News

In November 2026, I will start a new position at the National University of Singapore (NUS), working with Somabha Mukherjee. I am looking forward to this next chapter in Singapore!

Our preprint Colorful Exponential Random Graph Models, joint with Bhaswar B. Bhattacharya, Ankan Ganguly and Giulio Zucal, is now available on arXiv:2608.31130v1. We study random networks with several types of edge relations. Using probability graphons, we describe their large-network behaviour through an energy–entropy variational problem, from homogeneous colour mixing to structured phases. Examples include induced wedges and rainbow triangles. Read the preprint · Research overview

I completed a research stay at the Barcelona School of Economics (May–July 2026), hosted by Chiara Amorino. The project studies non-exchangeable interacting particle systems whose heterogeneous interactions are represented through probability graphons — ongoing work at the interface of mean-field limits, graph limits and statistical inference.

At IMPMS 2026 in Palermo I co-organised the contributed session Asymptotics of Random Graphs with Elena Magnanini, and presented Exponential Random Edge-Coloured Graphs via Probability Graphons: Free Energies and Extremal Colorings — joint work with Bhaswar Bhattacharya, Ankan Ganguly and Giulio Zucal. Programme · Read more

Quantum preferential attachment is on arXiv: 2512.22542, joint with T. Zhao, B. Maga, G. Ódor, K. Soni, A. Salova, B. Hao, M. Abért and I. A. Kovács. In a quantum network a new node need not attach to its chosen target directly, but to any node within a short distance of it. That local flexibility produces two distinct classes of network architecture — both small-world, neither scale-free. Read more

I gave a talk at the Kutszem Seminar of the Alfréd Rényi Institute of Mathematics in Budapest.

Large deviations for probability graphons, joint with Giulio Zucal, is on arXiv: 2509.14204. The paper proves a Sanov-type large-deviation principle for the limit objects of dense edge-weighted graphs, with a good rate function given by an integrated relative entropy, generalising the Chatterjee–Varadhan theory beyond the binary setting. Read more

The effects of initial conditions on the accuracy of mean-field approximations of Markov processes on large random graphs, joint with Dániel Keliger, is on arXiv: 2506.12872. The accuracy of a mean-field description turns out to depend on the initial condition, not on network density alone: for generic initial conditions the error is of order $d^{-1/2}$, improving to $1/d + N^{-1/2}$ when the initial state is fairly homogeneous. Read more