Agrima Seth

Agrima Seth

Ph.D. student, School of Information

CERN Webfest

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Published:

Created a text summarization and analytics platform that works on top of messaging systems being used at CERN, Switzerland. Programmed various natural language processing and machine learning routines for answering users’ queries (summary, most important chats and keywords). ParityApp

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COVID-19 Risk Calculator

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With the world trying to resume all activities as they were before the COVID-19 pandemic, citizens need to judge their risk levels from gatherings and activities. The numerous determinants and the evolving nature of risk make it confusing for the public to understand the risk from various activities. Hence we created this risk calculator app, the paper was accepted at Nature Scientific Reports.

Anomaly Detection using Machine Learning for Data Quality Monitoring in the CMS Experiment

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The project aims at applying recent progress in Machine Learning techniques to the automation of quality assessment allowing the check of large volumes of data in real-time and improving the ability to detect unexpected features. The test implementation was presented to a panel of Physicist and Computer scientists; I was awarded the 2nd position for my work.

Information Retrieval and Query Reformulation

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Published:

Indexing and evaluating the indexed ClueWeb12-B dataset and wrote an algorithm for automated query reformulation using concepts of graph theory