Machine Learning Research Assistant at Columbia Spoken Language Processing Group
San Francisco, California, United States
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Summary
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Senior
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Top School
Kaan Donbekci is a machine learning engineer and current MSCS student at Columbia University with eight years of professional experience spanning research and product-focused roles. He develops cross-lingual, multimodal emotion-detection models using transformer-based transfer learning and self-supervised speech representations (Wav2Vec2, RoBERTa, FAb-Net) on a DARPA-funded collaboration across three labs. Previously at Neosensory he built low-latency, privacy-preserving speech recognition for an embedded wristband and led ML infrastructure and two interns, with earlier work compressing and deploying models to microcontrollers. His background in symbolic systems from Stanford and hands-on IoT and behavioral study tooling gives him a rare blend of human-centered research and production ML engineering. He’s currently exploring audio-first data management and MLOps practices to streamline model building across multimodal pipelines.
8 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Columbia University
High School, High School at Robert College
Bachelor of Science - BS, Symbolic Systems, Bachelor of Science - BS, Symbolic Systems at Stanford University
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Kaan Donbekci - Machine Learning Research Assistant at Columbia Spoken Language Processing Group