Current Projects
New York University
Incremental Skill Discovery for RL Agents
I’m working in the CILVR Lab with Prof. Lerrel Pinto on expanding
Citation: Shafiullah et. al., (2022)
Shafiullah,
Nur Muhammad & Lerrel
Pinto
(2022).
One After Another: Learning Incremental Skills for a Changing World.
arXiv preprint arXiv:2203.11176.
https://arxiv.org/abs/2203.11176
’s incremental skill discovery framework to manipulation environments like AllegroHand.
New York University
Speech Recognition for Mandarin Conversations
I’m working with Prof. Michael Picheny on DARPA’s CCU Program to improve speech recognition systems for conversational Mandarin, primarily on the AISHELL4 dataset
(Citation: Fu et. al., 2021
Fu,
Yihui,
Luyao
Cheng,
Shubo
Lv,
Yukai
Jv,
Yuxiang
Kong,
Zhuo
Chen,
Yanxin
Hu,
Lei
Xie,
Jian
Wu,
Hui
Bu &
others
(2021).
AISHELL-4: An Open Source Dataset for Speech Enhancement, Separation, Recognition and Speaker Diarization in Conference Scenario.
arXiv preprint arXiv:2104.03603.
https://arxiv.org/abs/2104.03603
).
Course Projects
New York University
Contrastive Training with Masked Autoencoders
[Report]
Implemented a contrastive loss on Masked Autoencoders
(Citation: He et. al., 2021
He,
Kaiming,
Xinlei
Chen,
Saining
Xie,
Yanghao
Li,
Piotr
Dollár & Ross
Girshick
(2021).
Masked Autoencoders Are Scalable Vision Learners.
arXiv preprint arXiv:2111.06377.
https://arxiv.org/abs/2111.06377
)
Past Projects
Flixstock India
Bust Replacement on Photorealistic Model Images
I worked with StyleGANs to generate bust-level crops of photorealistic model images, making use of techniques like GAN inversion and style mixing. I also used classical methods like MLS
(Citation: Schaefer et. al., 2006
Schaefer,
Scott,
Travis
McPhail & Joe
Warren
(2006).
Image Deformation Using Moving Least Squares. In
ACM SIGGRAPH 2006 Papers. (pp. 533–540).
https://dl.acm.org/doi/10.1145/1179352.1141920
) to create an end-to-end pipeline for bust replacement upto 1024px.
IBM Research
Neural Conversational Question Answering
I worked with Danish Contractor on improving question answering systems on the ShARC dataset
(Citation: Saeidi et. al., 2018
Saeidi,
Marzieh,
Max
Bartolo,
Patrick
Lewis,
Sameer
Singh,
Tim
Rocktäschel,
Mike
Sheldon,
Guillaume
Bouchard & Sebastian
Riedel
(2018).
Interpretation of Natural Language Rules in Conversational Machine Reading.
arXiv preprint arXiv:1809.01494.
https://arxiv.org/abs/1809.01494
). This led to a patent (US 16/892805), and a paper
(Citation: Verma et. al., 2020
Verma,
Nikhil,
Abhishek
Sharma,
Dhiraj
Madan,
Danish
Contractor,
Harshit
Kumar & Sachindra
Joshi
(2020).
Neural Conversational QA: Learning to Reason vs Exploiting Patterns.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP).
https://doi.org/10.18653/v1/2020.emnlp-main.589
).
Even Further
Microsoft Research
Code to Natural Language
[Report]
I worked with Navin Goyal on techniques to describe code (SQL Queries and bash commands in particular) in natural language as part of my undergrad thesis.
IBM Research
Question Generation
[Report]
I worked on improving techniques to generate answerable questions from text.