CRISPR technology has enabled cell lineage tracing for complex multicellular organisms
through insertion-deletion mutations of synthetic genomic barcodes during organismal …

This paper studies a general framework for high-order tensor SVD. We propose a new
computationally efficient algorithm, tensor-train orthogonal iteration (TTOI), that aims to …

Six years of doctoral research, and what an incredible ride it has been. The pages of this
dissertation are filled with the fruits of my labour, and it is my absolute pleasure that you are …

In this work, we consider the problem of mode clustering in Markov jump models. This model
class consists of multiple dynamical modes with a switching sequence that determines how …

We study a Markovian agent-based model (MABM) in this paper. Each agent is endowed
with a local state that changes over time as the agent interacts with its neighbours. The …

Predicting stochastic cellular dynamics emerging from chemical reaction networks (CRNs) is
a long-standing challenge in systems biology. Deep learning was recently used to abstract …

We extend the existing theory of formal error bounds for the transient distribution of an
aggregated (or lumped) Markov chain when compared to the transient distribution of the …

Chemical reaction networks are a popular formalism for modeling biological processes
which supports both a deterministic and a stochastic interpretation based on ordinary …

If the state space of a homogeneous continuous-time Markov chain is too large, making
inferences becomes computationally infeasible. Fortunately, the state space of such a chain …

If the state space of a homogeneous continuous-time Markov chain is too large, making
inferences—here limited to determining marginal or limit expectations—becomes …