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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Machine Learning
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NLP
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Speech Technology
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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
Generative AI evaluation · Multilingual & cross-lingual NLP · Speech–language integration · Responsible AI
Stockholm, Sweden · Open to research collaborations and engineering roles