About me
I am a Master's student in Data Science at Indiana University–Bloomington, with a Bachelor's degree in Information Technology from Dwarkadas J. Sanghvi College of Engineering in Mumbai, India. I am enthusiastic about applying machine learning and data-driven solutions to real-world problems, combining analytical rigor and problem-solving skills.
As an ML intern at AMD, I optimized image preprocessing pipelines to enhance real-time lane detection performance. At Swan Solutions and Services, I developed an ensemble model for aspect-based customer segmentation, enabling more targeted business improvements. My notable projects include creating quantized models for NSFW classification, which achieved faster inference speeds and more efficient model architectures. I also designed an end-to-end ML pipeline for a network security dataset, employing MLOps tools like MongoDB, MLFlow, DagsHub, GitHub CI/CD, Docker, AWS S3, ECR, and EC2. Additionally, I implemented cataract detection using Explainable AI for improved transparency and interpretability and developed a privacy-preserving federated learning framework for medical diagnosis to ensure robust data security. Other key projects include a speech emotion recognition system, a Natural Language SQL query generator for an e-commerce database powered by GCS and Gemini 1.5, and a GCP-based analysis of IPL data. Proficient in machine learning and deep learning frameworks, as well as statistical methods, I am actively advancing my skills in MLOps. My skill set encompasses programming languages, databases, and essential software and cloud tools for data analysis and model development, enabling me to effectively tackle complex problems.
What i'm doing
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Grad Student
Pursuing a MSc in Data Science from Indiana University-Bloomington.
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Currently Learning...
Learning and working with MLOps tools to build end-to-end ML pipelines.
