Milad Lankarany

Dr. Lankarany is an early career investigator with a unique combination of knowledge: he has a PhD in electrical engineering (Concordia University, Montreal, Canada) and expertise in theoretical and computational neuroscience (Post-doc, SickKids, Canada), as well as advanced signal processing and information theory (Industrial Post-doc, Myant Inc). He has 10+ years of experience working with digital and analogue circuits. During his 2 years at the company Myant, he implemented advanced signal processing algorithms on micro-controllers and FPGAs and designed and developed analog circuits for sensing very weak electrophysiological signals (like EEG) using dry electrodes. He also gained experience performing in vitro experiments and using the dynamic clamp technique during his postdoctoral training at the Hospital for Sick Children (SickKids).

Scientist, Krembil Brain Institute, Division of Clinical and Computational Neuroscience, Krembil Research Institute, University Health Network (UHN)
Assistant Professor, Institute of Biomedical Engineering, University of Toronto?
Cross-appointed Faculty, Department of Physiology, University of Toronto
Affiliate Scientist, The KITE Research Institute, UHN

Dr. Lankarany's lab, the Neural System and Brain Signal Processing Lab, develops and uses advanced methods in Computational Neuroscience and Engineering as well as cutting-edge Neurotechnology to uncover information processing mechanisms of neural systems, in order to treat neurological disorders and to advance biologically-inspired computational frameworks.

Yupeng Tian, Srikar Saradhi, Edward Bello, Matthew D Johnson, Gabriele D’Eleuterio, Milos R Popovic, Milad Lankarany (2024). Model-based closed-loop control of thalamic deep brain stimulation. Frontiers in Netowork Physiology, Vol 4, 2024/4/8,
Tian, Y., Murphy, M. J., Steiner, L. A., Kalia, S. K., Hodaie, M., Lozano, A. M., Hutchison, W. D., Popovic, M. R., Milosevic, L., Lankarany, M. (2024). Modeling Instantaneous Firing Rate of Deep Brain Stimulation Target Neuronal Ensembles in the Basal Ganglia and Thalamus. Neuromodulation: Technology at the Neural Interface.
Rezaei MR, Jeoung H, Ghahramani A, Saha U, Bhat V, Popovic MR, Yousefi A, Chen REW, Lankarany M (2023). Inferring cognitive state underlying conflict choices in verbal stroop task using heterogeneous input discriminative-generative decoder model. J Neural Eng. 2023 Jul 20. doi: 10.1088/1741-2552/ace932. Epub ahead of print. PMID: 37473753.
Yupeng Tian, Edward Bello, David Crompton, Suneil K. Kalia, Mojgan Hodaie, Andres M. Lozano, William D. Hutchison, Matthew D. Johnson, Milos R. Popovic, Luka Milosevic, Milad Lankarany, (2023). Uncovering network mechanism underlying thalamic Deep Brain Stimulation using a novel firing rate model. bioRxiv 2023.12.09.570924; doi:
Diaz, A., Lankarany, M. (2023). Graph Representations of iEEG data for Seizure Detection with Graph Neural Networks. bioRxiv 2023.06.02.543277; doi:
Azzalini, L.J., Crompton, D., D’Eleuterio, G.M.T. , Skinner, F., Lankarany, M (2023). Adaptive unscented Kalman filter for neuronal state and parameter estimation. J Comput Neurosci (2023).

Neural Coding, Information Processing, Mathematical Modeling, Adaptive Algorithms, Neuro-technology, Computational Neuroscience, Computational Neuromodulation, Neuro-AI, Neural Data Science

Contact

milad.lakarany@uhn.ca
Personal Website
+1 (416) 634-8194
The Krembil Brain Institute, Krembil Discovery Tower, 4KD-512