About me
I'm a recent Master's graduate in Computer Science from Johns Hopkins University, with a specialization in Fullstack Development, Machine Learning, and Computer Vision. Interested in my work? Check out my resume.
During my time at the HEPIUS Innovation Lab, under the guidance of Dr. Amir Manbachi, I focused on applying machine learning techniques to ultrasound images of the spinal cord. My work involved benchmarking state-of-the-art object detection and semantic segmentation models aimed at improving injury localization and anatomical labeling.
I completed my Master's degree in May 2024, capping off an academic journey that was heavily centered around Deep Learning, Advanced Computer Vision techniques, NLP, and the design of ML systems. My undergraduate studies were in Computer Engineering at the University of Mumbai, where I built my technical foundation and developed a keen interest in software development and artificial intelligence.
This site is where I share insights from my academic journey and thoughts on the latest in AI.
What I'm doing
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Computer Vision
Design advanced computer vision solutions using state-of-the-art machine learning models.
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Large Language Models
Develop cutting-edge large language models tailored for high-quality applications.
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Fullstack development
High-quality development of sites at the professional level.
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Data Analysis
Advanced techniques for insightful and actionable results.
Awards
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Joel Dean Teaching Excellency
Honored to have received the Joel Dean Excellence in Teaching Award from Johns Hopkins University for outstanding contributions to computer science education as Lead Teaching Assistant.
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Best Project - NLP Self Supervised Models
Our project demonstrated innovative solutions to recovering prompts used by Large Language Models using Parameter Efficient Fine-Tuning (PEFT) techniques. This recognition is a testament to our team's hard work and the invaluable guidance of Prof. Daniel Khashabi and teaching assistant Jiefu Ou.
