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Zoom Education Suite, an add-on to Zoom calls that my team and I built as part of HooHacks 2020


An AI that attempts to find the treasure in an OpenAI gym envionment

Work Experience

Toyon Research Corporation


  • C++
  • PyTorch
  • Computer Vision
  • NLP

Multimodal Research

December, 2022

Advised by Professor Srijan Kumar and working with Gaurav Verma at Georiga Tech on multimodal system robustness.

• Implemented an adversarial approach that utilizes XLAN and Meshed Memory image captioning models to test the robustness of current multimodal models on the CrisisMMD Dataset.
• Using Bottom-Up Attention, BERT, CLIP, and NLTK to create image relevant text augmentations for multimodal models like CLIP. This work led to our paper at ACL'23 titled: "Cross-Modal Attribute Insertions for Assessing the Robustness of Vision-and-Language Learning"

  • PyTorch
  • Multimdodal
  • NLP


August, 2022

Developed algorithms and methods using deep learning approaches for automatic video segmentation/chapetering.

• Designed various pipelines, supervised and unsupervised, for topic segmentation of video transcripts to detect important points/segments of time within videos.
• Implemented and modified recent segmentation methods using pre-trained language models and PyTorch. These models ranged from Text Tiling as a baseline to hierarchical BERT style models.
• Processed publicly available meeting and article corpora to evaluate approaches using multiple segmentation metrics on top of common classification metrics.
• Presented these results alongside a qualitative assessment to highlight the challenges and successes that come with each approach.

  • PyTorch
  • Multimodal
  • NLP
  • AWS Sagemaker

Brain Technologies, Inc.

August, 2021

Worked with a small team to create a Flask app using GPT-3 for query analysis and refinement in order to make recommendations on food and products.

• Used NLP libraries (SpaCy, NLTK, etc.) alongside GPT-3 and prebuilt models for named entity recognition, question-answering, and relevancy filtering on both queries and reviews.
• Built models such as bidirectional RNNs in Tensorflow as well as pretrained task-agnostic/task-specific BERT models for intent recognition and vague/non-vague classification.
• Integrated recommendation components with production app by configuring an API.

  • Python
  • PyTorch
  • Tensorflow
  • GPT-3
  • AWS

Recommendation System Research

May, 2020

Working with Professor Hongning Wang and graduate student Renqin Cai at UVa on popularity bias in recommendation models.

• Implemented pipeline for both RNN and Self-Attention models which includes metrics, data preprocessing, training, evaluation, and the models themselves.
• Assessed bias in and more interestingly in testing, where sequential predictions in the RNN would impact the bias over time.
• Created evaluation metric called "temporal discounting" to assess popularity bias in sequential models, which will allow for debiasing architectures to be developed.

  • Python
  • PyTorch
  • CUDA


August, 2020

Worked as a full-stack software dev and product owner to create a COVID-19 dashboard where managers and directors could learn more about the virus as it pertains to their direct reports and/or the company as a whole.

• Set up a CI/CD pipeline through Jenkins to Openshift
• Created and maintained our MongoDB on top of constructing our ML pipeline
• Worked with express in NodeJS to set up endpoints for our data as well as harnessed active directory(LDAP) to collect location and direct reports of our users
• Contributed in building the web app using Angular, in which I utilized D3 to create and interactiveUS map, integrated single sign-on, and used Optum’s own UI toolkit for various components

  • NodeJS
  • Tensorflow
  • MongoDB
  • D3JS
  • Angular