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Justin Payan
About me
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Posts
portfolio
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publications
Artificial Neural Network Based Water Network State Estimation Tool for Bangalore Inflow System
Published in International Symposium on Lowland Technology, 2016
With Anjana G. Rajakumar, K.R. Sheetal Kumar, and M.S. Mohan Kumar.
Document Representations Using Fine-Grained Topics
Published in Sets & Partitions Workshop at NeurIPS 2019, 2019
With Nicholas Monath and Andrew McCallum.
Online Post-Processing In Rankings For Fair Utility Maximization
Published in International Conference on Web Search and Data Mining (WSDM), 2021
With Ananya Gupta (equal contribution), Eric Johnson (equal contribution), Aditya Roy, Ari Kobren, Swetasudha Panda, Michael Wick, and Jean-Baptiste Tristan.
Towards Realistic Single-Task Continuous Learning Research for NER
Published in Findings of The 2021 Conference on Empirical Methods in Natural Language Processing, 2021
With Yuval Merhav, He Xie, Satyapriya Krishna, Anil Ramakrishna, Mukund Sridhar and Rahul Gupta.
I Will Have Order! Optimizing Orders for Fair Reviewer Assignment
Published in International Joint Conference on Artificial Intelligence (IJCAI), 2022
With Yair Zick.
Relaxations of Envy-Freeness over Graphs
Published in Autonomous Agents and Multiagent Systems 2023 (AAMAS), 2023
With Rik Sengupta and Vignesh Viswanathan.
Graphical House Allocation
Published in Autonomous Agents and Multiagent Systems 2023 (AAMAS), 2023
With Hadi Hosseini, Rik Sengupta, Rohit Vaish, and Vignesh Viswanathan.
Into the Unknown: Assigning Reviewers to Papers with Uncertain Affinities
Published in Symposium of Algorithmic Game Theory 2023 (SAGT), 2023
With Cyrus Cousins and Yair Zick.
InstructExcel: A Benchmark for Natural Language Instruction in Excel
Published in Findings of The 2023 Conference on Empirical Methods in Natural Language Processing, 2023
With Swaroop Mishra, Mukul Singh, Carina Negreanu, Christian Poelitz, Chitta Baral, Subhro Roy, Rasika Chakravarthy, Benjamin Van Durme, and Elnaz Nouri.
Fair and Welfare-Efficient Resource Allocation under Uncertainty
Published in Neural Information Processing Systems, 2024
With Elita Lobo, Cyrus Cousins, and Yair Zick.
Who You Gonna Call? Optimizing Expert Assignment with Predictive Models
Published in Unpublished, 2024
With Cyrus Cousins, Sheshera Mysore, Neha Nayak Kennard, and Yair Zick.
talks
Fair Division of Indivisible Resources
Published:
Presented known results from On Approximately Fair Allocations of Indivisible Goods and The Unreasonable Fairness of Maximum Nash Welfare in the UMass CICS Theory Seminar. Video is available at this link.
teaching
CMPSCI 383: Introduction to Artificial Intelligence (Fall 2018)
Undergraduate course, Teaching assistant, UMass Amherst, 2018
Survey of artificial intelligence for upper-level undergraduates at UMass Amherst. Guest lectured on ethics in AI, held weekly office hours, and graded assignments.
CMPSCI 121: Introduction to Problem Solving with Computers (Fall 2020)
Undergraduate course, Teaching assistant, UMass Amherst, 2020
Introduction to programming using Java for undergraduates. I held weekly office hours, and I graded assignments, projects, and exams.
CMPSCI 590N: Introduction to Numerical Computing with Python (Fall 2020)
Graduate course, Instructor, UMass Amherst, 2020
Six week course for graduate students at UMass Amherst on using Python and libraries such as Numpy for scientific and numerical computing. I was the sole instructor for this course. I designed the syllabus, recorded and uploaded all lectures and demo sessions, designed and graded all assignments and a final project, and held office hours twice weekly.
CMPSCI 611: Advanced Algorithms (Spring 2021)
Graduate course, Teaching assistant, UMass Amherst, 2021
One of 2 required theory core courses for MS/PhD students at UMass Amherst. Covers many important algorithmic concepts by presenting a few examples of each in detail. Topics include: divide and conquer, matroids, matchings, network flow, randomized algorithms, approximation algorithms, and computational complexity. Instructor is Ramesh Sitaraman.
CICS 580: Introduction to Numerical Computing with Python (Fall 2021)
Graduate course, Instructor, UMass Amherst, 2021
Please visit people.cs.umass.edu/~jpayan/cics580.html for the course page.