Neil Shah

3.2k total citations · 1 hit paper
69 papers, 1.4k citations indexed

About

Neil Shah is a scholar working on Artificial Intelligence, Information Systems and Statistical and Nonlinear Physics. According to data from OpenAlex, Neil Shah has authored 69 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Artificial Intelligence, 27 papers in Information Systems and 16 papers in Statistical and Nonlinear Physics. Recurrent topics in Neil Shah's work include Advanced Graph Neural Networks (19 papers), Recommender Systems and Techniques (16 papers) and Complex Network Analysis Techniques (14 papers). Neil Shah is often cited by papers focused on Advanced Graph Neural Networks (19 papers), Recommender Systems and Techniques (16 papers) and Complex Network Analysis Techniques (14 papers). Neil Shah collaborates with scholars based in United States, India and China. Neil Shah's co-authors include Christos Faloutsos, Alex Beutel, Meet Soni, Yozen Liu, Hemant A. Patil, Brian Gallagher, Tong Zhao, Manan Shah, Meng Jiang and Bryan Hooi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers in Human Behavior and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Neil Shah

59 papers receiving 1.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Data Augmentation for Graph Neural Networks

2021 212 citations Tong Zhao, Yozen Liu et al. profile →

Peers

Countries citing papers authored by Neil Shah

Since Specialization

Citations

This map shows the geographic impact of Neil Shah's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Neil Shah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Neil Shah more than expected).

Fields of papers citing papers by Neil Shah

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Neil Shah. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Neil Shah. The network helps show where Neil Shah may publish in the future.

Co-authorship network of co-authors of Neil Shah

This figure shows the co-authorship network connecting the top 25 collaborators of Neil Shah. A scholar is included among the top collaborators of Neil Shah based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Neil Shah. Neil Shah is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Generative Recommendation with Semantic IDs: A Practitioner's Handbook 2025 ·(unknown), (unknown), (unknown), (unknown), Yufeng Wang, Tong Zhao, Neil Shah	0
2	Learning Universal User Representations Leveraging Cross-domain User Intent at Snapchat 2025 ·(unknown), (unknown), (unknown), (unknown), Tong Zhao, (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Neil Shah	1
3	MI4Rec: Pretrained Language Model based Cold-Start Recommendation with Meta-Item Embeddings 2025 ·(unknown), Yaochen Zhu, (unknown), (unknown), Tong Zhao, Neil Shah, Jundong Li	0
4	GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems 2025 ·(unknown), Donald Loveland, (unknown), Yozen Liu, Xin Chen, (unknown), Ali Jadbabaie, (unknown), Neil Shah, Tong Zhao	1
5	FedKDD 2025: The 2025 International Joint Workshop on Federated Learning for Data Mining and Graph Analytics 2025 ·Carl Yang, (unknown), Zhuangdi Zhu, Zheng Xu, (unknown), Nathalie Baracaldo, Neil Shah, A. Salman Avestimehr, Jiayu Zhou	0
6	GiGL: Large-Scale Graph Neural Networks at Snapchat 2025 ·Tong Zhao, Yozen Liu, (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), P. H. Yu, (unknown), (unknown), Neil Shah	1
7	Improving Out-of-Vocabulary Hashing in Recommendation Systems 2025 ·(unknown), (unknown), (unknown), (unknown), Evangelos E. Papalexakis, Tong Zhao, Neil Shah, Yozen Liu	0
8	Advancing NAM-to-Speech Conversion with Novel Methods and the MultiNAM Dataset 2025 ·Neil Shah, Shirish Karande, Vineet Gandhi	0
9	Explainability and Hate Speech: Structured Explanations Make Social Media Moderators Faster 2024 ·(unknown), Leonardo Neves, Neil Shah, Maarten W. Bos, Björn Roß, Mirella Lapata, Francesco Barbieri	2
10	Improving Embedding-Based Retrieval in Friend Recommendation with ANN Query Expansion 2024 ·(unknown), (unknown), Tong Zhao, Yozen Liu, (unknown), (unknown), (unknown), (unknown), Neil Shah, Ganesh Venkataraman	1
11	FedKDD: International Joint Workshop on Federated Learning for Data Mining and Graph Analytics 2024 ·(unknown), Carl Yang, Zhuangdi Zhu, Zheng Xu, Nathalie Baracaldo, Neil Shah, Salman Avestimehr, Jiayu Zhou	0
12	Embedding Based Retrieval in Friend Recommendation 2023 ·(unknown), (unknown), Yozen Liu, (unknown), (unknown), (unknown), Neil Shah, P. H. Yu, (unknown), (unknown), Ganesh Venkataraman, (unknown)	5
13	CARL-G: Clustering-Accelerated Representation Learning on Graphs 2023 ·arXiv (Cornell University) ·(unknown), (unknown), Yozen Liu, Tong Zhao, Neil Shah, Evangelos E. Papalexakis	2
14	Predicting Future Location Categories of Users in a Large Social Platform 2023 ·Proceedings of the International AAAI Conference on Web and Social Media ·(unknown), Yozen Liu, Heinrich Peters, Francesco Barbieri, Neil Shah, Leonardo Neves, Maarten W. Bos	2
15	Are Message Passing Neural Networks Really Helpful for Knowledge Graph Completion? 2023 ·(unknown), (unknown), (unknown), (unknown), Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin	5
16	A Synergistic Approach for Graph Anomaly Detection With Pattern Mining and Feature Learning 2021 ·IEEE Transactions on Neural Networks and Learning Systems ·Tong Zhao, (unknown), Neil Shah, Meng Jiang	34
17	Crime forecasting: a machine learning and computer vision approach to crime prediction and prevention 2021 ·SHILAP Revista de lepidopterología ·Neil Shah, (unknown), Manan Shah	91
18	Time-Frequency Masking-Based Speech Enhancement Using Generative Adversarial Network 2018 ·Meet Soni, Neil Shah, Hemant A. Patil	140
19	On Summarizing Large-Scale Dynamic Graphs. 2017 ·IEEE Data(base) Engineering Bulletin ·Neil Shah, Danai Koutra, (unknown), (unknown), Brian Gallagher, Christos Faloutsos	8
20	D elta C on 2016 ·ACM Transactions on Knowledge Discovery from Data ·Danai Koutra, Neil Shah, Joshua T Vogelstein, Brian Gallagher, Christos Faloutsos	85

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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