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Current role
Senior Research Scientist · Agigo AG
Zürich, Switzerland
Production speech-and-audio LLMs, synthetic conversational data, GPU-efficient multi-client inference.
Experience
Research Engineer · Telepathy Labs
Zürich, Switzerland
Speech recognition, understanding, and generation for conversational AI agents.
ML Engineer Intern · Apple
Cambridge, MA
Discriminative training of language models for ASR on tail named-entity data.
Applied Scientist Intern · Amazon Web Services
Seattle, WA
Joint speech-to-text translation and transcription research. Work published at EMNLP 2023.
PhD Researcher · Idiap Research Institute & EPFL
Martigny, Switzerland
Thesis: "Low-Resource Speech Recognition and Understanding for Challenging Applications." Advised by Dr. Petr Motlicek and Prof. Hervé Bourlard.
Research Engineer · Idiap Research Institute
Martigny, Switzerland
ATCO2 project (SESAR JU · EU Horizon 2020). Automatic speech recognition and contextual understanding for air traffic control.
Education
PhD · EPFL & IDIAP
Lausanne / Martigny, Switzerland
Computer Science. Dissertation on Automatic Speech Recognition for Air Traffic Control, domain shift, self-supervised pretraining, and contextual biasing.
MSc · Erasmus Mundus EU4M
Oviedo, Spain · Nancy, France · Cluj-Napoca, Romania
Mechatronics & Micro-Mechatronics. Thesis on computer vision for breast cancer diagnosis (SBRA EU project, Universidad de Oviedo).
BSc · Universidad Autónoma del Caribe
Barranquilla, Colombia
Mechatronics Engineering.
Awards
- Best Student Paper nominee: Interspeech 2023 (CommonAccent)
- 1st place: International Create Challenge 2020 · HealthTech Award (Groupe Mutuel)
- Erasmus Mundus Scholarship: EU Commission (EU4M programme, 2017)
- DAAD Research Scholarship: Germany (2014)
Skills
Core · Python · PyTorch · SpeechBrain · Kaldi · HuggingFace · LaTeX · Git · Linux · GPU training & inference · LLMs · ASR · TTS · Self-supervised learning · NLP
AI-assisted development · I use agentic coding tools, primarily Claude Code, as a core part of my engineering workflow, applying them from low-level GPU kernels up to high-concurrency serving:
- Kernel development: CUDA Graphs, Triton kernels, and
torch.compilefor GPU-efficient inference - TTS & LLM systems: streaming synthesis, controllability, and omni-modal model serving
- High-concurrency deployment: throughput and latency optimization for multi-client production serving
- Rapid prototyping: from idea to working proof of concept in hours rather than days
- Data curation: large-scale filtering, cleaning, and synthetic data generation pipelines
- Evaluation & infrastructure: automated benchmarking harnesses and reproducible experiment tooling
Languages
Spanish (native) · English (fluent) · French (intermediate)