activity
20172024
most citedFalse Data Injection Attacks in Internet of Things and Deep Learning enabled Predictive Analytics

16 citations · 32 across the 8 of their papers we have counts for

collaborators

11 papers

cs.HC2024

Mazed and Confused: A Dataset of Cybersickness, Working Memory, Mental Load, Physical Load, and Attention During a Real Walking Task in VR

Jyotirmay Nag Setu, Joshua M Le, Ripan Kumar Kundu +5

Virtual Reality (VR) is quickly establishing itself in various industries, including training, education, medicine, and entertainment, in which users are frequently required to car…

cs.HC2022

TruVR: Trustworthy Cybersickness Detection using Explainable Machine Learning

Ripan Kumar Kundu, Rifatul Islam, Prasad Calyam +1

Cybersickness can be characterized by nausea, vertigo, headache, eye strain, and other discomforts when using virtual reality (VR) systems. The previously reported machine learning…

cs.HC2021

Rule-based Adaptations to Control Cybersickness in Social Virtual Reality Learning Environments

Samaikya Valluripally, Vaibhav Akashe, Michael Fisher +3

Social virtual reality learning environments (VRLEs) provide immersive experience to users with increased accessibility to remote learning. Lack of maintaining high-performance and…

cs.LG2021

Exploring Fault-Energy Trade-offs in Approximate DNN Hardware Accelerators

Ayesha Siddique, Kanad Basu, Khaza Anuarul Hoque

Systolic array-based deep neural network (DNN) accelerators have recently gained prominence for their low computational cost. However, their high energy consumption poses a bottlen…

cs.LG20203 cited

Crafting Adversarial Examples for Deep Learning Based Prognostics (Extended Version)

Gautam Raj Mode, Khaza Anuarul Hoque

In manufacturing, unexpected failures are considered a primary operational risk, as they can hinder productivity and can incur huge losses. State-of-the-art Prognostics and Health…

cs.LG2020

Adversarial Examples in Deep Learning for Multivariate Time Series Regression

Gautam Raj Mode, Khaza Anuarul Hoque

Multivariate time series (MTS) regression tasks are common in many real-world data mining applications including finance, cybersecurity, energy, healthcare, prognostics, and many o…