First Year
Colleen Crouch
Mechanical, Aerospace and Biomedical Engineering Department
Brain Spatial Multi-omic Imaging & Analysis Protocol: Alzheimer’s Disease Proof of Concept
Our goal is to develop a multimodal research protocol to map phenotypic signatures of the brain that can be used to identify changes due to aging or disease. Better understanding of the spatial heterogeneity of phenotypic changes occurring during disease progression will allow more targeted diagnosis and treatment. We will use computational algorithms to integrate data we generate from mass spectrometry imaging, microscopy-guided single cell MS profiling, and spatial single-cell RNA sequencing from tissue sections of targeted brain regions to create a 3D atlas/map of a portion of the brain. To our knowledge, these 3 techniques have not been combined previously
Doowon Kim
Min H. Kao Department of Electrical Engineering and Computer Science
Enhancing the Security of Connected and Automated Vehicles Ecosystem
Connected and automated vehicles (CAVs) are considered a future, intriguing technology that can change our daily lives on future roadways in terms of drivers’ safety and fuel efficiency through the communications between vehicles and infrastructures. Despite these advantages, security has not been the first priority in the CAVs ecosystem; instead, the efficiency of algorithms has always been the higher priority. Therefore, this can open up unprecedently various attack surfaces for adversaries.
Joon Sue Lee
Department of Physics and Astronomy
Topological Quantum Materials Prepared by Epitaxy
Topology, a way of thinking about objects based on their broad properties that are preserved under continuous deformations, can be applied to condensed matter physics. In the context of quantum materials, topology can explain and predict why novel electronic states emerge at surfaces/edges and interfaces with unusual properties such as spin-charge coupling and novel superconducting features, which make the topologically nontrivial materials (topological materials) exciting candidates for future device applications.
Himanshu Thapliyal
Min H. Kao Department of Electrical Engineering and Computer Science
A Cross-Layer Application of Approximate Computing to Increase Noise Resilience of NISQ Quantum Circuits
Fully fault-tolerant quantum computation will take a significant amount of resources. Therefore, one of the current focuses in quantum computation is to establish the utility of small scale, error-prone, or “noisy intermediate-scale quantum” (NISQ), machines. In NISQ machines, the application of quantum gates as well as the measurement operations can introduce errors
Second Year
Subhadeep Chakraborty
Department of Mechanical, Aerospace and Biomedical Engineering
Artificial Intelligence based impairment detection system for vehicle operators through combined analysis of physiological and traffic sensor data
Impaired driving is a key contributing factor leading to more than 10,000 fatalities in 2016. By integrating and fusing multiple data sources such as driver biometrics, vehicle kinematics, and roadway and environmental conditions in real-time, this project aims to generate an intelligent Advanced Driver Assist System (iADAS) which will provide useful feedback to drivers and potentially mitigate accidents.
Jian Liu
Min H. Kao Department of Electrical Engineering and Computer Science
Towards Robust and Trustworthy Federated Learning for Ubiquitous Cyber-Physical Systems: Security, Privacy, and Scalability
Different from traditional centralized training, federated learning distributes the training process to the edge, enabling edge-computing devices to collaboratively learn/update a shared model using the data that is kept locally on the device. Liu’s project hopes to build a foundation for understanding how to push AI gains in performance, robustness, and scalability to CPS in mobile edge computing.