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ISTD PhD Oral Defence Seminar by Sai Sathiesh Rajan – Leveraging out of distribution testing to build robust machine learning systems

ISTD PhD Oral Defence Seminar by Sai Sathiesh Rajan – This dissertation serves to remind us of the importance of thoroughly testing machine learning models before deploying them as they can cause societal, economical and reputational damage.

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ISTD PhD Oral Defence Seminar by Jan Melechovsky – Analysis and synthesis of audio with AI: from neurological disease to accented speech and music

ISTD PhD Oral Defence Seminar by Jan Melechovsky – In the modern era, new technology is opening opportunities to help various groups of people around the world. In this thesis, deep learning and audio processing is utilized to target the needs of and develop specific applications for patients with progressive neurological diseases, speakers of non-native English accents, and amateur and leisure musicians and music enjoyers.

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ISTD PhD Oral Defense Seminar by Rulin Chen – Modelling and design of assemblies with discrete equivalence classes

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.

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Congratulations to Assistant Professor Liu Jun and his PhD Student Qu Haoxuan for winning PREMIA Best Student Paper Award

Congratulations to Assistant Professor Liu Jun and his PhD Student Qu Haoxuan for winning PREMIA Best Student Paper Award

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ISTD PhD Oral Defence Seminar by Ong Kian Eng – Towards intelligent analytics for smarter animal behavioural analysis

ISTD PhD Oral Defence Seminar by Ong Kian Eng – Understanding and analysing animal behaviours is crucial for gaining profound insights into the health, needs, and overall well-being of the animal. This involves measuring and monitoring factors such as size, growth, poses, and actions. The analysis of animal behaviour holds significant importance in a wide range of domains and industries, such as livestock farming, veterinary sciences, scientific research, ecological and conservation studies.

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Congratulations to Associate Professor Liu Xiaogang’s PhD Student in Winning the Best Oral Presentation Award

Congratulations to Associate Professor Liu Xiaogang’s PhD Student in Winning the Best Oral Presentation Award

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Congratulations to Srilalitha Gopalakrishnan, ASD PhD candidate, for her appointment as President of the Singapore Institute of Landscape Architects (SILA), 2021-2023

Congratulations to Srilalitha Gopalakrishnan, ASD PhD candidate, for her appointment as President of the Singapore Institute of Landscape Architects (SILA), 2021-2023

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Congratulations to Associate Professor Liu Xiaogang’s PhD Student in winning the Royal Society of Chemistry (RSC) Excellent Student Award

Congratulations to Associate Professor Liu Xiaogang’s PhD Student in winning the Royal Society of Chemistry (RSC) Excellent Student Award

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ISTD PhD Oral Defense Seminar by Haoran Li – Overcoming the limitations of autoregressive and non-autoregressive neural models

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.

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ISTD PhD Oral Defense Seminar by Li Xu – Towards effective, robust, and continual multi-modal learning

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.

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