Reinforcement Learning Engineer, PhD Student
Denis Ergashbaev is a PhD candidate at Concordia University in Montreal, where he researches on applications of deep reinforcement learning (RL) to real-world problems. In particular, he is interested in the techniques of intrinsic motivation, self-play, and long-term planning in RL.
Denis transitioned into machine learning after a long career in software development. For over ten years, he had been a software developer in agido GmbH, a German software company. There, he was involved in projects of high complexity, building scalable, resilient, and high-load systems for multiple clients.
In 2015, he graduated with a master’s degree in Artificial Intelligence at Polytechnic University of Catalonia, at a time when deep neural networks were starting to make its strides in the field. He also holds a BSc in Business Computing from Westminster International University in Tashkent, the first international university in Uzbekistan.
Denis grew up in Uzbekistan. His passions for traveling and learning have driven him to attend tech and AI workshops in Russia, Italy, Japan, and Latvia. He also enjoys long hikes and bike rides.