Tianle Huang

AI Engineer  ·  MSc in AI & Language, Stockholm University

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I design and build AI systems across the full research-to-deployment cycle. My work spans machine learning foundations, speech processing, and multilingual NLP — with a strong emphasis on rigorous evaluation, reproducibility, and practical deployment.

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Competencies

Machine Learning Statistical & representation learning Classical ML methods Experimental design Evaluation methodology Performance benchmarking

NLP Multilingual embeddings Cross-lingual semantic retrieval Text preprocessing Linguistic feature extraction Generative system evaluation

Speech Technology Automatic Speech Recognition Whisper-based ASR pipelines Speech signal analysis Speech continuation experiments Bias detection in ASR outputs

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Stack

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Projects

Multilingual Retrieval Engine  ·  Python PyTorch HuggingFace

Embedding-based semantic search system for cross-lingual similarity ranking.

• Aligned multilingual vector representations
• Cosine similarity scoring
• Modular, reproducible evaluation pipeline

Speech Bias Evaluation Framework  ·  Python Whisper R

End-to-end pipeline for detecting and quantifying demographic bias in ASR outputs.

• Automated Whisper transcription
• Statistical significance testing (R + Python)
• Reproducible experiment infrastructure

Human–LLM Speech Continuation Study  ·  Python Whisper

Experimental framework for benchmarking generative speech consistency against human baselines.

• Audio segmentation and transcription workflow
• Qualitative + quantitative evaluation design
• Comparative analysis between human and model outputs

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Research Interests

Generative AI evaluation  ·  Multilingual & cross-lingual NLP  ·  Speech–language integration  ·  Responsible AI

_{Stockholm, Sweden  ·  Open to research collaborations and engineering roles}