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publications

Automated, Non-Invasive Artificial Intelligence Machine Learning Method and System for Identifying and Redacting Personally Identifiable Information in a Monitored Environment using Real-Time Sensor Data

The present invention relates to computer security methods and systems, employing artificial intelligence and machine learning, for recording information in an electronic format relating to the individual under care, from a sensor, identifying the individual under care from the information, and redacting information associated with the individual under care before transmitting to the user.

Recommended citation: Turock, David Lawrence, Brockie, Justin Mark, Kelly, James Michael, Robbins, Richard Allen, Wahed, Md Rayed Bin, Mahmud, Rafid Ameer, Hossain, Meheraj, Nandi, Pranjal Kumar, Turock, Heather Anne, Ali, Md. Asif, Schulman Robbins, Jeremy Ian. (2024). "Automated, Non-Invasive Artificial Intelligence Machine Learning Method and System for Identifying and Redacting Personally Identifiable Information in a Monitored Environment using Real-Time Sensor Data," Publication No. US 2024-0212804 A1.
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How Good are LM and LLMs in Bangla Newspaper Article Summarization

Published in 27th International Conference on Pattern Recognition (ICPR), 2024

This paper evaluates the performance of Language Models (LM) and Large Language Models (LLM) in summarizing Bangla newspaper articles.

Recommended citation: Faria Sultana, Md Tahmid Hasan Fuad, Md Fahim, Rahat Rizvi Rahman, Meheraj Hossain, M Ashraful Amin, A K M Mahbubur Rahman, Amin Ahsan Ali. (2024). "How Good are LM and LLMs in Bangla Newspaper Article Summarization," in Proceedings of the 27th International Conference on Pattern Recognition, ICPR 2024.
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teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.