I am a 4th-year BS-MS student at IISER Pune, studying Data Science and Mathematics. My interest in ML started from curiosity about how recommendation systems work - and grew from there through projects, research, and eventually a published paper.

What I enjoy most is working with real-world datasets - building models, extracting patterns, and finding insights. Whether it is predicting mental health severity from clinical surveys, estimating causal effects from observational data, or detecting sentiment and framing patterns in social media - the problems feel worth solving when the data comes from the real world.

My current work is one such problem - applying large language models to social media content around the Iran crisis, analysing how sentiment and framing shift across thousands of posts over time.

I also enjoy deep learning and computer vision, and building systems that go from raw data all the way to something that works.

Published - Springer, 2026 A Mathematical Stacking Ensemble Model for Prediction of Multiple Mental Disorders Among Students Euro-China Conference on Intelligent Data Analysis (ECC 2025), Ostrava, Czech Republic

Stacking ensemble of 8 ML models for simultaneous prediction of stress, anxiety, and depression severity across 2,029 student records — 96% for stress, 98% for anxiety, 99% for depression.

• Machine learning and statistical modelling
• NLP and large language models
• Deep learning and computer vision
• Causal inference and experimental design
• Computational social science

• Vocal and speech signal processing
• Multimodal learning - video, image, language, and speech
• Real-world deployment and monitoring of ML systems

• Languages: Python, C, C++, SQL
• Libraries: NumPy, Pandas, Matplotlib, Scikit-learn, PyTorch, HuggingFace
• ML/DL: Model building, feature selection, optimization, performance evaluation
• NLP: LLM-based classification, zero-shot methods, RAG systems
• Statistics: Sampling distributions, hypothesis testing, regression analysis, ANOVA
• Systems: FastAPI, Docker, CI/CD, drift monitoring
• Tools: LaTeX, Git, Linux, Excel, PowerPoint

Always open to reading recommendations, paper suggestions, or conversations around any of the areas above. Also open to research opportunities and collaborations - feel free to reach out.