2 citations · 2 across the 1 of their papers we have counts for
6 papers
The Effect of Sensor Fusion on Data-Driven Learning of Koopman Operators
Shara Balakrishnan, Aqib Hasnain, Rob Egbert +1
Dictionary methods for system identification typically rely on one set of measurements to learn governing dynamics of a system. In this paper, we investigate how fusion of output m…
Prediction of fitness in bacteria with causal jump dynamic mode decomposition
Shara Balakrishnan, Aqib Hasnain, Nibodh Boddupalli +3
In this paper, we consider the problem of learning a predictive model for population cell growth dynamics as a function of the media conditions. We first introduce a generic data-d…
A data-driven method for quantifying the impact of a genetic circuit on its host
Aqib Hasnain, Subhrajit Sinha, Yuval Dorfan +12
Genetic circuits are designed to implement certain logic in living cells, keeping burden on the host cell minimal. However, manipulating the genome often will have a significant im…
Steady state programming of controlled nonlinear systems via deep dynamic mode decomposition
Aqib Hasnain, Nibodh Boddupalli, Shara Balakrishnan +1
This paper describes the optimal selection of a control policy to program the steady state of controlled nonlinear systems with hyperbolic fixed points. This work is motivated by t…
Koopman Operators for Generalized Persistence of Excitation Conditions for Nonlinear Systems
Nibodh Boddupalli, Aqib Hasnain, Sai Pushpak Nandanoori +1
It is hard to identify nonlinear biological models strictly from data, with results that are often sensitive to experimental conditions. Automated experimental workflows and liquid…
Optimal reporter placement in sparsely measured genetic networks using the Koopman operator
Aqib Hasnain, Nibodh Boddupalli, Enoch Yeung
Optimal sensor placement is an important yet unsolved problem in control theory. In biological organisms, genetic activity is often highly nonlinear, making it difficult to design…