Bálint Gyires-Tóth

verfied profile

Budapest University of Technology and Economics

I conduct research on fundamental and applied machine learning since 2007. With my leadership, the first Hungarian hidden Markov-model based Text-To-Speech (TTS) system was introduced in 2008. I obtained my PhD degree with summa cum laude in January 2014. Since then, my primary research field is deep learning. My main research interests are sequential data modeling with deep learning and deep reinforcement learning. I also participate in applied deep learning projects, like time series classification and forecast, image and audio classification and natural language processing. I was involved in various successful research and industrial projects. In 2017 I was certified as NVidia Deep Learning Institute (DLI) Instructor and University Ambassador.

My professional interests:

- Machine learning, data science

- Deep learning, deep neural networks

- Convolutional neural networks

- Residual, highway and dense networks
- Deep reinforcement learning
- Time series classification and forecast
- Natural language processing
- Speech technologies
- Signal processing
- Consultant (www.deeplearningoktatas.hu)
- Training and workshops (www.deeplearningoktatas.hu)
- University lecturer (deep learning, human-computer interactions)
- Supervisor of BSc, MSc and PhD students 

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