• Architect and contributor of the in-house compiler auto-optimization toolkit
• Proposed, implemented, and maintained Prefect-based distributed computing platform for heterogeneous devices (host, various generations of smartphone platforms)
• Proposed algorithms for compiler auto-optimization,
  boosted the inference speed in 20 ETHZ AI-benchmark models (out of 38)
• Inventor of 4 patents in compiler auto-optimization, efficient and scenario-aware network architecture search (NAS)
• Improved customers AI-model efficiency on time and power via team-developed toolkit

Compiler Auto-Optimization System Design Clean Code Architecture Search Quantization-Aware

• Proposed and refactored model training to Pytorch Lightning for faster development and easier maintenance
• Migrated model training to the official AzureML training pipeline
• Implemented unified multi-vertical document understanding model
  for variaous kinds of documents’ named entity recognition (NER)

Multi-Task Learning CI/CD

As the graduate student

• Graduate Researcher in Speech Processing & Machine Learning Lab,
  supervised by Prof. Hung-Yi Lee
• Researched on low-resource speech recognition and improved the system with gradient-based meta-learning and transfer learning algorithms
• Lead TA of Deep Learning for Human Language Processing (Spring 2020) [CommE5054]

As the network adminstrator

• Managed a 10+ nodes, 20+ GPU Slurm-based computing cluster
• Incorporated netdata to the workstation for real-time monitoring
• Developed automatic health check to improve user/administrator experience

• Researched on generative modeling to develop algorithms enhancing user experience during keyboard usage
• The research results have been incorporated in iOS 13 and published as US patent

Generative Modeling Domain Adaptation Seq2Seq

Exchanged to the department of Comuter Science & Communication (CSC)

• Collections of journeys in Europe [link]
• Life whisper [link]
• Travelling gallery [link]

• Proposed and built the interface between Kaldi & Tensorflow,
  migrating acoustic modeling part to Tensorflow for faster development
• Researched on end-to-end speech recognition based on alignment-free algorithm (CTC)
• Reduced 3% CER on the corpus held by DRC, comparable to the original system

ASR Seq2Seq

• Undergraduate Researcher in Speech Processing & Machine Learning Lab
• Proposed hierarchical attention-based model for TOEFL Listening Comprehension Test by machine
• Researched on self-supervised audio embeddings
• TA of Machine Learning → EE5184 designed assignment