Education
- MSc Data Science for Decision Making, Maastricht University | 2025-2027
- GPA: 8.5/10 (Cum Laude)
- Thesis:
- Key courses: Mathematical Optimisation, Computational Statistics, Algorithms for Big Data, Advanced Natural Language Processing, Computer Vision
- BSc Physics and Mathematics, Bangalore University | 2021-2024
- CGPA: 9.6/10
Experience
- Statistics Netherlands (CBS) | February 2026 - August 2026
- Improved prediction accuracy of bio-diversity assessment from RGB aerial images in the Netherlands
- Managed the full data science lifecycle; data collection, preprocessing, feature engineering, and experiment evaluation
- Fine-tuning foundational models and building custom datasets
- Creating new data augmentation techniques for earth observability
Hackathons
-
Veed.io | GenAI and Video Hackathon | Demo
- Maastricht University | Supernova buildathon | Demo
- A note taking platform where students get real-time feedback based on course materials and teachers understand student comprehension
- Built RAG pipelines for checking notes based on provided context in DataStax
- Prosus | AI University Games Hackathon | Demo
- An AI Agent personal assistant that schedules tasks and manages conflicts from natural language voice input and email
- Built Google Calendar integration tool and Gmail notification scheduler agent
Projects
Charismatic leadership tactics assessment
- Created explainable features using various Deep Learning techniques on multi-modal data, and made explainable predictions using Decision Trees on 77 data points
- Responsible for data pre-processing, label generation, gaze tracking, speech processing and correlation analysis
Automatic recommendations of preparatory math courses
Detailed article | YouTube demo
A website that delivers randomized math tests for each student and uses a custom algorithm to send personalized recommendations via email based on their results. This was a group project @ Maastricht University.
- Implemented recommendation algorithm based on custom priority scores
- Created no code-dashboard to help professors analyze all students results (.csv sent in email)
- Contributed to website creation, question generation logic, email delivery and overall debugging
Skills
Programming Languages
- Python, SQL, R, MATLAB
Frameworks and libraries
- NumPy, matplotlib, scikitlearn, PyTorch, OpenCV, LangGraph, HuggingFace, geopandas
Machine Learning
- Supervised, Unsupervised, Self-supervised, Deep Learning, Natural Language Processing, Computer Vision
Certificates
- Machine Learning Operations by Duke University
- HuggingFace AI Agents
- Probability by MIT (EdX)
- IELTS English C2
- CS50 Python
Technical bookshelf
- Introduction to Probability by Dimitri P. Bertsekas and John N. Tsitsiklis
- An Introduction to Statistical Learning with Applications in Python by Gareth James, Daniela Witten, Trevor Hastie Robert Tibshirani and Jonathan Taylor
- Designing Machine Learning Systems by Chip Huyen
- AI Engineering by Chip Huyen
- Designing Data Intensive Applications by Martin Kleppmann