I am an M.S. in Electrical Engineering student at Stanford University and my research interests include interpretable machine learning, deep learning and NLP. For the last 2 years, I have been working at Microsoft as a Data and Applied Scientist in the Cybersecurity research team. Previously, I graduated with a Bachelors degree in Electrical Engineering and a minor in Deep Learning from the Indian Institute of Technology (IIT) Madras. During this time, I pursued research at the intersection of NLP and deep learning that led to publications in top conferences such as ACL, COLING and ALENEX.

Honors & Awards

  • Dr. Dilip Veeraraghavan Memorial Award, IIT Madras (2021)
  • Best Paper Honorable Mention, ACM CODS-COMAD (2021)
  • KVPY Fellowship, Government of India (2017)
  • NTSE Scholarship, Government of India (2015)

Education & Certifications

  • B.Tech, Indian Institute of Technology Madras, Electrical Engineering (2021)

Work Experience

  • Data and Applied Scientist, Microsoft (June 2021 - September 2023)

    • Worked as a researcher at the intersection of data science and cybersecurity, with a focus on OAuth cloud app security.
    • Developed 10 industry-first machine learning solutions spanning knowledge graphs, anomaly detection, computer vision, and NLP to model cyber attack patterns, track app behavior, and avert security threats.
    • Built & deployed models that analyze terabytes of data every day meeting stringent goals on latency and efficacy.
    • Filed a patent, published a paper at MLADS 2022 & received an early promotion for exceptional work.


    Bangalore, India

  • Data and Applied Scientist Intern, Microsoft (May 2020 - July 2020)

    • Developed CNN and Transformer-based deep learning models to analyze multi-spectral satellite images for estimating biomass in agricultural fields and identifying prospective areas for oil exploration.
    • Designed a data structure for the open-source package, xarray to support tree-based hierarchical data storage.


    Hyderabad, India

  • Data Scientist Intern, GE Healthcare (May 2019 - July 2019)

    • Used graph-based keyword clustering and topic ranking to analyze text in service records of healthcare machines.
    • Set up an automated pipeline to flag common failure patterns and suggest quality improvement opportunities.
    • Reduced the time taken to extract insights from service records by 11x and was appreciated by company leaders.


    Bangalore, India

All Publications

  • Input-specific Attention Subnetworks for Adversarial Detection Biju, E., Sriram, A., Kumar, P., Khapra, M. M., Assoc Computa Linguist ASSOC COMPUTATIONAL LINGUISTICS-ACL. 2022: 31-44
  • Vocabulary-constrained Question Generation with Rare Word Masking and Dual Attention Biju, E., ASSOC COMP MACHINERY ASSOC COMPUTING MACHINERY. 2021: 431