1 citations · 1 across the 6 of their papers we have counts for
6 papers
Dual-Head Physics-Informed Graph Decision Transformer for Distribution System Restoration
Hong Zhao, Jin Wei-Kocsis, Adel Heidari Akhijahani +1
Driven by recent advances in sensing and computing, deep reinforcement learning (DRL) technologies have shown great potential for addressing distribution system restoration (DSR) u…
Advancing Personalized Learning Analysis via an Innovative Domain Knowledge Informed Attention-based Knowledge Tracing Method
Shubham Kose, Jin Wei-Kocsis
Emerging Knowledge Tracing (KT) models, particularly deep learning and attention-based Knowledge Tracing, have shown great potential in realizing personalized learning analysis via…
Unsupervised Machine Learning for Detecting and Locating Human-Made Objects in 3D Point Cloud
Hong Zhao, Huyunting Huang, Tonglin Zhang +3
A 3D point cloud is an unstructured, sparse, and irregular dataset, typically collected by airborne LiDAR systems over a geological region. Laser pulses emitted from these systems…
A Novel Data Encryption Method Inspired by Adversarial Attacks
Praveen Fernando, Jin Wei-Kocsis
Due to the advances of sensing and storage technologies, a tremendous amount of data becomes available and, it supports the phenomenal growth of artificial intelligence (AI) techni…
A Practical Adversarial Attack on Contingency Detection of Smart Energy Systems
Moein Sabounchi, Jin Wei-Kocsis
Due to the advances in computing and sensing, deep learning (DL) has widely been applied in smart energy systems (SESs). These DL-based solutions have proved their potentials in im…
Using Machine Learning to Predict Engineering Technology Students' Success with Computer Aided Design
Jasmine Singh, Viranga Perera, Alejandra J. Magana +5
Computer-aided design (CAD) programs are essential to engineering as they allow for better designs through low-cost iterations. While CAD programs are typically taught to undergrad…