Chathurangi Shyalika

Chathurangi Shyalika is currently a Graduate Research Assistant at the Artificial Intelligence Institute at the University of South Carolina, focusing on rare event prediction and anomaly prediction in manufacturing through advanced techniques such as time series analysis, computer vision models, multimodal AI, deep learning, and knowledge graph modeling. Prior experience includes a role as a Senior Engineer in Big Data and Data Science at Mobitel (Pvt) Ltd, where significant contributions were made to AI projects including customer data churn prediction and broadband tower optimization. Additional experience includes a position as a Software Engineer specializing in Artificial Intelligence at SimCentric Technologies, where work was done on the SmartTrainer project, and an internship at WSO2 developing an XACML Development Tool. Chathurangi holds a Doctor of Philosophy degree in Computer Science from the University of South Carolina, a Master's degree in Artificial Intelligence from the University of Moratuwa, and a Bachelor's degree in Information Technology from General Sir John Kotelawala Defence University, along with multiple certifications.

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Columbia, United States

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Artificial Intelligence Institute at University of South Carolina

The Artificial Intelligence Institute at the University of South Carolina (#AIISC, http://aiisc.ai) conducts core AI research combined with AI applications and impact through extensive interdisciplinary collaborations with most colleges across the university. Led by Prof. Amit Sheth, a researcher, educator, and entrepreneur with a proven leadership record of creating world-class research centers and funding record (> $33 million), the center strives to leverage the comprehensive nature of the university to advance state-of-the-art AI applications in fields like digital and public health, engineering including manufacturing, social sciences, education, communications, autonomous transportation, and personalized security and comfort, while also helping shape and inform the ethics and policies surrounding these emergent solutions.


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51-200

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