University of Massachusetts Amherst
I am a MS/PhD student in computer science at the University of Massachusetts Amherst advised by Professor Andrew McCallum. I am a member of the Information Extraction and Synthesis Laboratory. My research focuses on machine learning and natural language processing. I received my B.S. in computer science and mathematics from Brandeis University in 2013 where I worked with Professors James Storer and Antonella Di Lillo.
Scalable clustering; hierarchical clustering; incremental & online clustering; entity resolution.
KDCOVID - April 2020 - KDCOVID retrieves papers by measuring similarity between queries and sentences in the full text of papers in CORD19 corpus. KDCOVID highlights entities linked to knowledge-bases and drug-gene-disease associations. Developed by Manzil Zaheer, Nicholas Monath, Shehzaad Dhuliawala, Taamannae Taabassum, Rajarshi Das, Bhuwan Dhingra, and Andrew McCallum. [www.kdcovid.nl] [Kaggle submission] [code on github]
Sets & Partitions - December 2019 - The First Workshop on Sets and Partitions, was held as a part of the NeurIPS 2019 conference, focused on models for tasks with set-based inputs/outputs as well as models of partitions and novel clustering methodology. Organized with Manzil Zaheer, Ari Kobren, Junier Oliva, Barnabás Póczos, Ruslan Salakhutdinov, Andrew McCallum.
- Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Ji-Ah Lee, Patrick Flaherty, Kyle Cranmer, Andrew McGregor, Andrew McCallum. Compact Representation of Uncertainty in Hierarchical Clustering. [arxiv]
- Dung Thai, Zhiyang Xu, Nicholas Monath, Boris Veytsman, Andrew McCallum. Using BibTeX to Automatically Generate Labeled Data for Citation Field Extraction. AKBC. 2020 [pdf]
- Derek Tam, Nicholas Monath, Ari Kobren, Andrew McCallum. Predicting Institution Hierarchies with Set-based Models AKBC. 2020. [pdf]
- Derek Tam, Nicholas Monath, Ari Kobren, Aaron Traylor, Rajarshi Das, Andrew McCallum. Optimal Transport-based Alignment of Learned Character Representations for String Similarity. ACL. 2019. [arxiv] [pdf] [code + data]
- Nicholas Monath*, Ari Kobren*, Akshay Krishnamurthy, Michael Glass, Andrew McCallum. Scalable Hierarchical Clustering via Tree Grafting. KDD. 2019 (Oral presentation) (* Equal Contribution). [pdf] [code]
- Nicholas Monath, Manzil Zaheer, Daniel Silva, Andrew McCallum, Amr Ahmed. Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. KDD. 2019. [pdf] [code]
- Nishant Yadav, Ari Kobren, Nicholas Monath, Andrew McCallum. Supervised Hierarchical Clustering with Exponential Linkage. ICML. 2019. [arxiv] [pdf] [code]
- Ari Kobren, Nicholas Monath, Andrew McCallum. Integrating User Feedback under Identity Uncertainty in Knowledge Base Construction. AKBC, 2019. [pdf]
- Craig Greenberg, Nicholas Monath, Ari Kobren, Patrick Flaherty, Andrew McGregor, Andrew McCallum. Compact Representation of Uncertainty In Clustering. NeurIPS 2018. [pdf]
- Bo Xiao, Nicholas Monath, Shankar Ananthakrishnan, Abishek Ravi. Play Duration based User-Entity Affinity Modeling in Spoken Dialog System Interspeech 2018. [pdf]
- Ari Kobren*, Nicholas Monath*, Akshay Krishnamurthy, and Andrew McCallum. A Hierarchical Algorithm for Extreme Clustering . KDD. 2017. (* equal contribution). (Oral Presenation). [pdf] [code] [talk] [promo video]
Workshop & Other Publications
- Nicholas Monath *, Ari Kobren*, Akshay Krishnamurthy, Andrew McCallum. Gradient-based Hierarchical Clustering. NIPS Workshop on Discrete Structures in Machine Learning. 2017. (Oral Presentation). [pdf]
- Ari Kobren, Nicholas Monath, Andrew McCallum. Entity-centric Attribute Feedback for Interactive Knowledge Bases. NIPS Workshop on Automated Knowledge Base Construction. 2017. [pdf]
- Aaron Traylor *, Nicholas Monath *, Rajarshi Das, Andrew McCallum. Learning String Alignments for Entity Aliases. NIPS Workshop on Automated Knowledge Base Construction. 2017. [pdf] [code]
- Haw-Shiuan Chang, Abdurrahman Munir, Ao Liu, Johnny Tian-Zheng Wei, Aaron Traylor, Ajay Nagesh, Nicholas Monath, Patrick Verga, Emma Strubell, and Andrew McCallum. Extracting Multilingual Relations under Limited Resources: TAC 2016 Cold-Start KB construction and Slot-Filling using Compositional Universal Schema. NIST TAC KBP Workshop 2016. Notebook version [pdf]
- Benjamin Roth, Nicholas Monath, David Belanger, Emma Strubell, Patrick Verga and Andrew McCallum Building Knowledge Bases with Universal Schema: Cold Start and Slot-Filling Approaches TAC KBP 2015 Workshop [pdf]
- Nicholas Monath and Andrew McCallum. Discriminative Hierarchical Coreference for Inventor Disambiguation. PatentsView Inventor Disambiguation Technical Workshop. September 2015 [slides] [code]
- Mykel J. Kochenderfer and Nicholas Monath. Data Compression of Optimal Value Functions for Markov Decision Processes Data Compression Conference. Snowbird Utah 2013.
1st place. Inventor Disambiguation Challenge. PatentsView Inventor Disambiguation Technical Workshop. September 2015. [link] [slides] [code]. Our inventor name disambiguation system was integrated into USPTO PatentsView website.
University of Massachusetts Amherst.
Started MS (only) Fall 2013
Entered PhD Fall 2015
Brandeis University. BS 2013. Computer Science and Mathematics.
Scalable Hierarchical Clustering with Tree Grafting KDD 2019. [slides]
Optimal Transport-based Alignment of
Learned Character Representations
for String Similarity ACL 2019. [slides]
A Hierarchical Algorithm for Extreme Clustering KDD 2017. [poster] [slides from UMass Data Science Symposium]
for Inventor Disambiguation PatentsView Inventor Disambiguation Technical Workshop. 2015. [slides]. (Our inventor name disambiguation system received 1st place and is a part of the USPTO PatentsView website).