neil Shah, Yozen Liu
2024	A*	`conf`	LLaGA: Large Language and Graph Assistant. ICML Runjin Chen, Tong Zhao, Ajay Kumar Jaiswal, Neil Shah, Zhangyang Wang
2024	J	`jnl`	LLaGA: Large Language and Graph Assistant. CoRR Runjin Chen, Tong Zhao, Ajay Jaiswal, Neil Shah, Zhangyang Wang
2024	—	`conf`	Learning from Graphs Beyond Message Passing Neural Networks. Tiny Papers @ ICLR Tong Zhao, Neil Shah, Elham Ghazizadeh
2024	J	`jnl`	Multimodal Graph Benchmark. CoRR Jing Zhu, Yuhang Zhou, Shengyi Qian, Zhongmou He, Tong Zhao, Neil Shah, Danai Koutra
2024	J	`jnl`	Neural Scaling Laws on Graphs. CoRR Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang
2024	J	`jnl`	Node Duplication Improves Cold-start Link Prediction. CoRR Zhichun Guo, Tong Zhao, Yozen Liu, Kaiwen Dong, William Shiao, Neil Shah, Nitesh V. Chawla
2024	J	`jnl`	One Model for One Graph: A New Perspective for Pretraining with Cross-domain Graphs. CoRR Jingzhe Liu, Haitao Mao, Zhikai Chen, Wenqi Fan, Mingxuan Ju, Tong Zhao, Neil Shah, Jiliang Tang
2024	A*	`conf`	Position: Graph Foundation Models Are Already Here. ICML Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang
2024	A*	`conf`	Revisiting Link Prediction: a data perspective. ICLR Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
2024	—	`conf`	Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems. RobustRecSys@RecSys Matthew Kolodner, Mingxuan Ju, Zihao Fan, Tong Zhao, Elham Ghazizadeh, Yan Wu, Neil Shah, Yozen Liu
2024	J	`jnl`	Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems. CoRR Matthew Kolodner, Mingxuan Ju, Zihao Fan, Tong Zhao, Elham Ghazizadeh, Yan Wu, Neil Shah, Yozen Liu
2024	—	`conf`	Towards Neural Scaling Laws on Graphs. LoG Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang
2024	J	`jnl`	Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank. CoRR Donald Loveland, Xinyi Wu, Tong Zhao, Danai Koutra, Neil Shah, Mingxuan Ju
2024	J	`jnl`	Unpacking the exploration-exploitation tradeoff on Snapchat: The relationships between users' exploration-exploitation interests and server log data. Comput. Hum. Behav. Diego Gómez-Zará, Yozen Liu, Leonardo Neves, Neil Shah, Maarten W. Bos
2023	A*	`conf`	19th International Workshop on Mining and Learning with Graphs (MLG). KDD Neil Shah, Shobeir Fakhraei, Da Zheng, Bahare Fatemi, Leman Akoglu
2023	J	`jnl`	A Topological Perspective on Demystifying GNN-Based Link Prediction Performance. CoRR Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng, Neil Shah, Tyler Derr
2023	—	`conf`	Are Message Passing Neural Networks Really Helpful for Knowledge Graph Completion? ACL (1) Juanhui Li, Harry Shomer, Jiayuan Ding, Yiqi Wang, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
2023	A*	`conf`	CARL-G: Clustering-Accelerated Representation Learning on Graphs. KDD William Shiao, Uday Singh Saini, Yozen Liu, Tong Zhao, Neil Shah, Evangelos E. Papalexakis
2023	J	`jnl`	CARL-G: Clustering-Accelerated Representation Learning on Graphs. CoRR William Shiao, Uday Singh Saini, Yozen Liu, Tong Zhao, Neil Shah, Evangelos E. Papalexakis
2023	A*	`conf`	Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? NeurIPS Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
2023	J	`jnl`	Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? CoRR Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
2023	A*	`conf`	Embedding Based Retrieval in Friend Recommendation. SIGIR Jiahui Shi, Vivek Chaurasiya, Yozen Liu, Shubham Vij, Yan Wu, Satya Kanduri, Neil Shah, Peicheng Yu, Nik Srivastava, Lei Shi, Ganesh Venkataraman, Jun Yu
2023	A*	`conf`	Empowering Graph Representation Learning with Test-Time Graph Transformation. ICLR Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah
2023	A*	`conf`	Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking. NeurIPS Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
2023	J	`jnl`	Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking. CoRR Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
2023	A*	`conf`	Forget Unlearning: Towards True Data-Deletion in Machine Learning. ICML Rishav Chourasia, Neil Shah
2023	J	`jnl`	Graph Data Augmentation for Graph Machine Learning: A Survey. IEEE Data Eng. Bull. Tong Zhao, Wei Jin, Yozen Liu, Yingheng Wang, Gang Liu, Stephan Günnemann, Neil Shah, Meng Jiang
2023	A	`conf`	Graph Explicit Neural Networks: Explicitly Encoding Graphs for Efficient and Accurate Inference. WSDM Yiwei Wang, Bryan Hooi, Yozen Liu, Neil Shah
2023	J	`jnl`	Graph Transformers for Large Graphs. CoRR Vijay Prakash Dwivedi, Yozen Liu, Anh Tuan Luu, Xavier Bresson, Neil Shah, Tong Zhao
2023	A*	`conf`	GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation. NeurIPS Mingxuan Ju, Tong Zhao, Wenhao Yu, Neil Shah, Yanfang Ye
2023	J	`jnl`	GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation. CoRR Mingxuan Ju, Tong Zhao, Wenhao Yu, Neil Shah, Yanfang Ye
2023	A*	`conf`	Large-Scale Graph Neural Networks: The Past and New Frontiers. KDD Rui Xue, Haoyu Han, Tong Zhao, Neil Shah, Jiliang Tang, Xiaorui Liu
2023	A*	`conf`	Link Prediction with Non-Contrastive Learning. ICLR William Shiao, Zhichun Guo, Tong Zhao, Evangelos E. Papalexakis, Yozen Liu, Neil Shah
2023	A*	`conf`	Linkless Link Prediction via Relational Distillation. ICML Zhichun Guo, William Shiao, Shichang Zhang, Yozen Liu, Nitesh V. Chawla, Neil Shah, Tong Zhao
2023	A*	`conf`	MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization. ICLR Xiaotian Han, Tong Zhao, Yozen Liu, Xia Hu, Neil Shah
2023	A*	`conf`	Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization. ICLR Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, Chuxu Zhang
2023	A	`conf`	Predicting Future Location Categories of Users in a Large Social Platform. ICWSM Raiyan Abdul Baten, Yozen Liu, Heinrich Peters, Francesco Barbieri, Neil Shah, Leonardo Neves, Maarten W. Bos
2023	J	`jnl`	Revisiting Link Prediction: A Data Perspective. CoRR Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
2023	A*	`conf`	Sketch-Based Anomaly Detection in Streaming Graphs. KDD Siddharth Bhatia, Mohit Wadhwa, Kenji Kawaguchi, Neil Shah, Philip S. Yu, Bryan Hooi
2023	A	`conf`	The 3rd International Workshop on Machine Learning on Graphs (MLoG). WSDM Tyler Derr, Yao Ma, Benedek Rozemberczki, Neil Shah, Shirui Pan
2022	A*	`conf`	17th International Workshop on Mining and Learning with Graphs (MLG). KDD Shobeir Fakhraei, Tim Weninger, Neil Shah, Sami Abu-El-Haija, Saurabh Verma, Tara Safavi
2022	A*	`conf`	A Practical, Progressively-Expressive GNN. NeurIPS Lingxiao Zhao, Neil Shah, Leman Akoglu
2022	J	`jnl`	A Practical, Progressively-Expressive GNN. CoRR Lingxiao Zhao, Louis Härtel, Neil Shah, Leman Akoglu
2022	J	`jnl`	A Synergistic Approach for Graph Anomaly Detection With Pattern Mining and Feature Learning. IEEE Trans. Neural Networks Learn. Syst. Tong Zhao, Tianwen Jiang, Neil Shah, Meng Jiang
2022	J	`jnl`	Are Graph Neural Networks Really Helpful for Knowledge Graph Completion? CoRR Juan-Hui Li, Harry Shomer, Jiayuan Ding, Yiqi Wang, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
2022	A	`conf`	Attributed Graph Modeling with Vertex Replacement Grammars. WSDM Satyaki Sikdar, Neil Shah, Tim Weninger
2022	A*	`conf`	Automated Self-Supervised Learning for Graphs. ICLR Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang
2022	J	`jnl`	Editorial: Computational Behavioral Modeling for Big User Data. Frontiers Big Data Meng Jiang, Chuxu Zhang, Xiangliang Zhang, Neil Shah
2022	J	`jnl`	Empowering Graph Representation Learning with Test-Time Graph Transformation. CoRR Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah
2022	J	`jnl`	Explaining Graph-level Predictions with Communication Structure-Aware Cooperative Games. CoRR Shichang Zhang, Neil Shah, Yozen Liu, Yizhou Sun
2022	Misc	`conf`	Extending the Standard REDCap Dictionary Definitions Using REDCap. AMIA Andrew Niederhausern, Nadia Bahadur, Neil Shah, Fenil Gandhi, Alysha Insinga, Kimberly Chan, Laura Barton, John Philip, Chelsea Nichols
2022	A	`conf`	Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs. WSDM Hyeonjeong Shin, Taehyung Kwon, Neil Shah, Kijung Shin
2022	—	`conf`	Flashlight: Scalable Link Prediction With Effective Decoders. LoG Yiwei Wang, Bryan Hooi, Yozen Liu, Tong Zhao, Zhichun Guo, Neil Shah
2022	J	`jnl`	Flashlight: Scalable Link Prediction with Effective Decoders. CoRR Yiwei Wang, Bryan Hooi, Yozen Liu, Tong Zhao, Zhichun Guo, Neil Shah
2022	J	`jnl`	Forget Unlearning: Towards True Data-Deletion in Machine Learning. CoRR Rishav Chourasia, Neil Shah, Reza Shokri
2022	A	`conf`	Friend Story Ranking with Edge-Contextual Local Graph Convolutions. WSDM Xianfeng Tang, Yozen Liu, Xinran He, Suhang Wang, Neil Shah
2022	A*	`conf`	From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness. ICLR Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah
2022	A*	`conf`	GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games. NeurIPS Shichang Zhang, Yozen Liu, Neil Shah, Yizhou Sun
2022	A*	`conf`	Graph Condensation for Graph Neural Networks. ICLR Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah
2022	A*	`conf`	Graph-less Neural Networks: Teaching Old MLPs New Tricks Via Distillation. ICLR Shichang Zhang, Yozen Liu, Yizhou Sun, Neil Shah
2022	A	`conf`	Imbalanced Graph Classification via Graph-of-Graph Neural Networks. CIKM Yu Wang, Yuying Zhao, Neil Shah, Tyler Derr
2022	A*	`conf`	Is Homophily a Necessity for Graph Neural Networks? ICLR Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang
2022	A*	`conf`	Joint International Workshop on Misinformation and Misbehavior Mining on the Web & Making a Credible Web for Tomorrow (MIS2-TrueFact). KDD Pamela Bhattacharya, Jing Gao, Meng Jiang, Mehran Kafai, Srijan Kumar, Qi Li, Neil Shah, Sihong Xie, Philip S. Yu, Ming Zeng
2022	J	`jnl`	Link Prediction with Non-Contrastive Learning. CoRR William Shiao, Zhichun Guo, Tong Zhao, Evangelos E. Papalexakis, Yozen Liu, Neil Shah
2022	J	`jnl`	Linkless Link Prediction via Relational Distillation. CoRR Zhichun Guo, William Shiao, Shichang Zhang, Yozen Liu, Nitesh V. Chawla, Neil Shah, Tong Zhao
2022	J	`jnl`	MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization. CoRR Xiaotian Han, Tong Zhao, Yozen Liu, Xia Hu, Neil Shah
2022	J	`jnl`	Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization. CoRR Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, Chuxu Zhang
2022	A	`conf`	Sunshine with a Chance of Smiles: How Does Weather Impact Sentiment on Social Media? ICWSM Julie Jiang, Nils Murrugarra-Llerena, Maarten W. Bos, Yozen Liu, Neil Shah, Leonardo Neves, Francesco Barbieri
2022	A	`conf`	The 1st International Workshop on Federated Learning with Graph Data (FedGraph). CIKM Carl Yang, Xiaoxiao Li, Nathalie Baracaldo, Neil Shah, Chaoyang He, Lingjuan Lyu, Lichao Sun, Salman Avestimehr
2021	A	`conf`	A Unified View on Graph Neural Networks as Graph Signal Denoising. CIKM Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang, Neil Shah
2021	A	`conf`	Action Sequence Augmentation for Early Graph-based Anomaly Detection. CIKM Tong Zhao, Bo Ni, Wenhao Yu, Zhichun Guo, Neil Shah, Meng Jiang
2021	A*	`conf`	AdverTiming Matters: Examining User Ad Consumption for Effective Ad Allocations on Social Media. CHI Koustuv Saha, Yozen Liu, Nicholas Vincent, Farhan Asif Chowdhury, Leonardo Neves, Neil Shah, Maarten W. Bos
2021	J	`jnl`	Attributed Graph Modeling with Vertex Replacement Grammars. CoRR Satyaki Sikdar, Neil Shah, Tim Weninger
2021	J	`jnl`	Automated Self-Supervised Learning for Graphs. CoRR Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang
2021	A	`conf`	CEAM: The Effectiveness of Cyclic and Ephemeral Attention Models of User Behavior on Social Platforms. ICWSM Farhan Asif Chowdhury, Yozen Liu, Koustuv Saha, Nicholas Vincent, Leonardo Neves, Neil Shah, Maarten W. Bos
2021	J	`jnl`	Crime forecasting: a machine learning and computer vision approach to crime prediction and prevention. Vis. Comput. Ind. Biomed. Art Neil Shah, Nandish Bhagat, Manan Shah
2021	A*	`conf`	Data Augmentation for Graph Neural Networks. AAAI Tong Zhao, Yozen Liu, Leonardo Neves, Oliver J. Woodford, Meng Jiang, Neil Shah
2021	C	`conf`	FairOD: Fairness-aware Outlier Detection. AIES Shubhranshu Shekhar, Neil Shah, Leman Akoglu
2021	J	`jnl`	Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs. CoRR Hyeonjeong Shin, Taehyung Kwon, Neil Shah, Kijung Shin
2021	J	`jnl`	From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness. CoRR Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah
2021	J	`jnl`	Graph Condensation for Graph Neural Networks. CoRR Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah
2021	A*	`conf`	Graph Neural Networks for Friend Ranking in Large-scale Social Platforms. WWW Aravind Sankar, Yozen Liu, Jun Yu, Neil Shah
2021	J	`jnl`	Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation. CoRR Shichang Zhang, Yozen Liu, Yizhou Sun, Neil Shah
2021	A	`conf`	Identifying Misinformation from Website Screenshots. ICWSM Sara Abdali, Rutuja Gurav, Siddharth Menon, Daniel Fonseca, Negin Entezari, Neil Shah, Evangelos E. Papalexakis
2021	J	`jnl`	Identifying Misinformation from Website Screenshots. CoRR Sara Abdali, Rutuja Gurav, Siddharth Menon, Daniel Fonseca, Negin Entezari, Neil Shah, Evangelos E. Papalexakis
2021	J	`jnl`	Imbalanced Graph Classification via Graph-of-Graph Neural Networks. CoRR Yu Wang, Yuying Zhao, Neil Shah, Tyler Derr
2021	J	`jnl`	Is Homophily a Necessity for Graph Neural Networks? CoRR Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang
2021	J	`jnl`	KNH: Multi-View Modeling with K-Nearest Hyperplanes Graph for Misinformation Detection. CoRR Sara Abdali, Neil Shah, Evangelos E. Papalexakis
2021	A	`conf`	NED: Niche Detection in User Content Consumption Data. CIKM Ekta Gujral, Leonardo Neves, Evangelos E. Papalexakis, Neil Shah
2021	A	`conf`	Online Communication Shifts in the Midst of the Covid-19 Pandemic: A Case Study on Snapchat. ICWSM Qi Yang, Weinan Wang, Lucas Pierce, Rajan Vaish, Xiaolin Shi, Neil Shah
2021	A*	`conf`	The Second International MIS2 Workshop: Misinformation and Misbehavior Mining on the Web. KDD Aude Hofleitner, Meng Jiang, Srijan Kumar, Neil Shah, Kai Shu
2020	J	`jnl`	A Large-Scale Analysis of Attacker Activity in Compromised Enterprise Accounts. CoRR Neil Shah, Grant Ho, Marco Schweighauser, M. H. Afifi, Asaf Cidon, David A. Wagner
2020	J	`jnl`	A Unified View on Graph Neural Networks as Graph Signal Denoising. CoRR Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang, Neil Shah
2020	J	`jnl`	Data Augmentation for Graph Neural Networks. CoRR Tong Zhao, Yozen Liu, Leonardo Neves, Oliver J. Woodford, Meng Jiang, Neil Shah
2020	J	`jnl`	FAIROD: Fairness-aware Outlier Detection. CoRR Shubhranshu Shekhar, Neil Shah, Leman Akoglu
2020	J	`jnl`	HiJoD: Semi-Supervised Multi-aspect Detection of Misinformation using Hierarchical Joint Decomposition. CoRR Sara Abdali, Neil Shah, Evangelos E. Papalexakis
2020	—	`conf`	Impact of Minimum Hyperspherical Energy Regularization on Time-Frequency Domain Networks for Singing Voice Separation. APSIPA Neil Shah, Dharmeshkumar M. Agrawal
2020	A*	`conf`	Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps. KDD Xianfeng Tang, Yozen Liu, Neil Shah, Xiaolin Shi, Prasenjit Mitra, Suhang Wang
2020	J	`jnl`	Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps. CoRR Xianfeng Tang, Yozen Liu, Neil Shah, Xiaolin Shi, Prasenjit Mitra, Suhang Wang
2020	—	`conf`	Minority Reports Defense: Defending Against Adversarial Patches. ACNS Workshops Michael McCoyd, Won Park, Steven Chen, Neil Shah, Ryan Roggenkemper, Minjune Hwang, Jason Xinyu Liu, David A. Wagner
2020	J	`jnl`	Minority Reports Defense: Defending Against Adversarial Patches. CoRR Michael McCoyd, Won Park, Steven Chen, Neil Shah, Ryan Roggenkemper, Minjune Hwang, Jason Xinyu Liu, David A. Wagner
2020	—	`conf`	Query-By-Example Spoken Term Detection Using Generative Adversarial Network. APSIPA Neil Shah, Sreeraj R, Maulik C. Madhavi, Nirmesh J. Shah, Hemant A. Patil
2020	—	`conf`	Semi-supervised Multi-aspect Detection of Misinformation Using Hierarchical Joint Decomposition. ECML/PKDD (5) Sara Abdali, Neil Shah, Evangelos E. Papalexakis
2020	A	`conf`	Social Factors in Closed-Network Content Consumption. CIKM Parisa Kaghazgaran, Maarten W. Bos, Leonardo Neves, Neil Shah
2020	B	`conf`	The Devil is in the Details: Evaluating Limitations of Transformer-based Methods for Granular Tasks. COLING Brihi Joshi, Neil Shah, Francesco Barbieri, Leonardo Neves
2020	J	`jnl`	The Devil is in the Details: Evaluating Limitations of Transformer-based Methods for Granular Tasks. CoRR Brihi Joshi, Neil Shah, Francesco Barbieri, Leonardo Neves
2019	B	`conf`	Characterizing and detecting livestreaming chatbots. ASONAM Shreya Jain, Dipankar Niranjan, Hemank Lamba, Neil Shah, Ponnurangam Kumaraguru
2019	—	`conf`	Cybersafety 2019: The 4th Workshop on Computational Methods in Online Misbehavior. WWW (Companion Volume) Richard Han, Neil Shah
2019	B	`conf`	FARE: Schema-Agnostic Anomaly Detection in Social Event Logs. DSAA Neil Shah
2019	A*	`conf`	Impact of Contextual Factors on Snapchat Public Sharing. CHI Hana Habib, Neil Shah, Rajan Vaish
2019	J	`jnl`	Impact of Contextual Factors on Snapchat Public Sharing. CoRR Hana Habib, Neil Shah, Rajan Vaish
2019	A*	`conf`	Modeling Dwell Time Engagement on Visual Multimedia. KDD Hemank Lamba, Neil Shah
2019	B	`conf`	SliceNDice: Mining Suspicious Multi-Attribute Entity Groups with Multi-View Graphs. DSAA Hamed Nilforoshan, Neil Shah
2019	J	`jnl`	SliceNDice: Mining Suspicious Multi-attribute Entity Groups with Multi-view Graphs. CoRR Hamed Nilforoshan, Neil Shah
2019	J	`jnl`	Thrombophilia testing in the inpatient setting: impact of an educational intervention. BMC Medical Informatics Decis. Mak. Henry Kwang, Eric Mou, Ilana Richman, Andre Kumar, Caroline Berube, Rajani Kaimal, Neera Ahuja, Stephanie Harman, Tyler Johnson, Neil Shah, Ronald Witteles, Robert Harrington, Lisa Shieh, Jason Hom
2018	—	`conf`	Beyond Outlier Detection: LookOut for Pictorial Explanation. ECML/PKDD (1) Nikhil Gupta, Dhivya Eswaran, Neil Shah, Leman Akoglu, Christos Faloutsos
2018	J	`jnl`	Did We Get It Right? Predicting Query Performance in E-commerce Search. CoRR Rohan Kumar, Mohit Kumar, Neil Shah, Christos Faloutsos
2018	—	`conf`	Did We Get It Right? Predicting Query Performance in e-Commerce Search. eCOM@SIGIR Rohan Kumar, Mohit Kumar, Neil Shah, Christos Faloutsos
2018	A	`conf`	Effectiveness of Generative Adversarial Network for Non-Audible Murmur-to-Whisper Speech Conversion. INTERSPEECH Neil Shah, Nirmesh J. Shah, Hemant A. Patil
2018	J	`jnl`	False Information on Web and Social Media: A Survey. CoRR Srijan Kumar, Neil Shah
2018	—	`conf`	Novel Inter Mixture Weighted GMM Posteriorgram for DNN and GAN-based Voice Conversion. APSIPA Nirmesh J. Shah, R. Sreeraj, Neil Shah, Hemant A. Patil
2018	—	`conf`	Novel Spectral Root Cepstral Features for Replay Spoof Detection. APSIPA Prasad A. Tapkir, Ankur T. Patil, Neil Shah, Hemant A. Patil
2018	J	`jnl`	Reducing large graphs to small supergraphs: a unified approach. Soc. Netw. Anal. Min. Yike Liu, Tara Safavi, Neil Shah, Danai Koutra
2018	B	`conf`	Semi-supervised Content-Based Detection of Misinformation via Tensor Embeddings. ASONAM Gisel Bastidas Guacho, Sara Abdali, Neil Shah, Evangelos E. Papalexakis
2018	J	`jnl`	Semi-supervised Content-based Detection of Misinformation via Tensor Embeddings. CoRR Gisel Bastidas Guacho, Sara Abdali, Neil Shah, Evangelos E. Papalexakis
2018	—	`conf`	Time-Frequency Mask-based Speech Enhancement using Convolutional Generative Adversarial Network. APSIPA Neil Shah, Hemant A. Patil, Meet H. Soni
2018	Misc	`conf`	Time-Frequency Masking-Based Speech Enhancement Using Generative Adversarial Network. ICASSP Meet H. Soni, Neil Shah, Hemant A. Patil
2017	A*	`conf`	FLOCK: Combating Astroturfing on Livestreaming Platforms. WWW Neil Shah
2017	J	`jnl`	Graph-Based Fraud Detection in the Face of Camouflage. ACM Trans. Knowl. Discov. Data Bryan Hooi, Kijung Shin, Hyun Ah Song, Alex Beutel, Neil Shah, Christos Faloutsos
2017	J	`jnl`	LookOut on Time-Evolving Graphs: Succinctly Explaining Anomalies from Any Detector. CoRR Nikhil Gupta, Dhivya Eswaran, Neil Shah, Leman Akoglu, Christos Faloutsos
2017	B	`conf`	M3A: Model, MetaModel and Anomaly Detection for Inter-arrivals of Web Searches and Postings. DSAA Da-Cheng Juan, Neil Shah, Mingyu Tang, Zhiliang Qian, Diana Marculescu, Christos Faloutsos
2017	J	`jnl`	OEC: Open-Ended Classification for Future-Proof Link-Fraud Detection. CoRR Neil Shah, Hemank Lamba, Alex Beutel, Christos Faloutsos
2017	J	`jnl`	On Summarizing Large-Scale Dynamic Graphs. IEEE Data Eng. Bull. Neil Shah, Danai Koutra, Lisa Jin, Tianmin Zou, Brian Gallagher, Christos Faloutsos
2017	A*	`conf`	The Many Faces of Link Fraud. ICDM Neil Shah, Hemank Lamba, Alex Beutel, Christos Faloutsos
2016	A	`conf`	BIRDNEST: Bayesian Inference for Ratings-Fraud Detection. SDM Bryan Hooi, Neil Shah, Alex Beutel, Stephan Günnemann, Leman Akoglu, Mohit Kumar, Disha Makhija, Christos Faloutsos
2016	J	`jnl`	DeltaCon: Principled Massive-Graph Similarity Function with Attribution. ACM Trans. Knowl. Discov. Data Danai Koutra, Neil Shah, Joshua T. Vogelstein, Brian Gallagher, Christos Faloutsos
2016	—	`conf`	EdgeCentric: Anomaly Detection in Edge-Attributed Networks. ICDM Workshops Neil Shah, Alex Beutel, Bryan Hooi, Leman Akoglu, Stephan Günnemann, Disha Makhija, Mohit Kumar, Christos Faloutsos
2016	J	`jnl`	FLOCK: Combating Astroturfing on Livestreaming Platforms. CoRR Neil Shah
2016	A*	`conf`	FRAUDAR: Bounding Graph Fraud in the Face of Camouflage. KDD Bryan Hooi, Hyun Ah Song, Alex Beutel, Neil Shah, Kijung Shin, Christos Faloutsos
2016	J	`jnl`	M3A: Model, MetaModel, and Anomaly Detection in Web Searches. CoRR Da-Cheng Juan, Neil Shah, Mingyu Tang, Zhiliang Qian, Diana Marculescu, Christos Faloutsos
2015	J	`jnl`	An Empirical Comparison of the Summarization Power of Graph Clustering Methods. CoRR Yike Liu, Neil Shah, Danai Koutra
2015	J	`jnl`	BIRDNEST: Bayesian Inference for Ratings-Fraud Detection. CoRR Bryan Hooi, Neil Shah, Alex Beutel, Stephan Günnemann, Leman Akoglu, Mohit Kumar, Disha Makhija, Christos Faloutsos
2015	J	`jnl`	EdgeCentric: Anomaly Detection in Edge-Attributed Networks. CoRR Neil Shah, Alex Beutel, Bryan Hooi, Leman Akoglu, Stephan Günnemann, Disha Makhija, Mohit Kumar, Christos Faloutsos
2015	—	`conf`	ND-Sync: Detecting Synchronized Fraud Activities. PAKDD (2) Maria Giatsoglou, Despoina Chatzakou, Neil Shah, Alex Beutel, Christos Faloutsos, Athena Vakali
2015	—	`conf`	Retweeting Activity on Twitter: Signs of Deception. PAKDD (1) Maria Giatsoglou, Despoina Chatzakou, Neil Shah, Christos Faloutsos, Athena Vakali
2015	J	`jnl`	S-index: Towards Better Metrics for Quantifying Research Impact. CoRR Neil Shah, Yang Song
2015	A*	`conf`	TimeCrunch: Interpretable Dynamic Graph Summarization. KDD Neil Shah, Danai Koutra, Tianmin Zou, Brian Gallagher, Christos Faloutsos
2014	A*	`conf`	Spotting Suspicious Link Behavior with fBox: An Adversarial Perspective. ICDM Neil Shah, Alex Beutel, Brian Gallagher, Christos Faloutsos
2014	J	`jnl`	Spotting Suspicious Link Behavior with fBox: An Adversarial Perspective. CoRR Neil Shah, Alex Beutel, Brian Gallagher, Christos Faloutsos
2013	J	`jnl`	ALACRITY: Analytics-Driven Lossless Data Compression for Rapid In-Situ Indexing, Storing, and Querying. Trans. Large Scale Data Knowl. Centered Syst. John Jenkins, Isha Arkatkar, Sriram Lakshminarasimhan, David A. Boyuka II, Eric R. Schendel, Neil Shah, Stéphane Ethier, Choong-Seock Chang, Jackie Chen, Hemanth Kolla, Scott Klasky, Robert B. Ross, Nagiza F. Samatova
2013	—	`conf`	Challenges in understanding clinical notes: why NLP engines fall short and where background knowledge can help. DARE@CIKM Sujan Perera, Amit P. Sheth, Krishnaprasad Thirunarayan, Suhas Nair, Neil Shah
2013	J	`jnl`	ISABELA for effective in situ compression of scientific data. Concurr. Comput. Pract. Exp. Sriram Lakshminarasimhan, Neil Shah, Stéphane Ethier, Seung-Hoe Ku, Choong-Seock Chang, Scott Klasky, Robert Latham, Robert B. Ross, Nagiza F. Samatova
2012	—	`conf`	Analytics-Driven Lossless Data Compression for Rapid In-situ Indexing, Storing, and Querying. DEXA (2) John Jenkins, Isha Arkatkar, Sriram Lakshminarasimhan, Neil Shah, Eric R. Schendel, Stéphane Ethier, Choong-Seock Chang, Jacqueline H. Chen, Hemanth Kolla, Scott Klasky, Robert B. Ross, Nagiza F. Samatova
2012	A*	`conf`	ISOBAR Preconditioner for Effective and High-throughput Lossless Data Compression. ICDE Eric R. Schendel, Ye Jin, Neil Shah, Jackie Chen, Choong-Seock Chang, Seung-Hoe Ku, Stéphane Ethier, Scott Klasky, Robert Latham, Robert B. Ross, Nagiza F. Samatova
2012	C	`conf`	Improving I/O Throughput with PRIMACY: Preconditioning ID-Mapper for Compressing Incompressibility. CLUSTER Neil Shah, Eric R. Schendel, Sriram Lakshminarasimhan, Saurabh V. Pendse, Terry Rogers, Nagiza F. Samatova
2011	—	`conf`	Compressing the Incompressible with ISABELA: In-situ Reduction of Spatio-temporal Data. Euro-Par (1) Sriram Lakshminarasimhan, Neil Shah, Stéphane Ethier, Scott Klasky, Robert Latham, Robert B. Ross, Nagiza F. Samatova
2011	A*	`conf`	S-preconditioner for Multi-fold Data Reduction with Guaranteed User-Controlled Accuracy. ICDM Ye Jin, Sriram Lakshminarasimhan, Neil Shah, Zhenhuan Gong, Choong-Seock Chang, Jackie Chen, Stéphane Ethier, Hemanth Kolla, Seung-Hoe Ku, Scott Klasky, Robert Latham, Robert B. Ross, Karen Schuchardt, Nagiza F. Samatova
2009	Misc	`conf`	Heralding New Ringtones of Patient Safety: Blackberry-based Clinical Communication and Telementoring in Laparoscopic Surgery. AMIA Ogochukwu Azuh, Ayan Sen, Rubinfeld Ilan, Neil Shah, Alton Parker, Dionne Blyden, Autumn Broady, Vic Velanovich, Anthony Falvo, Pat Patton
2009	—	`conf`	PR: Automatic parallelization of data-parallel statistical computing codes for R in hybrid multi-node and multi-core environments. IADIS AC (2) Paul Breimyer, Guruprasad Kora, William Hendrix, Neil Shah, Nagiza F. Samatova