I am a first year PhD Student at the Center for Data Science at New York University where I am advised by Prof. He He. My research is broadly in the field of natural language processing and machine learning. I’m currently working on text generation for creative writing tasks and in interactive settings.
Prior to this, I completed my MS in Computer Science at NYU’s Courant Institute of Mathematical Sciences during which I was a Graduate Research Associate at the Center for Social Media and Politics working on political stance classification and multimodel content sharing in online disinformation campaigns. I also interned at LAER.AI in New York City where I did some work on unstructured document retrieval and active learning.
Unsupervised Extractive Summarization with Mutual Information
Vishakh Padmakumar, He He
To appear at EACL 2021
A comparison of methods in political science text classification: Transfer learning language models for politics
Zhanna Terechshenko, Fridolin Linder, Vishakh Padmakumar, Michael Liu, Jonathan Nagler, Josh Tucker, Richard Bonneau
Currently under review at the journal Political Science Research Methods
Multi-Modal Content Similarities in Online Disinformation Campaigns
Cody Buntain, Vishakh Padmakumar, Richard Bonneau, Jonathan Nagler, Josh Tucker
ACM Conference on Collective Intelligence, 2020
A Robust Approach to Open Vocabulary Image Retrieval with Deep Convolutional Neural Networks and Transfer Learning
Vishakh Padmakumar, Rishab Ranga, Srivalya Elluru, Sowmya Kamath S.
2018 Pacific Neighborhood Consortium Annual Conference and Joint Meetings (PNC), IEEE
Counterfactual Logit Pairing with Asymmetric Counterfactuals in Text Classification
Lucius Bynum, Vishakh Padmakumar
Transfer of Reinforcement Learning in a Natural Language Action Space
Vishakh Padmakumar, Francesco Preta