Alessandro Zocca

Alessandro Zocca

Tenured Assistant Professor

Vrije Universiteit Amsterdam


My research is centered around the study of complex networked systems in which randomness plays a crucial role. More specifically, I study dynamics and rare events in networks affected by uncertainty, drawing motivation from real-world applications in power systems. My work lies mostly in the area of applied probability but has deep ramifications in areas as diverse as operations research, graph theory, and optimization.

My long-term goal as a researcher is twofold. First, I aim to quantify and analyze the randomness emerging in these complex systems using both rigorous mathematical tools and data-driven learning methods. Second, I plan to develop adaptive algorithms and reinforcement learning control strategies to mitigate the impact of high-impact, low-probability events and enhance network robustness.

As the climate crisis exacerbates the frequency and severity of extreme weather events, my research aims to develop a novel and rigorous mathematical understanding of power systems’ resilience against such phenomena, which naturally exhibit pronounced spatial and temporal correlations.

More broadly, I am interested in stochastic dynamics on networks, especially when a non-trivial interplay emerges between the network structure and the system’s randomness, a setting where applied probability, learning, and optimization naturally meet.

I currently (co)supervise several PhD students:

  • Erica van der Sar at VU (2021-present) on “Multi-agent RL for power system topology control”
  • Chris Franssen at VU (2022-present) on “First-order methods for network optimization”
  • Berend Markhorst at VU (2022-present) on “Stochastic and robust optimization for pipe routing design”
  • Jobke Janssen at CWI (2023-present) on “Stochastic optimization of frequency reserve markets”

I am currently writing a textbook titled Hands-on Mathematical Optimization in Python together with K. Postek, J. Gromicho, and J. Kantor. Resources and companion code are available here .


  • applied probability
  • stochastic networks
  • rare events analysis
  • network optimization
  • reinforcement learning
  • power systems resilience


Read my full CV


Tenured Assistant Professor

Vrije Universiteit Amsterdam, Department of Mathematics

Oct 2019 – Present
From March 2021, I have been an affiliate researcher in the Stochastic Group at CWI Amsterdam .

Postdoctoral researcher

California Institute of Technology, Computing and Mathematical Sciences Department

Sep 2017 – Aug 2019

Funded by my own NWO Rubicon postdoctoral grant: Renewables and uncertainty in future power systems: Mathematical challenges and solutions

I worked with Adam Wierman and Steven Low at the Computing and Mathematical Sciences department. I also joined as an affiliate postdoctoral fellow the Resnick Institute for Sustainability .


Postdoctoral researcher

CWI Amsterdam, Stochastic group

Jan 2016 – Aug 2017
Funded by the NWO VICI grant Rare Events: Asymptotics, Algorithms, Applications of Bert Zwart

PhD in Mathematics

University of Eindhoven, Stochastic Operations research group

Sep 2011 – Dec 2015

Research projects

Reinforcement learning for power systems control

Adaptive topology control in power systems using reinforcement learning and spectral clustering.

Algorithms and optimization for power systems reliability

Understanding the fundamental interplay between network topology and failure propagation in power systems using graph theory and spectral methods

MCMC methods for rare events and non-convex supports

Developing novel sampling methods, with applications to rare event sampling and stochastic optimization.

Rare events in stochastic networks

Unveiling how correlated noise and coupled network dynamics can increase the likelihood of rare events, such as blackouts in power systems with a large renewable penetration

Asymptotic behavior of interacting particle systems

Hitting and mixing times of finite volume interacting particle systems with stochastic evolutions

Random-access networks

Quantifying throughput and delay performance of wireless networks protocols using Markov chains and heavy-traffic limits.

Recent Publications

See full list of publications

Robust ship pipe routing: navigating the energy transition (2023)
Generating synthetic power grids using Exponential Random Graphs (2023)
Critical configurations of the hard-core model on square grid graphs (2023)
Pricing uncertainty in stochastic multi-stage electricity markets (2023)
Uncovering Load-Altering Attacks Against $N-1$ Secure Power Grids: A Rare-Event Sampling Approach (2023)


  • Department of Mathematics, 1111 De Boelelaan, Amsterdam, 1081HV