Exploring how AI, multilingual content, and digitized curricula can accelerate vocational training outcomes in Pakistan, featuring live system demonstrations.
Share Progress: Present Ba-Ikhtiyar Jawan progress and practical approaches to curriculum digitization and multimodal learning for TVET.
Live Demonstrations: Showcase AI solutions for manual translation, personalized learning, and Urdu tutoring for underserved learners.
Collect Input: Gather stakeholder feedback to strengthen industry alignment and deployability in offline/edge settings.
Build Roadmaps: Produce actionable recommendations and a short roadmap for partnerships and strategic scaling.
Live showcases of three AI-powered learning systems developed to accelerate and localize technical training.
Adapts learning pathways via learner profiling and recommendation intelligence. Uses bilingual datasets to support automated creation of culturally relevant quizzes, tutorials, and microlearning modules across multiple delivery modes.
Designed for underserved, low-literacy Urdu speakers. Features multimodal text/speech interaction and fine-tuned language models for interactive learning, contributing curated low-resource Urdu datasets to the vocational domain.
Converts degraded, scanned industrial manuals into reliable instructional content. Uses instruction-tuned language models to preserve procedural meaning, technical terminology, and usability even under heavy OCR noise.
Theme: Digitization of TVET through AI-driven adaptive tools, multilingual tutoring, and robust machine translation pipelines.
The leadership and organizing committee behind the Ba-Ikhtiyar Jawan Seminar.
Professor & Associate Dean
SEECS, NUST
Assistant Professor
SEECS, NUST
Associate Professor & HoD Dept. of Computer Science
SEECS, NUST
Partners
This event is funded by the German Academic Exchange Service (DAAD) under the project titled Ba-Ikhtiyar Jawan: Upscaling and Digitization of Vocational Education Curriculum.