1️⃣ I'm a CS grad at University of California, San Diego for Fall 2022. I did my undergraduate in Computer Science and Engineering at SSN College of Engineering, Chennai, India.
2️⃣ I have worked on developing an Optimized Arrhythmia Detection Pipeline for resource-constrained devices, which has been accepted at the 20th International Conference on Machine Learning and Applications (ICMLA), 2021. You can find the code for it here.
3️⃣ I have also worked on another research paper on developing Scalable Machine Learning Architecture for Neonatal Seizure Detection, that has been accepted at the 2nd International Conference on Artificial Intelligence and Signal Processing (AISP), 2022. You can find the implementation for the same here.
4️⃣ I was a Teaching and Research Assistant at Solarillion Foundation where I researched in the area of Signal Processing and Embedded Machine Learning.
5️⃣ My interests include DevOps, Machine Learning, Deep Learning, Explainable AI, and Signal Processing. I am available to make contributions to the Open Source community, so kindly email me for any potential projects 😄!
6️⃣ Check my portfolio website for more details and an updated résumé.
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Focusing
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University of California, San Diego
- San Diego, CA, US
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13:59
(UTC -07:00) - https://vishaln15.github.io
- @vishal15n
- in/vishalnagarajan
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BlogAnalyticsDashboard
BlogAnalyticsDashboard PublicForked from rohithaug/ucsd-shs-viz-tool
UCSD CSE 210 Project
JavaScript
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NeonatalSeizureDetection
NeonatalSeizureDetection PublicImplementation of Neonatal Seizure Detection using EEG signals for deploying on edge devices including Raspberry Pi.
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OptimizedArrhythmiaDetection
OptimizedArrhythmiaDetection PublicCode for Optimized Arrhythmia Detection on Ultra-Edge Devices
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sentiment-analysis
sentiment-analysis PublicA simple Flask web app dockerized and deployed on Google Cloud Platform. Jump to the page below to view the live app.
Python 1
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