Socially Attentive Autonomous Vehicles
Efficiently modeling high traffic areas will maintain the level of safety in autonomous vehicles and other drivers while reducing the computational cost.
Yi Ren
Yi (Max) Ren is an assistant professor of aerospace and mechanical engineering in the School for Engineering of Matter, Transport and Energy at Arizona State University. Ren’s current research interests include optimization, product/configuration design, human-computer interaction and machine learning.
Total projects: 8
Projects
Learning Unknown Physics Behind Cellular Dynamics Using Time-Variant Neural Network
Creating a time-variant neural network that can model particle dynamics will demonstrate machine learning can learn unknown physics concepts.
Machine Learning and Dimensionality Reduction to Accelerate DFT Simulations of Material Properties and Enable Computational Material Design
Using machine learning for material property simulations will accelerate the process and decrease computational expense.
John Daly
FURI: Spring 2020
Blame All vs. Blame Me in AVs
Studying the ability for an autonomous vehicle to determine another vehicle's intent or loss of function will promote safer executions of traffic scenarios.
Adversarial Attacks in Reinforcement Learning for Autonomous Vehicle Control
By attempting to exploit learning systems in autonomous vehicles, we can better characterize the safety of the next disruptive technology.
Benjamin Danek
FURI: Fall 2019
The Reinforcement Learning Trojan Horse: Data Poisoning in Autonomous Driving Simulations
Validating the reliability of autonomous vehicle control models will ensure autonomous car machine learning systems can’t be poisoned.
Benjamin Danek
FURI: Spring 2019
Crowd-Sourced Service Utilizing Device Network to Facilitate Emergency Intervention
Brendan Scobie
FURI: Fall 2018
Energy-Free Personal Security Wristband
Xianfan Gu
FURI: Spring 2018
