PMU placement and error control using belief propagation. - Deepjyoti Deka; Sriram Vishwanath (SmartGridComm, 2011)

Network Models for Power Grids: A Generative Approach - Deepjyoti Deka; Sriram Vishwanath (CoRR, 2012)

Generative Growth Model for Power Grids. - Deepjyoti Deka; Sriram Vishwanath (SITIS, 2013)

Optimal hidden SCADA attacks on power grid: A graph theoretic approach. - Deepjyoti Deka; Ross Baldick; Sriram Vishwanath (ICNC, 2014)

Generative models for cellular social networks. - Deepjyoti Deka; Sriram Vishwanath (ICNC, 2014)

Attacking power grids with secure meters: The case for breakers and Jammers. - Deepjyoti Deka; Ross Baldick; Sriram Vishwanath (INFOCOM Workshops, 2014)

Hidden Attacks on Power Grid: Optimal Attack Strategies and Mitigation. - Deepjyoti Deka; Ross Baldick; Sriram Vishwanath (CoRR, 2014)

Data attacks on power grids: Leveraging detection. - Deepjyoti Deka; Ross Baldick; Sriram Vishwanath (ISGT, 2015)

Structural vulnerability of power grids to disasters: Bounds and reinforcement measures. - Deepjyoti Deka; Sriram Vishwanath (ISGT, 2015)

Optimal data attacks on power grids: Leveraging detection & measurement jamming. - Deepjyoti Deka; Ross Baldick; Sriram Vishwanath (SmartGridComm, 2015)

One Breaker is Enough: Hidden Topology Attacks on Power Grids. - Deepjyoti Deka; Ross Baldick; Sriram Vishwanath (CoRR, 2015)

Structural Vulnerability of Power Grids to Disasters: Bounds, Adversarial Attacks and Reinforcement. - Deepjyoti Deka; Sriram Vishwanath (CoRR, 2015)

Tractable structure learning in radial physical flow networks. - Deepjyoti Deka; Scott Backhaus; Michael Chertkov (CDC, 2016)

Learning topology of the power distribution grid with and without missing data. - Deepjyoti Deka; Scott Backhaus; Michael Chertkov (ECC, 2016)

Jamming Aided Generalized Data Attacks: Exposing Vulnerabilities in Secure Estimation. - Deepjyoti Deka; Ross Baldick; Sriram Vishwanath (HICSS, 2016)

Estimating distribution grid topologies: A graphical learning based approach. - Deepjyoti Deka; Scott Backhaus; Michael Chertkov (PSCC, 2016)

Learning topology of distribution grids using only terminal node measurements. - Deepjyoti Deka; Scott Backhaus; Michael Chertkov (SmartGridComm, 2016)

Optimal topology design for disturbance minimization in power grids. - Deepjyoti Deka; Harsha Nagarajan; Scott Backhaus (ACC, 2017)

Exact topology reconstruction of radial dynamical systems with applications to distribution system of the power grid. - Saurav Talukdar; Deepjyoti Deka; Donatello Materassi; Murti V. Salapaka (ACC, 2017)

Learning the exact topology of undirected consensus networks. - Saurav Talukdar; Deepjyoti Deka; Sandeep Attree; Donatello Materassi; Murti V. Salapaka (CDC, 2017)

Learning Exact Topology of a Loopy Power Grid from Ambient Dynamics. - Saurav Talukdar; Deepjyoti Deka; Blake Lundstrom; Michael Chertkov; Murti V. Salapaka (e-Energy, 2017)

State and noise covariance estimation in power grids using limited nodal PMUs. - Deepjyoti Deka; Armin Zare; Andrey Y. Lokhov; Mihailo R. Jovanovic; Michael Chertkov (GlobalSIP, 2017)

Estimating topology and injection statistics in distribution grids with hidden nodes. - Deepjyoti Deka; Michael Chertkov; Scott Backhaus (SmartGridComm, 2017)

Integrated multi-scale data analytics and machine learning for the distribution grid. - Emma M. Stewart; Philip Top; Michael Chertkov; Deepjyoti Deka; Scott Backhaus; Andrey Y. Lokhov; Ciaran M. Roberts; Val Hendrix; Sean Peisert; Anthony Florita; Thomas J. King; Matthew J. Reno (SmartGridComm, 2017)

Topology Estimation in Bulk Power Grids: Guarantees on Exact Recovery. - Deepjyoti Deka; Saurav Talukdar; Michael Chertkov; Murti V. Salapaka (CoRR, 2017)

Structure- & Physics- Preserving Reductions of Power Grid Models. - Colin Grudzien; Deepjyoti Deka; Michael Chertkov; Scott Backhaus (CoRR, 2017)

Chance-Constrained ADMM Approach for Decentralized Control of Distributed Energy Resources. - Ali Hassan 005; Yury Dvorkin; Deepjyoti Deka; Michael Chertkov (CoRR, 2017)

Optimal Ensemble Control of Loads in Distribution Grids with Network Constraints. - Michael Chertkov; Deepjyoti Deka; Yury Dvorkin (CoRR, 2017)

Online Learning of Power Transmission Dynamics. - Andrey Y. Lokhov; Marc Vuffray; Dmitry Shemetov; Deepjyoti Deka; Michael Chertkov (CoRR, 2017)

Exact Topology and Parameter Estimation in Distribution Grids with Minimal Observability. - Sejun Park; Deepjyoti Deka; Michael Chertkov (CoRR, 2017)

Analytical Models for Power Networks: The Case of the Western U.S. and ERCOT Grids. - Deepjyoti Deka; Sriram Vishwanath; Ross Baldick (IEEE Trans. Smart Grid, 2017)

Learning in Power Distribution Grids under Correlated Injections. - Sejun Park; Deepjyoti Deka; Michael Chertkov (ACSSC, 2018)

Topology Learning of Radial Dynamical Systems with Latent Nodes. - Saurav Talukdar; Deepjyoti Deka; Michael Chertkov; Murti V. Salapaka (ACC, 2018)

Data-Driven Identification of a Thermal Network in Multi-Zone Building. - Harish Doddi; Saurav Talukdar; Deepjyoti Deka; Murti V. Salapaka (CDC, 2018)

Uncovering Power Transmission Dynamic Model from Incomplete PMU Observations. - Andrey Y. Lokhov; Deepjyoti Deka; Marc Vuffray; Michael Chertkov (CDC, 2018)

Is Machine Learning in Power Systems Vulnerable? - Yize Chen; Yushi Tan; Deepjyoti Deka (SmartGridComm, 2018)

Topology Estimation using Graphical Models in Multi-Phase Power Distribution Grids. - Deepjyoti Deka; Michael Chertkov; Scott Backhaus (CoRR, 2018)

Joint Estimation of Topology & Injection Statistics in Distribution Grids with Missing Nodes. - Deepjyoti Deka; Michael Chertkov; Scott Backhaus (CoRR, 2018)

Real-time Fault Localization in Power Grids With Convolutional Neural Networks. - Wenting Li; Deepjyoti Deka; Michael Chertkov; Meng Wang (CoRR, 2018)

Structure- and Physics-Preserving Reductions of Power Grid Models. - Colin Grudzien; Deepjyoti Deka; Michael Chertkov; Scott N. Backhaus (Multiscale Model. Simul., 2018)

Structure Learning in Power Distribution Networks. - Deepjyoti Deka; Scott Backhaus; Michael Chertkov (IEEE Trans. Control. Netw. Syst., 2018)

Designing Power Grid Topologies for Minimizing Network Disturbances: An Exact MILP Formulation. - Siddharth Bhela; Deepjyoti Deka; Harsha Nagarajan; Vassilis Kekatos (ACC, 2019)

Exact Topology Learning in a Network of Cyclostationary Processes. - Harish Doddi; Saurav Talukdar; Deepjyoti Deka; Murti V. Salapaka (ACC, 2019)

Stochastic Battery Operations using Deep Neural Networks. - Yize Chen; Md Umar Hashmi; Deepjyoti Deka; Michael Chertkov (ISGT, 2019)

Learning a Generator Model from Terminal Bus Data. - Nikolay Stulov; Dejan J. Sobajic; Yury Maximov; Deepjyoti Deka; Michael Chertkov (CoRR, 2019)

Learning for DC-OPF: Classifying active sets using neural nets. - Deepjyoti Deka; Sidhant Misra (CoRR, 2019)

Arbitrage with Power Factor Correction using Energy Storage. - Md Umar Hashmi; Deepjyoti Deka; Ana Busic; Lucas Pereira; Scott Backhaus (CoRR, 2019)

Graphical Models in Loopy Distribution Grids: Topology estimation, change detection and limitation. - Deepjyoti Deka; Saurav Talukdar; Michael Chertkov; Murti V. Salapaka (CoRR, 2019)

An Adversarial Model for Attack Vector Vulnerability Analysis on Power and Gas Delivery Operations. - Ignacio Losada Carreno; Anna Scaglione; Anatoly Zlotnik; Deepjyoti Deka; Kaarthik Sundar (CoRR, 2019)

Stochastic AC Optimal Power Flow: A Data-Driven Approach. - Ilyès Mezghani; Sidhant Misra; Deepjyoti Deka (CoRR, 2019)

Stochastic and Distributionally Robust Load Ensemble Control. - Ali Hassan 005; Robert Mieth; Deepjyoti Deka; Yury Dvorkin (CoRR, 2019)

Optimal Load Ensemble Control in Chance-Constrained Optimal Power Flow. - Ali Hassan 005; Robert Mieth; Michael Chertkov; Deepjyoti Deka; Yury Dvorkin (IEEE Trans. Smart Grid, 2019)

Energy Storage Optimization for Grid Reliability. - Md Umar Hashmi; Ana Busic; Deepjyoti Deka; Lucas Pereira (e-Energy, 2020)

Physics informed topology learning in networks of linear dynamical systems. - Saurav Talukdar; Deepjyoti Deka; Harish Doddi; Donatello Materassi; Michael Chertkov; Murti V. Salapaka (Autom., 2020)

Data-Driven Learning and Load Ensemble Control. - Ali Hassan 005; Deepjyoti Deka; Michael Chertkov; Yury Dvorkin (CoRR, 2020)

Tractable learning in under-excited power grids. - Deepjyoti Deka; Harish Doddi; Sidhant Misra; Murti V. Salapaka (CoRR, 2020)

A Hierarchical Approach to Multi-Energy Demand Response: From Electricity to Multi-Energy Applications. - Ali Hassan 005; Samrat Acharya; Michael Chertkov; Deepjyoti Deka; Yury Dvorkin (CoRR, 2020)

Physics Regulated Neural Network for High Impedance Faults Detection. - Wenting Li; Deepjyoti Deka (CoRR, 2020)

Estimating Linear Dynamical Networks of Cyclostationary Processes. - Harish Doddi; Deepjyoti Deka; Saurav Talukdar; Murti V. Salapaka (CoRR, 2020)

A Hierarchical Approach to Multienergy Demand Response: From Electricity to Multienergy Applications. - Ali Hassan 005; Samrat Acharya; Michael Chertkov; Deepjyoti Deka; Yury Dvorkin (Proc. IEEE, 2020)

Joint Estimation of Topology and Injection Statistics in Distribution Grids With Missing Nodes. - Deepjyoti Deka; Michael Chertkov; Scott Backhaus (IEEE Trans. Control. Netw. Syst., 2020)

Learning With End-Users in Distribution Grids: Topology and Parameter Estimation. - Sejun Park; Deepjyoti Deka; Scott Backhaus; Michael Chertkov (IEEE Trans. Control. Netw. Syst., 2020)

Graphical Models in Meshed Distribution Grids: Topology Estimation, Change Detection & Limitations. - Deepjyoti Deka; Saurav Talukdar; Michael Chertkov; Murti V. Salapaka (IEEE Trans. Smart Grid, 2020)

Designing Reactive Power Control Rules for Smart Inverters Using Support Vector Machines. - Mana Jalali; Vassilis Kekatos; Nikolaos Gatsis; Deepjyoti Deka (IEEE Trans. Smart Grid, 2020)

Detecting Anomalies using Overlapping Electrical Measurements in Smart Power Grids. - Sina Sontowski; Nigel Lawrence; Deepjyoti Deka; Maanak Gupta (IEEE BigData, 2021)

Physics-Informed Graph Learning for Robust Fault Location in Distribution Systems. - Wenting Li; Deepjyoti Deka (CoRR, 2021)

Learning Networked Linear Dynamical Systems under Non-white Excitation from a Single Trajectory. - Harish Doddi; Deepjyoti Deka; Saurav Talukdar; Murti V. Salapaka (CoRR, 2021)

Guaranteed Phase & Topology Identification in Three Phase Distribution Grids. - Mohini Bariya; Deepjyoti Deka; Alexandra von Meier (IEEE Trans. Smart Grid, 2021)

Efficient and passive learning of networked dynamical systems driven by non-white exogenous inputs. - Harish Doddi; Deepjyoti Deka; Saurav Talukdar; Murti V. Salapaka (AISTATS, 2022)

Can locational disparity of prosumer energy optimization due to inverter rules be limited? - Md Umar Hashmi; Deepjyoti Deka; Ana Busic; Dirk Van Hertem (CoRR, 2022)

Data-Driven Stochastic AC-OPF using Gaussian Processes. - Mile Mitrovic; Aleksandr Lukashevich; Petr Vorobev; Vladimir V. Terzija; Semen Budenny; Yury Maximov; Deepjyoti Deka (CoRR, 2022)

Data-Driven Chance Constrained AC-OPF using Hybrid Sparse Gaussian Processes. - Mile Mitrovic; Aleksandr Lukashevich; Petr Vorobev; Vladimir V. Terzija; Yury Maximov; Deepjyoti Deka (CoRR, 2022)

Ranking-Based Physics-Informed Line Failure Detection in Power Grids. - Aleksandra Burashnikova; Wenting Li; Massih Amini; Deepjyoti Deka; Yury Maximov (CoRR, 2022)

Efficient Topology Design Algorithms for Power Grid Stability. - Siddharth Bhela; Harsha Nagarajan; Deepjyoti Deka; Vassilis Kekatos (IEEE Control. Syst. Lett., 2022)

Markovian Decentralized Ensemble Control for Demand Response. - Guanze Peng; Robert Mieth; Deepjyoti Deka; Yury Dvorkin (IEEE Control. Syst. Lett., 2022)

Tractable Learning in Underexcited Power Grids. - Deepjyoti Deka; Harish Doddi; Sidhant Misra; Murti V. Salapaka (IEEE Trans. Control. Netw. Syst., 2022)

Privacy-Aware Load Ensemble Control: A Linearly-Solvable MDP Approach. - Ali Hassan 005; Deepjyoti Deka; Yury Dvorkin (IEEE Trans. Smart Grid, 2022)

PPGN: Physics-Preserved Graph Networks for Real-Time Fault Location in Distribution Systems with Limited Observation and Labels. - Wenting Li; Deepjyoti Deka (HICSS, 2023)

Malicious Traffic Classification Using Convolutional Neural Network. - Nitin Choudhury; Deepjyoti Deka; Aryan Tewari; Soham Gaur; Satyajit Sarmah; Vangmayee Sharda; Sitesh Gautam (ICCCNT, 2023)

GP CC-OPF: Gaussian Process based optimization tool for Chance-Constrained Optimal Power Flow. - Mile Mitrovic; Ognjen Kundacina; Aleksandr Lukashevich; Petr Vorobev; Vladimir V. Terzija; Yury Maximov; Deepjyoti Deka (CoRR, 2023)

Optimal Power System Topology Control Under Uncertain Wildfire Risk. - Yuqi Zhou; Kaarthik Sundar; Deepjyoti Deka; Hao Zhu 001 (CoRR, 2023)

Graph-Structured Kernel Design for Power Flow Learning using Gaussian Processes. - Parikshit Pareek; Deepjyoti Deka; Sidhant Misra (CoRR, 2023)

Data-Efficient Power Flow Learning for Network Contingencies. - Parikshit Pareek; Deepjyoti Deka; Sidhant Misra (CoRR, 2023)

Fairly Extreme: Minimizing Outages Equitably. - Kaarthik Sundar; Deepjyoti Deka; Russell Bent (CoRR, 2023)

GP CC-OPF: Gaussian Process based optimization tool for Chance-Constrained Optimal Power Flow. - Mile Mitrovic; Ognjen Kundacina; Aleksandr Lukashevich; Semen A. Budennyy; Petr Vorobev; Vladimir V. Terzija; Yury Maximov; Deepjyoti Deka (Softw. Impacts, 2023)

Topology Learning in Radial Dynamical Systems With Unreliable Data. - Venkat Ram Subramanian; Deepjyoti Deka; Saurav Talukdar; Andrew G. Lamperski; Murti V. Salapaka (IEEE Trans. Control. Netw. Syst., 2023)

Information Theoretically Optimal Sample Complexity of Learning Dynamical Directed Acyclic Graphs. - Mishfad Shaikh Veedu; Deepjyoti Deka; Murti V. Salapaka (AISTATS, 2024)

Contributions of Individual Generators to Nodal Carbon Emissions. - Yize Chen; Deepjyoti Deka; Yuanyuan Shi (e-Energy, 2024)

Equitable Routing - Rethinking the Multiple Traveling Salesman Problem. - Abhay Singh Bhadoriya; Deepjyoti Deka; Kaarthik Sundar (CoRR, 2024)

Optimization Proxies using Limited Labeled Data and Training Time - A Semi-Supervised Bayesian Neural Network Approach. - Parikshit Pareek; Kaarthik Sundar; Deepjyoti Deka; Sidhant Misra (CoRR, 2024)

A Parametric, Second-Order Cone Representable Model of Fairness for Decision-Making Problems. - Kaarthik Sundar; Deepjyoti Deka; Russell Bent (CoRR, 2024)

Learning Distribution Grid Topologies: A Tutorial. - Deepjyoti Deka; Vassilis Kekatos; Guido Cavraro (IEEE Trans. Smart Grid, 2024)

Physics-Constrained Adversarial Training for Neural Networks in Stochastic Power Grids. - Wenting Li; Deepjyoti Deka; Ren Wang 008; Mario Roberto Arrieta Paternina (IEEE Trans. Artif. Intell., 2024)

Importance Sampling Approach to Chance-Constrained DC Optimal Power Flow. - Aleksander Lukashevich; Vyacheslav Gorchakov; Petr Vorobev; Deepjyoti Deka; Yury Maximov (IEEE Trans. Control. Netw. Syst., 2024)

Learning Networks From Wide-Sense Stationary Stochastic Processes. - Anirudh Rayas; Jiajun Cheng; Rajasekhar Anguluri; Deepjyoti Deka; Gautam Dasarathy (IEEE Trans. Signal Inf. Process. over Networks, 2025)

Power Flow Approximations for Multiphase Distribution Networks using Gaussian Processes. - Daniel Glover; Parikshit Pareek; Deepjyoti Deka; Anamika Dubey (CoRR, 2025)

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works. - Bendong Tan; Tong Su; Yu Weng; Ketian Ye; Parikshit Pareek; Petr Vorobev; Hung D. Nguyen 001; Junbo Zhao 001; Deepjyoti Deka (CoRR, 2025)