MS in Computer Science @ New York University
Interests: Machine Learning, Open Source Software, System Automation & Architecture
- Languages: Python, C++, Java
- Machine Learning: PyTorch, NumPy, SciPy
- Engineering & Architecture: API Design, System Architecture
- Testing & Workflows:
pytest, Git/GitHub Workflows, CI/CD
ICLR 2026 (Poster) | 3rd Author
Engineering & Data Contributions:
- Data Engineering: Synthesized and processed a substantial volume of high-quality EQ-related dialogue data utilizing an automated LLM TTS voice cloning pipeline, coupled with rigorous manual filtering.
- Evaluation Framework: Designed the multi-level EQ evaluation metrics and programmatically synthesized 100% of the Multiple Choice Questions (MCQs) for the benchmark.
- Infrastructure & Deployment: Participated in the deployment, device handling, and comprehensive evaluation testing of selected baseline PyTorch speech models.
Collaborator @ Human Language Technology Lab (HLT Lab), CUHKSZ
- Partnering with the HLT Lab to train a next-generation speech language model that utilizes both explicit conversational context and implicit acoustic vocal cues (e.g., emotion, sound events) for human-like empathetic interactions.
Lead Developer
- Designed and built an agentic workflow to dynamically construct high-quality benchmarks, solving the latency between rapid LLM iterations and static benchmark updates.


