Portfolio item number 1
Short description of portfolio item number 1
Short description of portfolio item number 1
Short description of portfolio item number 2
Published in International Symposium on Lowland Technology, 2016
With Anjana G. Rajakumar, K.R. Sheetal Kumar, and M.S. Mohan Kumar.
Published in Sets & Partitions Workshop at NeurIPS 2019, 2019
With Nicholas Monath and Andrew McCallum.
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.
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.
Published in International Joint Conference on Artificial Intelligence (IJCAI), 2022
With Yair Zick.
Published in Autonomous Agents and Multiagent Systems 2023 (AAMAS), 2023
With Rik Sengupta and Vignesh Viswanathan.
Published in Autonomous Agents and Multiagent Systems 2023 (AAMAS), 2023
With Hadi Hosseini, Rik Sengupta, Rohit Vaish, and Vignesh Viswanathan.
Published in Symposium of Algorithmic Game Theory 2023 (SAGT), 2023
With Cyrus Cousins and Yair Zick.
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.
Published in Neural Information Processing Systems, 2024
With Elita Lobo, Cyrus Cousins, and Yair Zick.
Published in Unpublished, 2024
With Cyrus Cousins, Sheshera Mysore, Neha Nayak Kennard, and Yair Zick.
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.
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.
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.
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.
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.
Graduate course, Instructor, UMass Amherst, 2021
Please visit people.cs.umass.edu/~jpayan/cics580.html for the course page.