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@article{206744,
        author = {Namit Jagadeesh and Prof Neetha and Abhishek S Thayyil and Karthik Ajay and Mahammad Mashood},
        title = {Student AI Hub},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {269-275},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206744},
        abstract = {The use of Artificial Intelligence (AI) in the education industry has seen the introduction of numerous systems supporting students with coding, summarization, writing reports, and planning academics. Nevertheless, these systems operate separately, leading to scattered workflow and decreased productivity. The proposed solution of Student AI Hub seems to address this issue by offering a comprehensive multi-model AI platform incorporating multiple education systems under a centrally accessible platform. The platform combines functionality such as code generation, code debugging, summarization of both text and video content, analysis of resumes, and construction of roadmaps, thus making it easier for students to conduct academics more efficiently and easily. Created with the PERN tech stack and incorporated with Large Language Models such as LLaMA, DeepSeek, and Cerebras, the platform offers the capability to use the model freely, with a high level of accuracy and the facility of processing the query in the blink of an eye.},
        keywords = {Artificial Intelligence in Education, Code Generation, Video Summarization, Debugging Tools, Multi-Model AI Platform, Student Productivity, PERN Stack, Resume Analysis, Roadmap Generation.},
        month = {July},
        }