• 2022 - Now
    PhD in Computer Science
    New York University
  • 2021
    MS in Computer Science
    Arizona State University
  • 2019
    BTech in Electronics and Communication Engineering
    National Institute of Technology Delhi


  • 2023
    Graduate Teaching Assistant
    New York University
    • Assisted with and reviewed research proposals for the course Privacy in the Electronic Society
  • 2020-2022
    Data Scientist
    Atos zData
    • MLOps- As part of my MLOps work, I containerized applications & deployed them using GCP services & on Kubernetes clusters. Also used KServe (for model inferencing), MLflow (model experimentation and tracking), and Kubeflow pipelines for managing ML workflows.
    • Entity Extraction- Used a multi-modal deep learning based architecture to extract data from unstructured pdfs.
    • Constrained Optimization- worked on a constrained optimization problem using mixed integer programming.
    • Retail Video Analytics- Transfer learned a Faster R-CNN based model for object detection. Implemented a deep learning based tracker.
    • Conversational AI Chatbot- Built a chatbot using Rasa Machine Learning Framework and other external APIs (Google Maps API).
    • PII Detection- Developed a Personally Identifiable Information Detection model by fine-tuning a pre-trained model for custom named entity recognition task. The application can be used to detect & mask sensitive data in text files, including files on GCP buckets. I used Apigee for API management and testing.
    • Worked on a scheduling algorithm that matches members with medical service providers within various radii. I used multiprocessing which saved the firm 40 hours of execution time. I managed GCP compute instances, used cloud SQL for PostgreSQL, and used Plotly and Dash framework for developing an interactive web application.
  • 2019-2020
    Graduate Teaching Assistant
    Arizona State University
    • I worked as a Graduate Teaching Assistant for the course Principles of International Business at W. P. Carey School of Business.
    • As part of my work at the Behavioral Research Lab, I worked on an algorithm that categorized open-ended survey responses into two categories using NLP algorithms for topic extraction.
  • 2019-2020
    Research Intern - Software Engineering
    Qatar Computing Research Institute
    • Worked on developing a new dimensionality reduction technique using tree-indexing.
  • 2018 - 2018
    Research Intern - Software Engineering
    Qatar Computing Research Institute
    • Developed a Multi-Lingual Information Retrieval System that retrieves Wikipedia Articles across languages (French, Arabic and English).
    • Used pre-trained Arabic, French and English word embeddings on monolingual vector spaces.
    • Aligned these monolingual vector spaces using Orthogonal Procrustes Alignment Technique to get a multilingual vector space.
    • Used t-SNE technique for dimensionality reduction and Bokeh for visualization purposes.
  • 2017 - 2017
    Research Intern - Software Engineering
    Qatar Computing Research Institute
    • Analyzed different data sets to understand urban dynamics in fast-growing cities. Worked on a platform for integrating data from disparate physical and social sensors and implemented analytical approaches to mine such data and developed two applications as a result -- One, that visualizes various social demographics of Qatar and the other, an application called QEvents which visualizes various events happening in Qatar through a map-centered dashboard.

Academic Projects & Research

  • 2022 - Now
    PhD Research
    • Currently looking at using scalable LLMs to counter propaganda and disinformation online with a focus on analyzing linguistic techniques
    • Research on detecting AI-generated content
    • User Research using Quantitative Methods
    • Fast Semantic Search using high dimensional vectors, Hadoop, Spark, and Milvus (a scalable vector database)
  • 2019 - 2021
    MS Research
    • Continuous Glucose Monitoring & Prediction- Feature engineering of CGM time-series data. Train SVM and K-NN model to understand meal intake pattern. Forecasting of hypoglycemic events using RNN LSTM.
    • Botnet detection on social media- CoorNet algorithm to detect coordinated inauthentic behavior.
    • Pattern recognition- bayesian decision theory based classification use cases.
  • 2015 - 2019
    Undergraduate Research
    • Project 1 - Built a face authenticated and voice-controlled robot that detects objects, and recognizes emotions from facial expressions using deep learning algorithms and models, on Raspberry Pi.
    • Project 2 - Developed a Sign Language Recognition System (using two approaches — sensor-based and image-based)
    • The sensor-based approach involves a glove that converts sign to speech using sensors such as flex sensors, contact sensors, accelerometers and gyroscopes, etc.
    • The image-based approach was implemented with the help of Machine Learning and Computer Vision algorithms.

Honors and Awards

  • 2023
    • GREPSEC VI Grant Recipient
    • USENIX Security '23 Student Grant Recipient
  • 2022
    • NYU School of Engineering Fellowship


  • 2022
    • Machine Learning Engineering for Production (MLOps)
  • 2021
    • Rasa Developer Certification
  • 2020
    • AWS Fundamentals- Addressing Security Risk
  • 2020
    • AWS Fundamentals- Going Cloud-Native
  • 2018
    • Huawei Certified Network Associate


  • 2022
    • Member of AI Ethics Committee - Atos zData
  • 2016-2018
    • Under-Secretary-General, Executive Board Affairs - NITD Model United Nations
  • 2016
    • Human Rights Delegate - BITSMUN
  • 2014
    • Student Volunteer - TEDxBirlaPublicSchool