I'm an IT undergrad and ML Engineer with research interests in AI/ML, building intelligent systems and full-stack AI applications that solve real-world problems through user-centric solutions. With hands-on experience in web dev, I'm an Amazon ML Summer School(Amazon MLSS) 2026 Scholar, have won 3 hackathons through team collaboration, and have published 2 research papers in applied AI/ML. I'm an active member of Google's Women Techmakers and IEEE Robotics and Automation Society on ML and NVIDIA Developer Community.
Gaining hands-on knowledge in advanced ML, Deep Learning, Generative AI, and LLMs through sessions led by Amazon research scientists.
Implementing advanced feature engineering techniques, including TF-IDF and word representations, to extract highly predictive signals from raw dataset inputs.
Leveraged Python, Pandas, and Scikit-learn to engineer data pipelines, perform exploratory data analysis, and build predictive models for real-world business datasets.
Engineered a vulnerability scanner for Solidity contracts to detect critical flaws like Reentrancy and Access Control.
Resolved bugs and integrated new feature modules across 4 open-source repositories via GitHub.
| Category | Technologies |
|---|---|
| Languages | Python Java C++ SQL JavaScript HTML5 CSS3 |
| Libraries & Frameworks | Scikit-learn PyTorch Pandas NumPy XGBoost Flask FastAPI React OpenAI |
| Tools & Platforms | Amazon AWS Streamlit Git Jupyter Power BI Docker |
When I'm not coding, you'll probably find me drawing, winning debates, reading manga, or strumming guitars every once in a while. I'm a living proof that a human can function with black coffee as their primary blood type. My interests naturally gravitate toward anything that adds to the growing body of Human Knowledge.