Contact
- neil at nshah dot net [personal]
- nshah at snap dot com [work]
Location
- 2025 1st Avenue
- Seattle, WA 98121
About Me
I am a Senior Research Scientist at Snap. My work spans the data mining, machine learning, and computational social science domains, specifically in the contexts of understanding and modeling user behavior and misbehavior on social platforms.
Before I joined Snap, I defended my PhD thesis in the Computer Science Department at Carnegie Mellon University, where I worked on discovering and modeling various types of abusive online behaviors as anomaly detection problems in large networks. I was very fortunate to have been advised by Christos Faloutsos.
Prior to this, I received my B.S. in Computer Science from the Department of Computer Science at North Carolina State University. There, I worked with Nagiza Samatova on reduction, indexing and storage systems for large-scale scientific data.
If you would like to learn more about my work, take a look at my publications and CV.
A note to prospective interns:
Please apply on the Snap Research website here,
and e-mail me afterwards.
Recent News
- December 2020: Our paper AdverTiming Matters: Examining User Ad Consumption for Effective Ad Allocations on Social Media was accepted to CHI 2021!
- December 2020: Our exciting new work FairOD: Fairness-aware Outlier Detection is now available as a preprint!
- December 2020: Our paper Data Augmentation for Graph Neural Networks was accepted to AAAI 2021 -- see you over Zoom!
- October 2020: Our exciting new work A Unified View on Graph Neural Networks as Graph Signal Denoising is now available as as preprint!
- September 2020: Our paper The Devil is in the Details: Evaluating Limitations of Transformer-based Methods for Granular Tasks was accepted to COLING 2020 -- see you over Zoom!
- July 2020: Our paper Social Factors in Closed-Network Content Consumption was accepted to CIKM 2020 -- see you over Zoom!
- July 2020: Our paper Identifying Misinformation from Website Screenshots was accepted to ICWSM 2021 -- see you in Venice!
- July 2020: Our paper Scale-Free, Attributed and Class-Assortative Graph Generation to Facilitate Introspection of Graph Neural Networks was accepted to KDD MLG 2020 -- see you over Zoom!
- June 2020: Our exciting new work Data Augmentation for Graph Neural Networks is now available as a preprint!
- June 2020: Our paper Semi-Supervised Multi-aspect Misinformation Detection with Hierarchical Joint Decomposition was accepted to ECML-PKDD 2020 -- see you over Zoom!
- May 2020: Our paper Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps was accepted to KDD 2020 -- see you over Zoom!
- February 2020: I will be chairing the CyberSafety workshop at TheWebConf 2020 -- see you over Zoom!
- October 2019: I will be a keynote speaker and panelist at the Doctoral Consortium at ICDM 2019 -- see you in Beijing!
- July 2019: I will be giving a keynote talk on Outlier Detection for Mining Social Misbehavior at the Learning and Mining for Cybersecurity (LEMINCS) workshop at KDD 2019 -- see you in Anchorage!
- July 2019: Our paper SliceNDice: Mining Suspicious Multi-attribute Entity Groups with Multi-view Graphs was accepted to DSAA 2019 -- see you in Washington, DC!
- July 2019: Our paper FARE: Schema-Agnostic Anomaly Detection in Social Event Logs was accepted to DSAA 2019 -- see you in Washington, DC!
- July 2019: I will be chairing WSDM Cup at WSDM 2020 -- see you in Houston!
- June 2019: Our paper Characterizing and Detecting Livestreaming Chatbots was accepted to ASONAM 2019 -- see you in Vancouver!
- April 2019: Our paper Modeling Dwell Time Engagement on Visual Multimedia was accepted to KDD 2019 -- see you in Anchorage!
- March 2019: Our CHI 2019 paper on Impact
of Contextual Factors on Public Snapchat Sharing
won a Best Paper Honorable Mention award! - December 2018: Our paper Impact of
Contextual Factors on Public Snapchat Sharing
was accepted to CHI 2019 -- see you in Glasgow! - December 2018: Our work on false information with Vagelis Papalexakis was featured on the NVIDIA AI Podcast!
- November 2018: I will be chairing the CyberSafety workshop at WWW 2019 -- see you in San Francisco!
- October 2018: I will be chairing the ASONAM 2019 Industrial Track -- see you in Vancouver!
- September 2018: I will be giving a keynote talk on Lessons I learned during my PhD at the PhD Forum at ECML-PKDD 2019 -- see you in Dublin!
- August 2018: Our work on false information with Vagelis Papalexakis is featured in a Digital Trends article.
- July 2018: I will be giving a keynote talk on Outlier Detection for Mining Social Misbehavior at the Outlier Detection De-constructed (ODD) workshop at KDD 2018 -- see you in London!
- June 2018: Our paper Did We Get It Right? Predicting Query Performance in E-commerce Search was accepted to the eCom Workshop at SIGIR 2018!
- June 2018: Our paper Beyond Outlier Detection: LookOut for Pictorial Explanation was accepted to ECML-PKDD 2018 -- see you in Dublin!
- June 2018: Our paper Semi-supervised Content-based Detection of Misinformation via Tensor Embeddings was accepted to ASONAM 2018 -- see you in Barcelona!
- April 2018: Srijan Kumar and I published a comprehensive survey on characterizing and detecting false information, False Information on Web and Social Media: A Survey. Check it out!
- March 2018: I will be giving a keynote talk on Anomaly Detection on Large Social Graphs at the CyberSafety workshop at WWW 2018 -- see you in Lyon!
- January 2018: Our paper Reducing Large Graphs to Small Supergraphs: A Unified Approach will be published in SNAM 2018!
- December 2017: I have joined Snap Inc as a Research Scientist in Los Angeles, CA!
- October 2017: I successfully defended my thesis, Anomaly Detection in Large Social Graphs, from Carnegie Mellon University's School of Computer Science, advised by Christos Faloutsos.