"AI and machine learning can significantly enhance the user experience within social
networks.
Given our daily reliance on various social platforms, user-generated posts, comments, and
reactions
serve as valuable resources for research purposes. Investigating social networks can lead to
innovative
insights into user data security and privacy, ultimately delivering novel user
experiences."
Ismail Hossain
Ph.D Student
Researcher Assistant, Security and Privacy Enhanced Machine Learning (SUPREME) Lab
ihossain@miners.utep.edu
Curriculum Vitae
Researcher Assistant, Security and Privacy Enhanced Machine Learning (SUPREME) Lab
ihossain@miners.utep.edu
Curriculum Vitae
Upcoming Conferences
| Conference | Cycle | Submission Deadline | Location |
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I am a Ph.D. candidate in Computer Science at the University of Texas at El Paso, conducting research in LLMs, Machine Learning, Deep Learning, Federated Learning, and NLP under Dr. Sajedul Talukder at SUPREME Lab. Previously, I worked as a Senior Software Engineer at Samsung R&D Institute Bangladesh, contributing to web-based tools for 4G and 5G developers in collaboration with Samsung Network Division. My expertise spans full-stack development, competitive programming (Leetcode, Codeforces, Uva, LightOJ etc.), and knowledge-sharing, including training on software engineering and clean coding. Recognized for excellence, I collaborated with Samsung’s Suwon team on projects at Digital City, Korea.
Publications at a glance
Research Domain Interests
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Social Networks
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Health Care
"AI has the ability to analyze big data sets – pulling together patient insights and leading to predictive analysis. Quickly obtaining patient insights helps the healthcare ecosystem discover key areas of patient care that require improvement. Wearable healthcare technology also uses AI to better serve patients." -
Security Enhancements
"AI uses machine learning and deep learning to recognize patterns on the network and cluster them, it will then detect deviations or security incidents from the norm before responding to them. These patterns can help to improve security in the future. Similar potential threats can be detected and blocked early enough."