Catalyzing Engineering Research Teaming

Background

One of the key Research & Innovation actions within the 2024 College Strategic Plan is to:

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Over the past several years the College has invested internal funding resources in support of research initiatives (e.g., Interdisciplinary Research Themes – IRT; Sandia National Labs Collaborative Fund) to incentivize faculty in the College to develop teams to advance collaborative, interdisciplinary research. These efforts have enhanced faculty collaborations across units and resulted in significant external research funding awards from federal agencies, including multi-million-dollar awards for Institutes, Centers and Industry-University collaborations.Ìý

To further the Strategic Plan’s goals, the college has committed to create a Catalyzing Research Teaming opportunity for collaborative, interdisciplinary research teams amongst our faculty. The overall intent is to provide seed-grant funding to research teams of interdisciplinary faculty to ideate new engineering and scientific advances and to plan for submission to specific, large-scale external funding opportunities forthcoming in 2025-26. Submitting teams will be required to identify downstream funding opportunities at the Center/Institute levels of funding that span multiple years (>$1.5M/yr).

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CERT Winning Teams 2026

Customizable Battery Infrastructure for Rapid and Reliable Power Delivery

The Team: Chunmei Ban (ME) and Bri-Mathias Hodge (ECEE)Ìý

The Impact:
This initiative is reimagining how battery-powered energy systems are designed by connecting battery science, manufacturing, and power system engineering into a single, integrated framework. Rather than treating batteries as standard components, the team seeks to customize battery technologies based on power demands,operatingconditions,andelectricitysources.Theeffortaimstocreatemorereliable,resilient,andcost-effectiveenergyinfrastructurefordatacenters,industrialfacilities,homes,andtheelectricgrid.

Their work focuses on:

  • Developingmaterials-informedbatterymodelsthatconnectbatterychemistryandmanufacturingtoreal-worldpowersystemperformance.
  • Creatingdesignframeworksthatimprovebatterysafety,reliability,longevity,thermalmanagement,andcosteffectiveness.
  • Integratingcustomizedbatterysystemswithrenewableandconventionalpowersourcestostrengthenenergyresilienceandpowerdelivery.

Thisresearchbringstogetherexpertiseinmaterialsscience,electrochemistry,manufacturing,andpowerengineeringtoestablishanewparadigmforapplication-specificenergystorageandpowerdelivery.

The Team: Danny Dig (CS), Brad Hayes (CS), Ellen Do (ATLAS and CS), and Amir Behzadan (CEAE)

The Impact:Ìý
The Center on Trustworthy AI aims to ensure that generative artificial intelligence can be safely, transparently, and effectively integrated into engineering practice. As AI becomes increasingly embedded in the design, operation, and management of complex systems, the center will develop frameworks that keep humans accountable, improve AI reliability, and enable engineers to work confidently with AI technologies. The effort will position CU Â鶹ӰԺ as a leader in the next generation of AI-enabled engineering systems.

Their work focuses on:

  • Developing reliable and transparent AI systems that can be verified, tested, and trusted in engineering applications.
  • Designing human-in-the-loop AI approaches that preserve human oversight, accountability, and decision-making authority.
  • Creating domain-aware AI tools that understand engineering data, designs, physical constraints, and real-world operating environments.

By combining computer science, engineering, human-centered design, and AI education, the center will create new approaches for trustworthy AI while preparing the future workforce to collaborate effectively with intelligent systems.Ìý

The Team: Debanjan Mukherjee (ME), Jed Brown (CS), Corey Neu (ME), Alessandro Roncone (CS), and Virginia Ferguson (ME)Ìý

The Impact:
CU VITALS is advancing the future of healthcare through the development of digital twins, dynamic virtual models that replicate human biology and medical systems. By improving the computational technologies behind these models, the center aims to enable more personalized treatments, safer medical devices, and better clinical decision-making. The initiative seeks to establish CU Â鶹ӰԺ as a regional leader in digital health, biomedical AI, and precision medicine.Ìý

Their work focuses on:

  • Developing AI-accelerated simulations and high-performance computing tools that make healthcare digital twins faster and more practical for clinical use.
  • Integrating medical imaging, patient data, and physiological models to create more accurate and reliable virtual representations of patients.
  • Building interactive visualization and decision-support technologies that help clinicians evaluate treatments, procedures, and medical devices before implementation.

This highly interdisciplinary effort combines expertise in computational science, artificial intelligence, biomedical engineering, virtual reality, and medicine to create reusable digital twin technologies that can transform healthcare research, education, and patient care.

CERT Winning Teams 2025

The Watering Hole

The Team: Cresten Mansfeldt (CEAE), Julie Korak (CEAE), Sheldon Masters (CEAE), Shideh Dashti (CEAE), Abbie Liel (CEAE), Stephen Kissler (CS), and Nicole Xu (ME)

The Impact:Ìý The Watering Whole at CU Â鶹ӰԺ is transforming how we manage water systems by shifting from a unit-by-unit approach to a flow-history perspective. This new approach emphasizes the interconnectedness of human, material, and environmental interactions within the One Water cycle. The initiative focuses on three key research areas: Their work focuses on:

  • Human-infrastructure interaction, helping people identify and respond to water system failures.
  • Policy and materials management, guiding decisions on safer, more sustainable infrastructure.
  • Bio-inspired sensor technology, driving the next generation of smart water monitoring tools.

This wide range of applications reflects both the flexibility of the research, and the deep, cross-disciplinary expertise involved.


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The Team: Mija Hubler (CEAE, MSE), Anthony Straub (CEAE), Maryam Shakiba (AES), Wil Srubar (CEAE,MSE), and Sherri Cook (CEAE).

The Impact:
The Living BIO-CEM Filters initiative is developing a new generation of sustainable water treatment technologies by combining living biopolymer membranes with durable, low-cost ceramic supports. These tunable filters are designed to selectively capture contaminants and recover valuable resources from water while improving membrane durability, efficiency, and lifespan.Ìý

Their work focuses on:

  • Designing living biopolymer membranes with customizable permeability and contaminant selectivity.
  • Developing durable 3D-printed ceramic support materials that improve filter strength and reduce fouling.
  • Using modeling, machine learning, and life-cycle analysis to optimize performance and identify high-impact water treatment applications.

By integrating expertise in materials science, environmental engineering, structural engineering, and computational modeling, the team is creating a new class of sustainable filtration systems with applications in resource recovery, contaminant removal, and environmental sensing.

The Team: Todd Murray (ME, BME), Longji Cui (ME, MSE), Nick Bottenus (M), Rafael Piestun (ECEE), and Nicole Bienert (ECEE).

The Impact:
The Center for Modal Projection Imaging (MODI) is advancing a breakthrough imaging technology that can overcome traditional resolution limits across multiple sensing platforms. By applying Hermite-Gaussian mode imaging, the team aims to create a universal super-resolution imaging framework capable of revealing details previously undetectable in materials science, medical diagnostics, ultrasound, radar, infrared imaging, and remote sensing.Ìý

Their work focuses on:

  • Developing computational and experimental methods for super-resolution imaging across a wide range of wavelengths and sensing technologies.
  • Improving ultrasound and photoacoustic imaging for applications in medical diagnostics and nondestructive materials evaluation.
  • Expanding super-resolution sensing to radar, infrared, and remote sensing systems for applications in transportation, aerospace, security, and environmental monitoring.

This research brings together expertise in mechanical engineering, biomedical engineering, materials science, optics, radar, and machine learning to create a new imaging paradigm with the potential to transform how we observe and understand complex systems.Ìý