Aerospace Engineering Seminar Series: Chloe Johnson "Understanding Rotorcraft: Experimental Approaches for Next-Generation Flight"

Thursday, February 26, 2026; 3:00pm-4:00pm
028 ECoRE
Speaker: Chloe Johnson from University of Maryland

Abstract: Advancing the next generation of rotorcraft demands tightly integrated experimental and predictive capabilities. This seminar presents a multi-modal framework for rotor investigation spanning wind tunnel testing, flight experiments, and computational modeling. Drawing on work at the University of Maryland, I will highlight compound rotor and tiltrotor testing in controlled facilities, along with recent investigations of propeller-driven rotor concepts. These efforts include detailed stability analysis, aerodynamic wake interactions, and coupled aeroelastic characterization of rotor-propulsor configurations. In-house predictive tools are used to complement and extend these findings across operating regimes. Together, these capabilities enable improved performance prediction, deeper understanding of interactional aeromechanics, and expanded operating envelopes for advanced vertical lift systems.

Speaker Bio: Dr. Chloe Johnson is an Assistant Professor in the Alfred Gessow Rotorcraft Center at the University of Maryland, where she leads the Rotorcraft Aerodynamics and Acoustics Lab. Her research focuses on unsteady aerodynamics, blade-wake interactions, aeroelasticity, and interactional aeromechanics in next-generation rotorcraft configurations. Her work leverages wind tunnel testing and the UMD Acoustic Hover Chamber, employing experimental diagnostics including time- and phase-resolved particle imagine velocimetry (PIV), high-fidelity load and pressure sensing, and distributed microphone arrays. Prior to joining UMD, Dr. Johnson was an aerospace engineer at the Naval Surface Warfare Center, where she supported UAS development and ship airwake testing efforts. She received her Ph.D. in Aerospace Engineering from the University of Texas at Austin.

Hosted by: Jessica Chhan,  jmc7050@psu.edu

Machine Learning–Driven Modeling for Personalized Predictions in Alzheimer’s Disease

Wednesday, February 25, 2026; 12:15 - 1:15 pm
W306 Millennium Science Complex
Speaker: Wenrui Hao from Penn State University

Alzheimer’s disease (AD) is highly heterogeneous, with patients showing different biomarker trajectories, progression rates, and treatment responses. Traditional models offer insight but miss individual variability. We integrate machine learning with mechanistic mathematical modeling to build patient digital twins that simulate disease progression and test personalized therapies. This framework deepens understanding of the biomarker cascade and supports precision medicine, with potential to reduce clinical trial cost and accelerate therapeutic development.

https://psu.zoom.us/j/94639233394

Hosted by: Rebecca Benson,  rle4@psu.edu

Safe and Trustworthy AI with Verifiable Guarantees

Friday, February 27, 2026; 10:00AM
W375 Westgate Building
Speaker: Dr. Min Wu from Stanford University

ABSTRACT

In this talk, I will present my work on developing safe and trustworthy AI systems with verifiable guarantees, situated at the intersection of AI and formal methods. I’ll begin with a brief overview of my research scope, then highlight two key areas: (1) formal explainable AI to promote trustworthiness, and (2) robustness guarantees to enhance AI safety. In the first part, I’ll discuss how we use neural network verification techniques to compute optimal verified explanations for deep neural networks, and how these explanations can be applied to evaluate trustworthiness in real-world scenarios—such as an autonomous aircraft taxiing application developed in collaboration with Stanford AeroAstro and NASA. In the second part, I’ll introduce a game-based verification framework that computes the maximum safe radius of neural networks to quantify their robustness. Notably, the concept of "safe radius" has been adopted by ISO and IEC in their newly established standard ISO/IEC TR 5469:2024 Artificial Intelligence – Functional Safety and AI Systems. I will conclude with a discussion of future research directions.

BIOGRAPHY

Min Wu is a postdoctoral scholar working with Prof. Clark Barrett in the Department of Computer Science at Stanford University. She is also affiliated with the Stanford Center for AI Safety and the Stanford Center for Automated Reasoning. She received her PhD in Computer Science from the University of Oxford under the supervision of Prof. Marta Kwiatkowska. Her research aims to develop AI systems—particularly those used in high-stakes applications—that are verifiably safe and trustworthy. More details about her work are available on her academic webpage: https://cs.stanford.edu/~minwu.

Hosted by: Emmalia Lutz,  exr123@psu.edu

Locating Refueling Stations for Alternative-Fuel Vehicles in a Multi-Class Vehicle Transportation Network and Its Impact on the Environment

Wednesday, February 25, 2026; 121 Earth & Engineering Science Building
3:35-4:25 p.m.
Speaker: Jose Ventura from Industrial and Manufacturing Engineering

The existing literature regarding the location of alternative fuel (AF) refueling stations in transportation networks generally assumes that all vehicles are capable of traveling the same driving range and have similar levels of fuel in their tanks at the moment they enter the network and when they exist it. In this research, we relax these assumptions and introduce a multi-class vehicle transportation network in which vehicles have different driving ranges and fuel tank levels at their origins and destinations. A 0-1 linear programming model is proposed for locating a given number of refueling stations that maximize the total traffic flow covered (in round trips per time unit) by the stations on the network. Through numerical experiments with recent medium- and heavy-duty truck traffic data in the Pennsylvania Turnpike, we identify the optimal sets of refueling stations for liquified natural gas (LNG) trucks considering multiple truck classes with different driving ranges and fuel tank levels at origins and destinations. Moreover, we discuss the impact of refueling station construction cost on annual greenhouse gas (GHG) emissions reduction and social cost of carbon (SCC) savings.

Dr. Jose Ventura is a Distinguished Professor of Industrial Engineering at Penn State. He holds a BS degree in Industrial Engineering from Polytechnic Univ. of Catalonia (Spain), and MEng and PhD degrees in Industrial Engineering and Operations Research from Univ. of Florida. His research interest focuses on supply chain management, with a varying emphasis that includes supplier selection, auctions and price negotiation strategies for procurement, inventory coordination, and transportation. He is also interested in traffic network equilibrium, energy transport logistics, and energy policy. Ventura has published over 130 archival journal papers. His research has garnered funding from federal and state agencies, such as NSF, DARPA-TRP, the Pentagon, and PA Turnpike Commission, and industry, such as GE and McDonnell Douglas. His research has been recognized by numerous awards, including the 2017 IISE David F. Baker Distinguished Research Award, the 1990 NSF Presidential Young Investigator Award, and the 1988 IISE Doctoral Dissertation Award.

Hosted by: Lana Fulton,  lub18@psu.edu

Aerospace Engineering Seminar Series: Aaron Johnson

Thursday, March 5, 2026; 3:00pm-4:00pm
028 ECoRE
Speaker: Aaron Johnson from University of Michigan

Hosted by: Jessica Chhan,  jmc7050@psu.edu

How Cancers Lose Their Nerve

Wednesday, March 4, 2026; 12:15 - 1:15 pm
W306 Millennium Science Complex
Speaker: Bojana Gligorijevic from Temple University

To image tumor-associated sensory neurons, we have recently integrated retrograde tracing and tissue-clearing with advanced 3D microscopy (J Microscopy 2024). We have also designed a 3D dorsal root ganglia (DRG)-on-chip (iScience 2026) and established cultures of mechanosensory neurons. Using our novel approaches, we found an increase in sensory neuron outgrowth and activity concomitant with breast tumor progression. Activated neurons release the peptide CGRP, which binds to CRLR/RAMP1 on cancer cells, decreasing their ability to metastasize. This cascade of events suggests that sensory innervation in primary tumors has a protective role.

https://psu.zoom.us/j/94639233394

Hosted by: Rebecca Benson,  rle4@psu.edu

Waste to Resource: Sustainable Plastic Management for a Circular Global Economy

Wednesday, March 4, 2026; 121 Earth & Engineering Science Building
335-425PM
Speaker: Hilal Ezgi Toramann from Energy, Mineral and Chemical Engineering PSU

Abstract:

About 60% of all plastics ever made are currently in waste sites, resulting in a yearly loss of $80-120 billion USD. Plastic production, accounting for 6% of global oil use, is projected to rise to 20% by 2050. Unique conditions in landfills and the natural environment expose plastic waste to factors like high salinity, varied temperatures, and microbial breakdown which can lead to the formation of microplastics. My lab leverages expertise in catalysis and reaction engineering along with advanced separation techniques such as two-dimensional gas chromatography and artificial intelligence to study the fundamental chemistry behind plastic recycling technologies. Accurate product characterization is essential to develop kinetic models for both catalytic and non-catalytic pathways. By leveraging the advanced separation capabilities of GC×GC, this talk highlights its critical role in resolving complex pyrolysis products and elucidating reaction mechanisms. These insights enable resilient plastic-recycling strategies by deepening our understanding of pyrolysis chemistry, ensuring process adaptability, and reinforcing the foundations of a strong circular economy.

Bio:

Hilal Ezgi Toraman leads an interdisciplinary research program at Penn State focused on sustainable reaction engineering and catalysis for the valorization of non-traditional carbon feedstocks, particularly plastic waste. Her group integrates advanced pyrolysis experimentation, GC×GC-based analytics, and kinetic modeling to develop and optimize scalable chemical recycling technologies. She leads multi-institutional projects on mixed plastic pyrolysis and catalytic upgrading, where her group contributes intrinsic kinetic studies, GC×GC method development, and data management and analysis infrastructure to support process design and evaluation. Toraman has received both national and international recognition, including the C&EN Talented 12, AIChE CRE Pioneers in Catalysis and Reaction Engineering, and ACS Energy & Fuels Rising Star. She has held leadership roles as Director of AIChE's Catalysis and Reaction Engineering Division and president of the Pittsburgh-Cleveland Catalysis Society. Her honors include the Virginia S. and Philip L. Walker Jr. Faculty Fellowship and the Wilson Fellowship. Before joining the Penn State faculty, Toraman was a postdoctoral researcher with the Department of Chemical and Biomolecular Engineering and Delaware Energy Institute at the University of Delaware. She received her B.S. and M.S. degrees in Chemical Engineering from Middle East Technical University, Türkiye , and her Ph.D. degree in Chemical Engineering from Ghent University, Belgium.

Hosted by: Lana Fulton,  lub18@psu.edu

Aerospace Engineering Seminar Series: TBA

Thursday, March 19, 2026; 3:00pm-4:00pm
ECoRE
Speaker: from

Hosted by: Jessica Chhan,  jmc7050@psu.edu

From neuron classification to spiking neural network simulations: a neuroinformatics approach to data-driven computational models

Wednesday, March 18, 2026; 12:15 - 1:15 pm
W306 Millennium Science Complex
Speaker: Giorgio Ascoli from George Mason University

Neuroscience textbooks describe the brain as a massive network of spiking neurons with complex dynamics. Neural circuits, the story goes, are largely defined by the connectivity between axons, reliably propagating all-or-none action potentials to distant targets, and local dendrites integrating synaptic inputs. In this model, activity-dependent plasticity continuously alters synaptic strength, while neurotransmitters determine excitation v. inhibition. Are these ingredients sufficient to explain cognition? If not, what is missing? Tackling these questions for the hippocampal formation, I will show how neuronal diversity is the key to explore the relationship between synapses and behavior.

https://psu.zoom.us/j/94639233394

Hosted by: Rebecca Benson,  rle4@psu.edu