Alexandru Coca
AI Research Engineer at University of Cambridge
London, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolAlexandru Coca is an AI research engineer with eight years’ experience building robust speech and language systems, from neural TTS and ASR to task-oriented dialogue and computational protein design. A Cambridge MPhil scholar and current PhD researcher with award-winning SIGDIAL work, he blends rigorous academic research with hands-on industry impact at Apple, Papercup, Seldon and now Xaira Therapeutics. He contributed core features and distributed backends to the popular alibi explainability library, improving KernelSHAP and anchor algorithms for scalable model explanations. His research focuses on variational inference and Bayesian neural methods to improve robustness and commercial readiness of speech technologies, and he has a track record of turning those ideas into deployable systems. Comfortable across PyTorch/TensorFlow stacks and Kubernetes-based scaling, Alexandru pairs deep model insight with practical engineering for production ML. He also brings multidisciplinary strengths—systems engineering roots, languages skills, and competitive club-level athletics—that shape a resilient, team-oriented approach to research and product development.
8 years of coding experience
4 years of employment as a software developer
Master of Philosophy - MPhil, Machine Learning, Speech and Language Technology, Master of Philosophy - MPhil, Machine Learning, Speech and Language Technology at University of CambridgeNational College "Petru Rares", Suceava, RomaniaMaster’s Degree, Systems Engineering, Master’s Degree, Systems Engineering at University of Warwick
Romanian, English, French
Github Skills (10)
machine-learning10
interpretation10
python10
testing9
integration-testing9
test-unit9
unit-test9
unit-testing9
test-integration9
algorithms8
Programming languages (5)
Github contributions (5)
SeldonIO/alibi
Feb 2020 - Oct 2020
Algorithms for explaining machine learning models
Role in this project:
ML Engineer
ML EngineerContributions:2 releases, 17 reviews, 81 commits in 8 months
Contributions summary:Alexandru focused on enhancing the "alibi" library, which provides algorithms for explaining machine learning models. Their contributions include implementing new methods for sampling from training data, building lookup tables, and improving the anchor explanation functionality. They also introduced unit and integration tests for KernelShap, improved documentation, and refactored KernelShap.
fairness-mlpythoninterpretabilityxaiexplanations
alexcoca/dst
Mar 2022 - Nov 2022
Contributions:200 pushes, 1 branch in 7 months
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