I am a Max Planck Research Group Leader, leading the Physics for Inference and Optimization group, and a Faculty Member at the International Max Planck Research School for Intelligent Systems. My group is part of the Cyber Valley Initiative.
I am interested in understanding, optimizing and predicting relations between the microscopic and macroscopic properties of complex large-scale interacting systems. I like to approach research by addressing application-oriented problems involving domain experts from different disciplines via developing models and algorithms derived from statistical physics principles.
Inquires about Master degree thesis or internship are always welcomed. Please include your CV, motivation letter with research interests, and BSc/MSc transcripts.
The research goal of the Physics for Inference and Optimization group is understanding, optimizing and predicting relations between the microscopic and macroscopic properties of complex large-scale interacting systems. We pursue this agenda by addressing application-oriented problems of inference and optimization on networks via developing models and algorithms derived from statistical physics principles.
The two main motivations behind this interest are the idea that there is a pressing need for theory to be grounded in concrete applications in order to solve relevant scientific problems in rigorous ways, improving both methodological and domain-specific knowledge.
In addition, in recent years statistical physics has been able to provide new insights and novel approaches to problems in computer science.
Our approach is to address this problem with two main research questions that tackle this issue under different angles and together should provide a cohesive and coherent analysis of the problem:
The objective is that by answering these questions one can provide a comprehensive analysis of the bigger problem of understanding large-interacting systems in their different aspects.
Our research reflects this interdisciplinary approach and considers:
De Bacco, C., Larremore, D. B., Moore, C.
A physical model for efficient ranking in networks
Science Advances, 4(7), American Association for the Advancement of Science, 2018 (article)
Brelsford, C., De Bacco, C.
AreWater Smart Landscapes’ Contagious? An epidemic approach on networks to study peer effects
Networks and Spatial Economics (NETS), pages: 1572-9427, 2018 (article)
Barthel, T., De Bacco, C., Franz, S.
Matrix product algorithm for stochastic dynamics on networks applied to nonequilibrium Glauber dynamics
Physical Review E, 97(1):010104, APS, 2018 (article)
De Bacco, C., Power, E. A., Larremore, D. B., Moore, C.
Community detection, link prediction, and layer interdependence in multilayer networks
Physical Review E, 95(4):042317, APS, 2017 (article)
Lesieur, T., De Bacco, C., Banks, J., Krzakala, F., Moore, C., Zdeborová, L.
Phase transitions and optimal algorithms in high-dimensional Gaussian mixture clustering
In Communication, Control, and Computing (Allerton), 2016 54th Annual Allerton Conference on, pages: 601-608, 2016 (inproceedings)
Bhat, U., De Bacco, C., Redner, S.
Stochastic search with Poisson and deterministic resetting
Journal of Statistical Mechanics: Theory and Experiment, 2016(8):083401, IOP Publishing, 2016 (article)
Berdahl, A., Brelsford, C., De Bacco, C., Dumas, M., Ferdinand, V., Grochow, J. A., Hébert-Dufresne, L., Kallus, Y., Kempes, C. P., Kolchinsky, A., others,
Dynamics of beneficial epidemics
arXiv preprint arXiv:1604.02096, 2016 (article)
De Bacco, C., Guggiola, A., Kühn, R., Paga, P.
Rare events statistics of random walks on networks: localisation and other dynamical phase transitions
Journal of Physics A: Mathematical and Theoretical, 49(18):184003, IOP Publishing, 2016 (article)
De Bacco, C., Majumdar, S. N., Sollich, P.
The average number of distinct sites visited by a random walker on random graphs
Journal of Physics A: Mathematical and Theoretical, 48(20):205004, IOP Publishing, 2015 (article)
Altarelli, F., Braunstein, A., Dall’Asta, L., De Bacco, C., Franz, S.
The edge-disjoint path problem on random graphs by message-passing
PloS one, 10(12):e0145222, Public Library of Science, 2015 (article)
De Bacco, C., Baldovin, F., Orlandini, E.
Non-equilibrium statistical mechanics of the heat bath for two Brownian particles : Internal degrees of freedom found where there shouldn’t be (Special Issue on New Challenges in Complex Systems Science)
理工研報告特集号 : ASTE : advances in science, technology and environmentology : special issue, 11, pages: 111-113, 早稲田大学理工学術院総合研究所 (理工学研究所), March 2015 (article)
De Bacco, C.
Decentralized network control, optimization and random walks on networks
(2015PA112164), Université Paris Sud - Paris XI, sep 2015 (phdthesis)
De Bacco, C., Baldovin, F., Orlandini, E., Sekimoto, K.
Nonequilibrium statistical mechanics of the heat bath for two Brownian particles
Physical review letters, 112(18):180605, APS, 2014 (article)
De Bacco, C., Franz, S., Saad, D., Yeung, C. H.
Shortest node-disjoint paths on random graphs
Journal of Statistical Mechanics: Theory and Experiment, 2014(7):P07009, IOP Publishing, 2014 (article)