45 citations · 101 across the 18 of their papers we have counts for
18 papers
Physics-Informed Neural Network for Parameter Identification: a Buck Converter Case Study
Shuyu Ou, Subham Sahoo, Ariya Sangwongwanich +5
System-level condition monitoring methods estimate the electrical parameters of multiple components in a converter to assess their health status. The estimation accuracy and variat…
Uncertainty-Aware Artificial Intelligence for Gear Fault Diagnosis in Motor Drives
Subham Sahoo, Huai Wang, Frede Blaabjerg
This paper introduces a novel approach to quantify the uncertainties in fault diagnosis of motor drives using Bayesian neural networks (BNN). Conventional data-driven approaches us…
Semiconductor Devices Condition Monitoring Using Harmonics in Inverter Control Variables
Shuyu Ou, Ariya Sangwongwanich, Subham Sahoo +1
The health status of power semiconductor devices in power converters is important but difficult to monitor. This paper analyzes the relationship between harmonics in inverter contr…
Neuromorphic Event-Driven Semantic Communication in Microgrids
Xiaoguang Diao, Yubo Song, Subham Sahoo +1
Synergies between advanced communications, computing and artificial intelligence are unraveling new directions of coordinated operation and resiliency in microgrids. On one hand, c…
A Monolithic Cybersecurity Architecture for Power Electronic Systems
Kirti Gupta, Subham Sahoo, Bijaya Ketan Panigrahi
Power electronic systems (PES) face significant threats from various data availability and integrity attacks, significantly affecting the performance of communication networks and…
Delay-Aware Semantic Sampling in Power Electronic Systems
Kirti Gupta, Subham Sahoo, Bijaya Ketan Panigrahi
In power electronic systems (PES), attacks on data availability such as latency attacks, data dropouts, and time-synchronization attacks (TSAs) continue to pose significant threats…
Digital Twins for Moving Target Defense Validation in AC Microgrids
Suman Rath, Subham Sahoo, Shamik Sengupta
Cyber-physical microgrids are vulnerable to stealth attacks that can degrade their stability and operability by performing low-magnitude manipulations in a coordinated manner. This…
Impact Assessment of Data Integrity Attacks in MVDC Shipboard Power Systems
Kirti Gupta, Subham Sahoo, Bijaya Ketan Panigrahi +1
The development of power electronics-based medium voltage direct current (MVDC) networks has revolutionized the marine industry by enabling all-electric ships (AES). This technolog…
Atomic Anatomy of Low-Inertia Power Systems
Subham Sahoo, Arpan Malkhandi, Kristian Skafte Jensen
In this article, we determine a fundamental anatomical modeling parallelism between low-inertia power systems and Bohr's atomic model. The proposed atomic architecture will serve a…
Optimizing a Digital Twin for Fault Diagnosis in Grid Connected Inverters -- A Bayesian Approach
Pavol Mulinka, Subham Sahoo, Charalampos Kalalas +1
In this paper, a hyperparameter tuning based Bayesian optimization of digital twins is carried out to diagnose various faults in grid connected inverters. As fault detection and di…
A Robust and Explainable Data-Driven Anomaly Detection Approach For Power Electronics
Alexander Beattie, Pavol Mulinka, Subham Sahoo +4
Timely and accurate detection of anomalies in power electronics is becoming increasingly critical for maintaining complex production systems. Robust and explainable strategies help…
Self-Healing Secure Blockchain Framework in Microgrids
Suman Rath, Lam Duc Nguyen, Subham Sahoo +1
Blockchain has recently been depicted as a secure protocol for information exchange in cyber-physical microgrids. However, it is still found vulnerable to consensus manipulation at…
Training Neural Networks using SAT solvers
Subham S. Sahoo
We propose an algorithm to explore the global optimization method, using SAT solvers, for training a neural net. Deep Neural Networks have achieved great feats in tasks like-image…
Semi-Autoregressive Energy Flows: Exploring Likelihood-Free Training of Normalizing Flows
Phillip Si, Zeyi Chen, Subham Sekhar Sahoo +2
Training normalizing flow generative models can be challenging due to the need to calculate computationally expensive determinants of Jacobians. This paper studies the likelihood-f…
Backpropagation through Combinatorial Algorithms: Identity with Projection Works
Subham Sekhar Sahoo, Anselm Paulus, Marin Vlastelica +3
Embedding discrete solvers as differentiable layers has given modern deep learning architectures combinatorial expressivity and discrete reasoning capabilities. The derivative of t…
Home Energy Management Systems: Operation and Resilience of Heuristics against Cyberattacks
Hafiz Majid Hussain, Arun Narayanan, Subham Sahoo +3
Internet of Things (IoT) and advanced communication technologies have demonstrated great potential to manage residential energy resources by enabling demand-side management (DSM).…
Scaling Symbolic Methods using Gradients for Neural Model Explanation
Subham Sekhar Sahoo, Subhashini Venugopalan, Li Li +2
Symbolic techniques based on Satisfiability Modulo Theory (SMT) solvers have been proposed for analyzing and verifying neural network properties, but their usage has been fairly li…
Learning Equations for Extrapolation and Control
Subham S. Sahoo, Christoph H. Lampert, Georg Martius
We present an approach to identify concise equations from data using a shallow neural network approach. In contrast to ordinary black-box regression, this approach allows understan…