CSU Systems Engineering Department

AI is set to become a powerful tool in building the circular economy. In a recently published paper, our CSU researchers demonstrate how AI can transform circular economy marketplaces by improving resource allocation, stabilizing prices, and optimizing demand-supply dynamics. They compared several AI approaches and found that gradient boosting regressor (GBR) was the best for demand forecasting, an important aspect of managing resource flow. 🧠🌱🤖 While a great deal of research remains to be done in this area, this study represents an important step in the practical integration of AI into systems designed for a better world. Title: Evaluating Artificial Intelligence Models for Resource Allocation in Circular Economy Digital Marketplace Link to article: https://lnkd.in/gWmxcmq8 Congratulations to the authors! - Arif Sheikh, PhD candidate, CSU Systems Engineering Department - Steve Simske, professor, CSU Systems Engineering - Edwin Chong, Electrical & Computer Engineering Department - Colorado State University #ArtificialIntelligence #CircularEconomy #Sustainability

Can AI understand how we feel about advertisements? In a recently published study, our researchers found that AIs using convolutional neural network (CNN) architectures can accurately predict if someone is interested or not interested in a digital advertisement using facial recognition. They used two different CNN architectures to compare performance and developed a validated Xception model to predict viewers’ interest with 99% accuracy. Title: AI-Driven Marketing Personalization: Deploying Convolutional Neural Networks to Decode Consumer Behavior Link to article: https://lnkd.in/gU4xVPpe Congratulations to the authors for this interesting publication! - Panteha Alipour, PhD candidate, CSU Systems Engineering - Erika E. Gallegos, assistant professor, CSU Systems Engineering - Shrihari (Hari) Sridhar, Senior Associate Dean of Mays Business School, Texas A&M University

Validating input data in real-time for digital twin simulations is essential for ensuring accurate and reliable results. As digital twins grow more sophisticated, so do the risks of defects that arise from flawed input streams. Faulty inputs can derail simulations, leading to incorrect outputs and poor decision-making. Our researchers Nathan Brown and Steve Simske recently published a paper proposing a new framework that uses machine learning to identify defects in sequential data – like rocket trajectories – by leveraging only historical information. Their work builds on research into real-time validation and the trustworthiness of digital twin models. Congratulations to the authors! Title: Detecting Defects in Sequential Inputs to Digital Twins Using Machine Learning Journal: IEEE Open Journal of Systems Engineering Link: https://lnkd.in/gCAZMx-q

📢New INCOSE Technical Product! The Needs and Requirements Manual (NRM) version 2 offers in-depth guidance on system lifecycle processes, specifically covering needs, requirements, verification, and validation, providing practical advice for successful implementation across product development, systems engineering, and project management INCOSE members can download the guide for free and get a 20% discount on a hard copy. https://bit.ly/4eHfsKA

Last month, we hosted a wonderful in-person networking event for Systems Engineering current students and alumni in the Fremont, CA, area. This gathering fostered meaningful connections, shared experiences, and celebrated the strength of our engineering community! Pictured (left to right): Chen Bao, Aaron Rabinowitz, Thomas Bradley, Stone Silva, Sinan B., Jas Sheth, Darshan Shah Thank you to everyone who joined us! We want to connect more with our alumni moving forward so we can strengthen our bonds and build bridges for future collaborations and opportunities. You are always welcome to reach out!

Congratulations to Assistant Professor Erika Gallegos for being recognized as Outstanding Distance Educator 2024 by Colorado State University Online last week! Kenny Corl, who graduated this semester with a Doctorate of Systems Engineering, nominated Gallegos. "Dr. Gallegos has been an inspiring mentor, offering the perfect balance of guidance and freedom that has empowered me to grow both academically and personally throughout my doctoral journey,” he said. Congratulations to Dr. Corl also! Graduating is a grand accomplishment, and we are gratified to be part of your story.

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We had a fun in-person lunch for our graduates last Friday. Thank you to all those who attended! It's so special to have this smart and wholesome community.    Most of our students graduate at a distance because we are a primarily online program. To all of those who celebrated at a distance, congratulations! You are always welcome here.

Three of our top water students and Associate Professor Steve Conrad joined more than 27,000 earth and space scientists in Washington, D.C. for the 2024 American Geophysical Union (AGU) Fall Meeting last week! They presented their research and engaged in hours of discussion with scientists from around the world. Guillermo Vizarreta Luna presented about the need for water system managers to adapt their practices to non-stationarity in watersheds, proposing AI as an innovative solution. Title: Al/ML Tools for Early Decision-Making in Managing Non-Stationarity Water Quality States in Water System Operations. Abstract: https://lnkd.in/gHJEasr7 Dixie Lin Poteet presented on her team’s efforts to understand collaborative water allocation agreements. Instead of fighting over water rights, forming these agreements collaboratively can allow for temporary water allocations. These agreements are largely driven by urban growth but can neglect stakeholder socio-considerations. This is a case study. Title: Socio-Considerations for Collaborative Stakeholder Driven Water Allocation Decisions in Colorado Abstract: https://lnkd.in/gRrBP_Ze Joshua Oluwatumise highlighted collaborative research between Colorado State University and Pennsylvania State University focused on understanding the factors that influence wastewater treatment facilities to adopt solar energy systems and other renewable energy technologies. Title: Solar PV Adoption in Wastewater Treatment Plants: A Qualitative Exploration Abstract: https://lnkd.in/gnHHSQB8 #agu24

We are proud of you and grateful to have you part of our story!