About

I’m an Associate Professor at the School of Computing and AI, Nazarbayev University, where I lead research on deep learning for neural signal processing and brain-computer interfaces (EEG/iEEG). My work spans the full arc from algorithm to deployed system — including a real-time neural decoding system for stroke rehabilitation validated on a clinical cohort.

My research focuses on the hard parts: non-stationary signals, cross-subject and cross-site distribution shift, and models that are fast and reproducible under real-world constraints. I work primarily in PyTorch — transformers, self-supervised and contrastive learning, transfer learning and domain adaptation — backed by rigorous validation.

I’m also deeply engaged with LLMs, multi-agent systems, and AI engineering in practice. And I find teaching genuinely rewarding: turning hard ideas into something a student can actually use.

Contact

Open to collaboration in applied AI, neural engineering, and machine learning. Reach out.