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My research

Throughout my career, I have been fortunate to contribute to various research directions, including machine translation, natural language processing, imitation learning, reinforcement learning, optimization, offline reinforcement learning, and machine learning infrastructure and systems.  A detailed list of my publications can be found on my Google Scholar page.

Currently, my main research interests are in building scalable machine-learning systems that are aligned with a feedback. The feedback might be coming from either humans or as a result of some form of algorithmic computation. On this page, I also list three pillars of my research that I believe will be crucial to address as we integrate AI algorithms into the real world and societies.

The three research pillars

My Research Vision

Build safe, robust🦾 agents🤖 that can make use of the experiential📝 data efficiently 🏎 to make a positive impact.

Efficiency

Achieving compute and human-like sample efficiency via:

  • Better architectures

  • Hardware-aware algorithms

  • Improved learning paradigms and losses

  • Better test-time decoding algorithms

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© 2024 by Caglar Gulcehre

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