Research and Publications

Selected ongoing projects


Opening the quantum box: understanding the D-Wave quantum annealer

Andrey Y. Lokhov, Yaroslav Kharkov, Carleton Coffrin, Marc Vuffray

Short description: Discovery of persistent biases and listening to the echo of the chip architecture using the Interaction Screening method



Statistical learning for cyber-physical systems

Zheguang Zhao, Deepjyoti Deka, Andrey Y. Lokhov

Short description: Learning a dynamical graphical model representation with discrete and continuous variables from available time series, and using it for subsequent detection, localization and mitigation of anomalies

 Published research


Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov
Efficient learning of discrete graphical models
Submitted [ArXiv]

Short description: Learning discrete graphical models with arbitrary alphabets and multi-body interactions



Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra, Michael Chertkov
Optimal structure and parameter learning of Ising models
Science Advances, 4 , e1700791 (2018) [pdf] [ArXiv] [Code]

Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov, Michael Chertkov
Interaction screening: efficient and sample-optimal learning of Ising models
Advances in Neural Information Processing Systems (NIPS) 2016 [pdf] [ArXiv]

Short description: Sample-optimal “Interaction Screening” method for provably learning arbitrary binary graphical models without any assumptions


Sidhant Misra, Marc Vuffray, Andrey Y. Lokhov
Information theoretic optimal learning of Gaussian graphical models
Submitted [ArXiv]

Short description: Beyond LASSO with the new SLICE and DICE algorithms that achieve the IT bound on sample complexity for learning the structure of Gaussian graphical models


Andrey Y. Lokhov, David Saad
Optimal deployment of resources for maximizing impact in spreading processes
Proceedings of the National Academy of Sciences, 114 (39) E8138-E8146 (2017) [pdf] [ArXiv]

Short description: Optimal targeting in spreading processes with dynamic message-passing equations and forward-backward optimization method used in artificial neural networks


Andrey Y. Lokhov
Reconstructing parameters of spreading models from partial observations
Advances in Neural Information Processing Systems (NIPS) 2016 [pdf] [ArXiv] [spotlight video]

Andrey Y. Lokhov, Theodor Misiakiewicz
Efficient reconstruction of transmission probabilities in a spreading process from partial observations
Work in progress [ArXiv]

Short description: Reconstructing spreading couplings from incomplete cascades

Andrey Y. Lokhov, Marc Vuffray, Dmitry Shemetov, Deepjyoti Deka, Michael Chertkov
Online Learning of Power Transmission Dynamics
Accepted to PSCC 2018 [ArXiv]

Deepjyoti Deka, Armin Zare,  Andrey Y. Lokhov, Mihailo Jovanovic, Michael Chertkov
Estimation of state and noise covariance in power grids using limited nodal PMUs
IEEE Global Conference on Signal and Information Processing (2017) [pdf]

Short description: Learning dynamic state matrix in transmission power systems from phasor measurement units data


Andrey Y. Lokhov, Nathan Lemons, Thomas C. McAndrew, Aric Hagberg, Scott Backhaus
Detection of cyber-physical faults and intrusions from physical correlations
IEEE 16th International Conference on Data Mining Workshops (ICDMW), 303-310 (2016)
[pdf] [ArXiv]
Presented at “Outlier Definition, Detection, and Description on Demand” workshop at KDD 2016

Short description: Detection of anomalies in cyber-physical systems from real data


Andrey Y. Lokhov, Marc Mézard, Lenka Zdeborová
Dynamic message-passing equations for models with unidirectional dynamics
Phys. Rev. E 91, 012811 (2015) [pdf] [ArXiv]

Short description: Solution of many dynamic models (random field Ising model, epidemic and rumor spreading, threshold models) on given network instances

Andrey Y. Lokhov, Olga V. Valba, Mikhail V. Tamm, Sergei K. Nechaev
Phase transition in random planar diagrams and RNA-type matching
Phys. Rev. E 88, 052117 (2013) [pdf] [ArXiv]Andrey Y. Lokhov, Olga V. Valba, Sergei K. Nechaev, Mikhail V. Tamm
Topological transition in disordered planar matching: combinatorial arcs expansion
J. Stat. Mech. P12004 (2014) [pdf] [ArXiv]Short description: Combinatorics of RNA-type matching structures and new phase transition


Andrey Y. Lokhov, Marc Mézard, Hiroki Ohta, Lenka Zdeborová
Inferring the origin of an epidemic with a dynamic message-passing algorithm
Phys. Rev. E 90, 012801 (2014)  [pdf] [ArXiv]

Short description: Localization of the epidemic source from a partial snapshot at unknown time

For more details and an up-to-date list see my google scholar page


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