Hadi Abdi Khojasteh
Hadi is an R&D senior machine learning engineer at the Deltatre group, where he is an integral member of the innovation lab and a fellow at the Sport Experiences unit, based in Czechia and Italy. With a solid academic background, Hadi is a former lecturer at the Institute for Advanced Studies in Basic Sciences (IASBS) in Iran and as a researcher at the Institute of Formal and Applied Linguistics (ÚFAL) at Charles University in Prague. Throughout his career, he has actively participated in numerous industrial projects, collaborating closely with renowned experts in the fields of CV/NLP/HLT/CL/ML/DL. His research focuses on multimodal learning inspired by neural models that are both linguistically motivated and tailored to language and vision, visual reasoning and deep learning. His main research interests are Machine Learning, Deep Learning, Computer Vision, Multimodal Learning and Visual Reasoning while he is experienced in a wide variety of international projects on cutting-edge technologies.
Sessions
This talk explores distillation learning, a powerful technique for compressing and transferring knowledge from larger neural networks to smaller, more efficient ones. It delves into its core components and various applications such as model compression and transfer learning. The speaker aims to simplify the topic for all audiences and provides implementation, demonstrating how to apply distillation learning in real scenarios. Attendees will gain insights into developing efficient neural networks by reviewing the various examples of the complex model. The material will be accessible online for convenient access and understanding.