In my research, I strive to apply a breadth of network science, statistical physics, information theory and machine learning methods to understand complex biological, social and technological systems. Of these, biological systems are the most fascinating to me, and the ones that I find the most challenging. My current research interests lie at the intersection of network medicine, systems biology and bioinformatics, and involve:

• • the global characterization (classification, subtyping) of human diseases and the discovery of new disease-disease associations

  • the identification and prioritization of key pathways and molecular drivers of cardiovascular, metabolic and pulmonary diseases.

  • addressing the incompleteness and the generic nature of the interactome by introducing context-specificity to it using proteomics measurements

  • the identification of therapeutic targets for cardiovascular diseases

  • the use of multi-omics data to model biological function and dysfunction on multiple molecular levels using the framework of multilayer and multiplex networks

My previous postdoctoral work at MIT CEE involved the modeling of sustainable urban microgrids and made use of real-world city-wide electricity consumption data and time-resolved solar generation data. In this model, I used a combination of network topology, power flow equations and unsupervised learning for the spatiotemporal clustering of microgrids to offer a first peek into the potential benefits, and the interplay between the cost and resilience, of such power networks in urban settings. This work was featured in The Atlantic's CityLab.

My physics PhD at Northeastern involved the quantification of the complexity of networks with an information theoretic approach using entropic measures, the characterization of phase transitions and quantum critical phenomena on complex networks, and biological evolutionary modeling of epistatic interaction networks using community detection techniques inspired from hierarchical clustering algorithms. An important part of my thesis was about the co-evolution and dynamical properties of interacting and multiplex networks, in particular:

• • the modeling of opinion dynamics in antagonistically interacting social networks,

  • investigating the dynamics of the ranking process via the extension of the PageRank centrality measure to multiplex networks, and its implementation on social networks of online communities,

  • the statistical mechanical treatment of spatial multiplex and spatial interacting network ensembles and the study of navigability and transport efficiency on multimodal transportation networks.