Theoretical and Computational Neuroscience Laboratory 

Time-series analysis: Bayesian filtering; topological data analysis 

Deep learning: recurrent neural networks; autoencoders 

Dynamical systems: oscillations; coupled oscillators; whole-brain computational modeling at large scale  

Stochastic processes: queueing theory; multi-timescale stochastic simulations; agent-based modeling 

Parameter estimation: Bayesian inference; global stochastic optimization methods 

Wearable data: Analysis of high-dimensional, noisy data collected from wearable devices

Psychiatry disorders: Wearable-based biomarkers for depression; Computational psychiatry

Neural dynamics: Understanding brain function at multiple scales: molecular, cellular, network, and system levels

Precision medicine: Personalized chronotherapy using wearable technology and systems modeling 

Chronotherapy:  Time-of-day effects of R-CHOP treatment in DLBCL patients; time-of-day effects of tumor resection in GBM patients 

Mammalian circadian rhythms: Transcriptional and post-transcriptional regulatory mechanisms 

Plant circadian rhythms: Post-translational regulation through protein-protein interactions  

p53 oscillation: Impact of DNA damage on p53 oscillations and their interplay with the circadian clock 

Systems pharmacology: Influence of CK1δ/ε inhibitor PF-670462 on circadian rhythms