Events

ISTD PhD Oral Defence Seminar by Joel Ong – We explore the modern application of deep learning techniques in portfolio construction, presenting innovative methodologies that significantly enhance traditional investment strategies. Central to this research are three advanced frameworks that leverage deep learning to optimize financial portfolios.

It’s all in the mix: Wasserstein machine learning with mixed features

ISTD PhD Oral Defence Seminar by Perry Lam – Neural networks are known to be over-parametrised and sparse models have been shown to perform as well as dense models over a range of image and language processing tasks. However, while compact representations and model compression methods have been applied to speech tasks, sparsification techniques have rarely been used on text-to-speech (TTS) models. We seek to characterise the impact of selected sparse techniques on the performance and model complexity.

ISTD PhD Oral Defense Seminar by Gong Jia – 3D digital human has been widely used in fields like virtual reality, fashion, and film/game production. Traditionally, creating and animating digital humans requires skilled engineers and expensive equipment, typically accessible only to large companies. Thus, developing deep learning tools to democratize the creation and animation of digital humans is urgently needed.

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.

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.

Urban Larsson (IIT Bombay, India) – The Fundamental Theorem of Normal Play

Yuanwei Liu (Queen Mary University of London) – Near-field Communications: What Will be Different?

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 Menglin Li – Social media has become an integral part of daily life, leading to an explosion of social data. Geographical information within social media is essential for applications such as location-based analysis, recommendations, and targeted advertising. However, such information is sparse, prompting the exploration of mining it from social media data.