Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Singh, Satyam; Singh, Tanish Pal; Maurya, Ankur; Sinha, Ambrisha; Sharma, Vandana; Singh, Ajay Vikram Title A name given to the resource Leveraging Neural Networks for Personalized Student Engagement and Performance Prediction Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 International Conference on Artificial Intelligence and Machine Vision, AIMV 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/AIMV66517.2025.11203342" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/AIMV66517.2025.11203342</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105021841189?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105021841189?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Singh S., Kalinga Institute of Industrial Technology, Deemed to Be University, Odisha, India; Singh T.P., Kalinga Institute of Industrial Technology, Deemed to Be University, Odisha, India; Maurya A., Bennett University, School of Computer Science Engineering &amp; Technology, India; Sinha A., Galgotias University, School of Education, Greater Noida, India; Sharma V., CHRIST University, Computer Science Department, Bengaluru, India; Singh A.V., Amity University, AIIT, Uttar Pradesh, India Description An account of the resource Neural Networks can be used to predict students' performance and future placement opportunities. Nowadays, it is a really difficult task for students to predict their chances of getting a good campus placement, even if they have prepared well for it. There is an intense competition among peers, and many factors that influence a student's placement. To manage this data and predict their chances, they need a reliable system. In this paper, we discuss a model in which the system focuses on three main areas: predicting placement chances, analyzing skill gaps, and offering personalized recommendations for improvement. The system would predict many potential career paths by analyzing academic records, extracurricular activities, and job market trends, while also highlighting immediate opportunities and long-term growth prospects. The integration of agentic AI further enhances this system by enabling autonomous decision-making and adaptive learning. Which ensures personalized guidance for each student. By dynamically refining the predictions which are based on real-time feedback, agentic AI helps to empower students to proactively navigate their career paths with greater confidence and precision. This approach provides a genuine solution, in order to improve placement strategies, by ensuring that the students are well-equipped to meet the challenges of the modern workforce. 2025 IEEE. Subject The topic of the resource Agentic AI; Career Paths; Neural networks; Placement prediction; Skill gaps Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833152697-9; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online