Professor Zhou Jianying and PhD student Liu Bowen received the best paper award from IEEE DAPPS 2021 – Information Systems Technology and Design (ISTD)

Congratulations to PhD Student Garbelini Matheus Eduardo for winning the Intel Bug Bounty Award – Information Systems Technology and Design (ISTD)

Congratulations to PhD student Tok Yee Ching for his win at The Cybersecurity Awards 2019 – Information Systems Technology and Design (ISTD)

Congratulations to PhD student Hee Ming Shan for obtaining SDSC Dissertion Research Fellowship 2023

ISTD PhD Oral Defense Seminar by Rulin Chen – An assembly comprises parts joined together to achieve a specific form or functionality. Compared to monolithic objects, assemblies have many benefits in terms of fabrication, transportation, and adaptability. Parts of assemblies are always geometrically simple to fabricate with digital techniques, can be efficiently packed for transportation, and offer adaptability through flexible replacement or modification. Hence, assemblies are widely used in our daily lives that most of our consumer products, industry machines, and architectural structures are assemblies.

ISTD PhD Oral Defense Seminar by Haoran Li – Language models are critical to the advancement of natural language processing and general artificial intelligence. In this thesis, we aim to address the limitations of language models, particularly focusing on the exposure bias in Autoregressive (AR) models and the label bias in Non-Autoregressive (NAR) models.

Congratulations to Assistant Professor Liu Jun and his PhD students Xu Li and Li Tianjiao for papers accepted by CVPR 2021 – Information Systems Technology and Design (ISTD)

Congratulations to Assistant Professor Soujanya Poria and his PhD Student Bhardwaj Rishabh for winning Gemma Academic Program GCP credit award

OzCHI is the annual non-profit conference for the Computer-Human Interaction Special Interest Group (CHISIG) and Australia’s leading forum for the latest in HCI research and practice. OzCHI attracts a broad international community of researchers, industry practitioners, academics and students.

ISTD PhD Oral Defense Seminar by Li Xu – In the ever-evolving field of artificial intelligence (AI), deep learning has emerged as a pivotal technique driving remarkable advancements across various domains. Among its many branches, multi-modal learning stands out as a particularly significant approach, which involves integrating and processing information from multiple modalities of data, such as visual content and language information, to enhance the capabilities of AI systems.