Lyric Generation with Style    [pdf]

• Built a GAN-like neural network model to generate lyric given a style and a topic
• Proposed a novel hierarchical structure for both lyric generation and encoding
• Presented two different evaluation methods to quantitatively measure the authenticity of the generated lyric

Semi-supervised Image Captioning via Reconstruction    [pdf]

• Proposed an end-to-end model that can generate image captions in a semi-supervised way
• Adopted the idea of reconstruction to utilize images without paired captions
• Applied the Gumbel-Softmax approximation to backpropage gradients through word samples during training

Handwritten Chinese Character Generation via Conditional Neural Generative Models    [pdf]

• Exploited generative adversarial networks (GAN), variational auto-encoders (VAE), and their combinations to generate handwritten Chinese characters conditioned on their GBK encodings
• Used PyTorch library to build the neural network models

Evaluating Visual Perception with Bouncing Motion    [pdf]  [code]

• Designed a perceptual experiment and developed a novel interactive interface that supports to investigate human perception to bouncing motions
• Displayed a rigid ball falling and bouncing from a hill to detect a just noticeable range of plausible motions that loosely follow the law of physics
• Validated the experiment design and the interface in piloting studies, providing insights to the theory of perception and physical simulation

Connectionist Temporal Classification for Group Activity Recognition in Videos    [pdf]  [poster]

• Combined VGG Net, recurrent neural network, and connectionist temporal classification (CTC) to recognize a sequence of activities performed by a group of people in a video through supervised learning
• Constructed a new volleyball dataset using the volleyball game videos available on YouTube.

Distributed File System with Transactional Semantics    [code]

• Implemented a distributed file system with transactional semantics following the properties of Atomicity, Consistency, Isolation, and Durability using Java
• Handled omission, byzantine and failstop failures on the client and failstop failures on the server
• Detail specification