How Safe Is Safe Enough? Ensuring Safety and Resilience in Critical Infrastructure Control Systems

Wednesday, September 23, 2026; 3:35-4:25 pm
254 Health and Human Development
Speaker: ROMULO MEIRA GOES from

Abstract: Critical infrastructure control systems (CIS), such as energy, transportation, and manufacturing, are expected to operate safely despite uncertain environments, unexpected failures, cyberattacks, and AI-enabled decision-making. Although modern control and verification techniques can provide safety guarantees, these guarantees are only as reliable as the assumptions on which they are built. In this talk, we focus on three questions: (1) How safe is a system when its environment deviates from the assumptions used during design? (2) Can a system recover safe operation after a disruption while continuing to function? (3) How can we leverage emerging AI technologies without sacrificing safety guarantees?

To address these questions, we use supervisory control theory of discrete-event systems to develop new methodologies for robustness analysis of controllers, recovery strategy synthesis, and AI-assisted decision verification. These methodologies enable engineers to characterize safe operating envelopes of controllers, identify realistic vulnerabilities, design controllers that restore safe operation, and formally validate AI-generated plans before deployment. We demonstrate how these methods enhance the safety and resilience of CIS through case studies in manufacturing systems.

Bio: Rômulo Meira-Góes is an Assistant Professor in the School of Electrical Engineering and Computer Science at the Pennsylvania State University. Previously, he was a postdoctoral researcher working with Eunsuk Kang, Stavros Tripakis, and Stéphane Lafortune at Carnegie Mellon University and the University of Michigan. In 2022, he received the CPS Rising Stars Award from the University of Virginia. He received his Ph.D. in Electrical and Computer Engineering from the University of Michigan in 2020, working with Stéphane Lafortune. Prior to the University of Michigan, he earned his B.S. degree in Electrical Engineering from the Universidade Tecnológica Federal do Paraná - Curitiba in 2015.

Hosted by: Lana Fulton,  lub18@psu.edu

Scaling Photonic Computing Across Device, Architecture, and System Levels

Wednesday, September 30, 2026; 3:35-4:25 pm
254 Health and Human Development
Speaker: Nathan Youngblood from

Abstract: Photonics information processing strategies offer the unique ability to perform analog computation with ultra-low latency and high efficiency. However, designing compact and reconfigurable photonic architectures which scale well at the architecture and system level is a challenge. The combination of bistable optical materials (such as phase-change materials like Ge2Sb2Te5 and Sb2Se3) and integrated photonics is a promising approach which enables nonvolatile optical memory on-chip with low drift, compact footprint, and high-speed readout. This talk will first present our work developing robust and scalable photonic memories using phase-change and magneto-optic materials (Ce:YIG) for photonic “in-memory” computing techniques. I will then discuss our recent theoretical and experimental results using coherent photonic crossbar arrays to implement large-scale matrix-matrix multiplication. Finally, I will present a new approach to enable distributed photonic computing over fiber without costly electrical-to-optical or analog-to-digital conversions.

BIO: Dr. Nathan Youngblood, William Kepler Whiteford Faculty Fellow and Associate Professor of Electrical and Computer Engineering, joined the University of Pittsburgh in September 2019. As a postdoctoral researcher at the University of Oxford from 2017 to 2019, he developed phase-change optical systems and photonic architectures for non-von Neumann computing. In 2016, he received a PhD in Electrical Engineering from the University of Minnesota where his research focused on integrating 2D materials with silicon photonics for optoelectronic applications. Nathan is the recipient of the NSF CAREER and AFOSR Young Investigator Awards, as well as the Friedrich Wilhelm Bessel Research Award from the Alexander von Humboldt Foundation for his innovations in optical computing and photonic memory technologies. His work has been published in leading journals such as Nature, Nature Photonics, and Science Advances, and featured in popular news outlets such as The Times, London and the Daily Mail.

Hosted by: Lana Fulton,  lub18@psu.edu

Engineering Nanomembranes for Molecular and Ion Separations

Thursday, October 8, 2026; 10:35am
Capone Learning Auditorium (CBEB 001)
Speaker: Haiqing Lin from University of Buffalo

Polymeric membranes have emerged as an energy-efficient technology for carbon capture and ion separations, and they should have desirable sub-nm free volumes to achieve superior separation properties. Furthermore, these materials must be fabricated into nanofilm composite (NFC) membranes of < 100 nm using roll-to-roll processes, while the nanofilm properties can significantly deviate from their bulk properties. I will discuss two approaches to designing and fabricating such nanomembranes. First, polysiloxane-based membranes can be sequentially treated with oxygen plasma and atomic layer deposition (ALD), producing a few-nm amorphous zeolite layer and yielding superior H2/CO2 separation properties for precombustion carbon capture. Second, nanofiltration membranes can be surface-engineered to impart Mg2+-philic groups, thereby dramatically increasing the separation factor for Li+/Mg2+, a critical separation for lithium recovery from brines. The correlation between manufacturing, structure, and separation properties will be elucidated.

Dr. Haiqing Lin is a professor in the Department of Chemical and Biological Engineering at the University at Buffalo, State University of New York. His research elucidates structure-property relationships of polymeric membranes for gas, liquid, and ion separations, with the end goal of addressing key challenges in energy and sustainability. He earned his Ph.D. in Chemical Engineering from the University of Texas at Austin in 2005 and then joined Membrane Technology and Research, Inc. (MTR) as a Senior Research Scientist. He led the successful development of PolarisTM membranes for CO2 removal from syngas. In 2013, he began his career at the University at Buffalo as an assistant professor and was promoted to professor in 2021.

Dr. Lin has published nearly 180 peer-reviewed articles and book chapters, and he is a co-inventor of 10 US patents and patent applications. He was a recipient of the 2016 NSF CAREER Award and the 2025 AIChE Institute Award for Excellence in Industrial Gases Technology.

Hosted by: Angela Dixon,  adc12@psu.edu

Breaking the Memory Wall with Optical Interconnects and In-Memory Computing

Wednesday, October 7, 2026; 3:35-4:25 pm
254 Health and Human Development
Speaker: Ning Li from

Abstract: The explosive growth of emerging applications in data analytics and high-performance computing is placing unprecedented demands on today’s computing systems. Consequently, hyperscale computing systems now face critical bottlenecks in data transfer rather than computational power. I will talk about two projects we are working on to address this challenge. In the first project, we are developing glass panel-enabled 3D optical interconnects to significantly increase bandwidth density and energy efficiency for panel-scale computing. We employ volumetric waveguides and 3D routing in glass to enhance the density of waveguides and optical components and eliminate the shoreline density limitations in planar photonics. In the second project, we are developing non-volatile memory devices for in-memory computing to greatly reduce the data shuffling between processors and memory. With numerous memory devices developed in recent years, there is a need for benchmarking their performance in the deep neural network computing. We developed such a comprehensive methodology for such benchmarking and found that electrochemical memory has great potential for high-performance large-scale analog in-memory computing.

BIO: Ning Li is an associate professor in the Department of Electrical Engineering and Materials Research Institute at The Pennsylvania State University. He was a research staff member at IBM T.J. Watson Research Center from 2010 to 2022. His research experience includes photonic components and links for communications and interconnects, heterogeneous integration of materials and devices for new applications, nonvolatile memories for in-memory computing. He was awarded more than 250 U.S. patents, many High Value Patent Awards, and multiple Master Inventor Awards. He published in scientific journals and conferences including Nature Photonics, Nature Communications, Advanced Materials, Optical Fiber Communication (OFC), etc. His work has been featured on Nature Research Highlight, Semiconductor Today, etc. He received his BS degree from Tsinghua University and PhD degree from The University of Texas at Austin.

Hosted by: Lana Fulton,  lub18@psu.edu

Modern Applications of Quantitative Ultrasound for Medical Research

Wednesday, October 14, 2026; 3:35-4:25 pm
254 Health and Human Development
Speaker: JONATHAN MAMOU from University of Pitt

Presentation Abstract:

Quantitative ultrasound (QUS) is an active research field focused on obtaining quantitative tissue properties (i.e., system- and user-independent) from ultrasound data. Conventional ultrasound imaging is commonly used to visualize soft tissue morphology. During scanning, a gray-scale B-mode image is displayed on screen from which a trained clinician can evaluate tissue states. However, B-mode ultrasound image formation discards valuable information in the raw backscattered echo signal that encodes information about tissue microstructure. Therefore, microstructural changes in soft tissues that accompany disease processes, but do not directly affect tissue morphology, may not be visible in B-mode images. QUS methods use the raw ultrasound data to reconstruct parametric maps that are representative of tissue microstructure. In this talk, I will review conventional ultrasound imaging and QUS methods based on analyzing the backscatter coefficient and envelope statistics. I will present recent vivo QUS results from in vivo human studies in cancer, ophthalmology, and dermatology.

Dr. Jonathan Mamou graduated in 2000 from the Ecole Nationale Supérieure des Télécommunications in Paris, France. In January 2001, he began his graduate studies in Electrical and Computer Engineering at the University of Illinois in Urbana-Champaign, Urbana, IL. He received his M.S. and Ph.D. degrees in May 2002 and 2005, respectively. He previously was the Associate Research Director of the F. L. Lizzi Center for Biomedical Engineering at Riverside Research in New York, NY. He currently is a Professor of Electrical Engineering in the Department of Radiology of Weill Cornell Medicine in New York, NY. Dr. Mamou also is an Adjunct Professor in the Department of Electrical Engineering of New York University. His fields of interest include theoretical aspects of ultrasound scattering, ultrasonic medical imaging, acoustic microscopy, ultrasound contrast agents, and biomedical image processing.

Hosted by: Lana Fulton,  lub18@psu.edu