BATTCAVE Seminar Series

Sept 16, Thursday, 11:30-12:30, Fenglian Pan (UNC Charlotte, ISE)

Title: Computationally Efficient Learning of Artificial Intelligence System Reliability Considering Error Propagation

Abstract: Artificial intelligence (AI) systems are increasingly prominent in emerging smart cities. Even with their demonstrated promising potential, reliability assessment for AI systems is in high demand before large-scale deployment. Unlike traditional systems, AI systems typically fuse heterogeneous data streams and operate through a sequence of interdependent functional stages. Errors that occurred in upstream stage(s) may propagate and cause additional errors in downstream stage(s).  This error propagation will be accumulated and ultimately affect the reliability of the overall AI system. Understanding and quantifying the impact of such error propagation is critical, yet remains challenging due to three main factors: i) data availability: real-world AI systems reliability data are often scarce and constrained by privacy concerns; ii) modeling complexity: error events across sequential stages are interdependent, violating the independence assumptions of most existing reliability models; and iii) scalability limitations: AI systems process large volumes of high-speed data, resulting in frequent and complex recurrent error events that are difficult to track and analyze. To address these challenges, this paper proposes a systematic and justifiable error injection framework that incorporates real-world information into a physics-based simulation to efficiently generate reliable data. With the simulated data, a statistical model is formulated to explicitly consider the error propagation for AI systems reliability modeling. To estimate model parameters from extensive error event data, a computationally efficient and theoretically guaranteed composite likelihood expectation-maximization algorithm is proposed. Our approaches are applied to assess the reliability of AI systems in autonomous vehicles. Both numerical experiments and physics-based simulation case studies demonstrate the prediction accuracy and computational efficiency of the proposed methods.

Oct. 17, Friday, 11:30-12:30, Nan Zhao (UNC Charlotte, MEES)

Title: Tissue-Engineered Brain Microvessels and Their Applications

Microvessels—comprising arterioles, capillaries, and venules—are essential for nutrient and waste exchange, tissue homeostasis, and immune surveillance. Their proper function underpins the health of all major organs, while microvascular dysfunction is a hallmark of numerous diseases, including stroke, myocardial infarction, neurodegenerative disorders, and cancer. Given their central role in both physiology and pathology, substantial efforts have been devoted to engineering functional microvascular networks and developing strategies for vascular repair. In this seminar, I will present a series of engineered human brain microvessel models developed using induced pluripotent stem cells, hydrogel biomaterials, and microfluidic platforms. I will then highlight key applications of these tissue-engineered brain microvessels in disease modeling and regenerative medicine.

Nov. 14, Friday, Christofer Bejger (UNC Charlotte, CHEM)

Title: Radialene Active Species as Flow Battery Catholytes
The need for efficient grid-scale energy storage is crucial as the demand for renewable energy sources steadily increases. Redox flow batteries (RFBs) have emerged as capable electrochemical energy storage devices to mediate the void between power generation and consumption. Traditional RFBs rely on expensive vanadium-based materials and corrosive electrolytes. Aqueous organic RFBs are becoming more economically feasible, and systems that operate at neutral pH are particularly desirable from a cost and safety perspective. However, few organic compounds can function as efficient redox couples in neutral pH aqueous solutions. Substituted [3]radialenes are water-soluble, cross-conjugated organic compounds that undergo multielectron transfer and can be synthesized in a stepwise fashion. This talk will discuss our group’s work using hexasubstituted [3]radialene dianions as single-electron charge storage species in RFBs. Specifically, the use of these compounds in pH-neutral aqueous RFBs will be presented. Capacity degradation mechanisms will be discussed, and strategies to mitigate radical-anion dimerization will be highlighted. In addition, we will present our investigation of radialene dianions as two-electron catholytes in non-aqueous RFBs.

Jan. 16, Friday, 11:30-12:30, Farah Deeba (UNC Charlotte, ECE)

Feb. 13, Friday, 11:30-12:30 Sheldon Xie (UNC Charlotte, ETCM)

Mar. 13, Friday, 11:30-12:30, Youxing Chen (UNC Charlotte, MEES)

Apr.  10, Friday, 11:30-12:30 Mahmoud Dinar (UNC Charlotte, MEES)

May. 8. Friday, 11:30-12:30 Lynnora Grant (UNC Charlotte, MEES)