About

Hi, I’m Adam. I work on time series — probabilistic forecasting, state-space modelling, and increasingly the new wave of foundation models that’s reshaping the field. I’ve spent a decade thinking in terms of probabilistic models, Markov modeling, Hierarchical Bayesian Models, Structural Causal Models.

Background

I’m currently a data scientist at Cisco where I apply all this forecasting experience to supply chain optimization problems.

Before Cisco, I was an early employee at deeptech startup causaLens. I also led the data science team at MADE.com (RIP in peace).

The bridge

My PhD was in Computational Chemistry at KCL, supervised by Edina Rosta and Alessia Annibale. The work was Markov modelling of protein dynamics — building, validating, and analysing discrete-state models of high-dimensional stochastic processes. I published 9 papers in under 3 years and developed several algorithms for automating the construction of these models.

Before the PhD: MSc (Distinction) in non-equilibrium systems at KCL (2016), and a 1st Class BSc in Theoretical Physics from UCD (2015).

Outside work

I’m passionate about art in all its forms — music, film, books, theatre, photography exhibitions. There’s a favourites page where I keep a rolling list of what’s been good lately. I also have a mild crossfit addiction.

If you want to talk about probabilistic forecasting, state-space models, foundation models for time series, or anything adjacent — get in touch.