Thao Ha

I graduated from the PhD programme at the Singapore University of Technology and Design (SUTD) in 2022. During my PhD journey, I was under the supervision of Prof. Gemma Roig (in Goethe University Frankfurt, Germany) and Prof. Dorien Herremans (in SUTD).

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My research interests include computer vision, affective computing, and multimodal representation learning.

In addition to doing research, I also enjoy participating in startup projects.

We construct a collection of three datasets (called EmoMV) for affective correspondence learning between music and video modalities. A benchmark deep neural network model for binary affective music-video correspondence classification is also proposed. This proposed benchmark model is then modified to adapt to affective music-video retrieval.

This is an extended version of the paper "AttendAffectNet: Self-Attention based Networks for Predicting Affective Responses from Movies". In addition to visual and audio features, we also use features extracted from video subtitles as the model input. Extensive experiments are also carried out.

We develop a deep neural network namely AttendAffectNet for predicting emotions of movie viewers from different input modalities (video, audio) by using the self-attention mechanism.

We develop and analyze multimodal models for predicting experienced affective responses of viewers watching movie clips. The first model is based on fully connected layers without memory on the time component, while the second one incorporates the sequential dependency with a long shortterm memory recurrent neural network (LSTM).

TA, Introduction to Probability and Statistics, 2018, SUTD

TA, Artificial Intelligence, 2019, SUTD