Hi there 👋! I’m an Applied Scientist at Microsoft AI. My interests are in building efficient and interpretable machine learning systems. I earned my Master’s degree at the Language Technologies Institute, Carnegie Mellon University and my Bachelor’s degree in Computer Science and Engineering at PES University. You can find my projects, my publications and my resume.
Currently, my team builds training and evaluation pipelines for ads conversion modeling. I work on distributed data pipelines, large-scale daily re-training, counterfactual modeling, analyzing prediction fluctuations and predicting model behavior. I also enjoy building software frameworks and methods that push efficiency further. Some keywords I’m a fan of: efficiency, interpretability, deep learning systems.
Personal Interests
I believe in the power of visual storytelling and teaching. I enjoy making study notes and I was awarded by PES University’s Department of Computer Science and Engineering for my immense contributions. Feel free to check out my notes! They are categorized by subject – most of them are CS subjects, but some are math/science.
I learn to play the South-Indian instrument Saraswathi Veena in the Carnatic style. I also enjoy cooking and baking quite a bit. I have recently been super into hiking in and around the Seattle area. 🌲
News
- 2025-03: Returning to Microsoft AI as a full-time Applied Scientist
- 2024-12: Graduated with my Master’s from CMU LTI
- 2024-05: Excited to spend my summer at Microsoft AI as an Applied Scientist Intern
- 2023-12: Attending my first NeurIPS
- 2023-08: Starting my Master’s at CMU LTI
- 2023-05: I graduated with my Bachelor’s in Computer Science and Engineering from PES University.
- 2023-01: Spending the next 6 months interning at Apple to work on Applied ML!
Education
Carnegie Mellon University | Pittsburgh, PA
Master of Computational Data Science (MCDS)
Coursework: Intro to Deep Learning (PhD), Intro to ML, On-Device ML (PhD), Cloud Computing, Advanced NLP (PhD)
PES University | Bangalore, India
Bachelor of Technology in Computer Science and Engineering
Awards: Prof. CNR Rao Scholarship (top 2%), Immense Contribution Award