Projects

Education Related Projects

NSF RED Spin-off project:

Our current assessment techniques struggle to facilitate adaptive teaching and self-directed learning, which acknowledge differences in students’ prior knowledge, skills, and attitudes. The struggle gets compounded as classroom diversity increases across educational domains, hence the need for more informative assessment practices that may better guide instructor teaching and individualized student learning. Towards this, introducing descriptive digital tags into assessment material is a useful method to effectively organize and analyze both group and individual student performance information. Furthermore, tagged assessment and instructional materials allow for categorical and chronological grouping of student data, thus allowing for automated determination of student and class strengths, learning deficiencies, and their respective progressions over time. This extracted information can be used by the instructors to verify and predict their intentioned learning objectives – empowering scalable adaptive teaching methods – and by students as a tool to support self-directed learning.

To address this gap, we have developed relevant skill and conceptual knowledge descriptive tags in tag-organized assessment (TOA). The approach leverages online assignment grading platform to provided data for creating interactive visuals of student and class performance that can be scaled to much larger class sizes. The analysis of TOA helps map performance indicators for each tag in the hierarchical network of concepts and skills in the course to teacher and student practices.

SIIP: SIIP and Share: Podcasts to Connect the Engineers of Grainger COE

  • Holly Golecki, Bioengineering (PI)
  • Jennifer Amos, Bioengineering 
  • Wayne Chang, Aerospace Engineering
  • Ramez Hajj, Civil and Environmental Engineering
  • Blake Johnson, Mechanical Science and Engineering
  • Colleen King, Journalism, College of Media
  • Saad Shehab, Siebel Center 

This project aims to strengthen the entrepreneurial mindset of students in the Grainger College of Engineering via podcasting. In Year 1 of the project, we produced and released Season 1 of SIIP & Share which contains 8 episodes available on Apple Podcasts and Spotify.

After a successful launch and evaluation of the SIIP-focused podcast, we are shifting focus to student-facing podcasts connecting technical content with anecdotes from faculty and alumni to create connections and value for engineering students.

SIIP: Crystal Vision: “ A Video Game to Enhance Student Learning Outcomes on Engineering Materials”

  • Nishant Garg, Civil and Environmental Engineering (PI)
  • Jacob Henschen, Civil and Environmental Engineering
  • Matthew Goodman, Materials Science and Engineering
  • Eric Scaffer, Computer Science 
  • Jennifer Amos, Bioengineering 

This project proposes the development of a cloud-based 3D educational video game to enhance student engagement and learning in CEE 300: Behavior of Materials and MSE 280: Engineering Materials at UIUC. Building on prior VR-based educational tools, which improved learning outcomes but faced scalability and user comfort challenges, the new platform will be built on WebGL for broad accessibility and incorporate machine learning algorithms to adapt difficulty based on user performance. The game will cover key materials science topics, including stress-strain behavior, fracture mechanisms, phase diagrams, and XRD analysis, with a narrative-driven, exploratory structure to promote systems thinking, critical analysis, and entrepreneurial mindset habits. Learning effectiveness will be evaluated through pre- and post-tests, in-game metrics, and surveys, under IRB-approved protocols.

SIIP: Highlighting Course Connections

  • Ke Tang, Mechanical Science and Engineering (PI)
  • Tom Golecki, Mechanical Science and Engineering
  • Jacob Henschen, Civil and Environmental Engineering
  • Matthew Goodman, Materials Science and Engineering
  • Jason Merret, Aerospace Engineering
  • Jennifer Amos, Bioengineering 

Toward the goal of improving student’s interdisciplinary problem-solving skills, we propose an idea to help students see the dense web of connections between courses in other Grainger departments. The only explicitly stated connections between courses may be the chains formed by prerequisites. However, many courses across disciplines rely on very similar concepts, tools, applications, methods, learning objectives, etc. We propose to make these connections across the engineering curriculum more widely known, discussed, and highlighted by faculty.

SIIP Adaptation: Open Educational Resources

  • Caroline Cvetkovic, Bioengineering (PI)
  • Holly Golecki, Bioengineering 
  • Jennifer Amos, Bioengineering 
  • Ali Ansari, Bioengineering

This project focuses on the development of interactive Bioengineering reference pages that would standardize the concepts present in the curriculum across many of the undergraduate courses. This will allow faculty to use the same language and notations, validate the content and depth of what other pre- or post-requisite courses are covering, and then call backwards or forwards to other courses that reiterate those topics. Following in the spirit of interdisciplinary SIIP projects, this team will work to tie bioengineering concepts to those in other engineering reference pages (such as the Mechanical Engineering Reference Pages, from which this Adaptation project was proposed).

Healthcare Related Projects

ARCHES – Toward automated diagnosis and 3D visualization of seizure onset zones from SEEG, MRI and CT clinical data

  • Brad Sutton, PhD, University of Illinois Urbana-Champaign
  • Andres Maldonado, MD, OSF HealthCare
  • Jennifer Amos, PhD, University of Illinois Urbana-Champaign
  • Matthew Bramlet, MD, OSF HealthCare

Using multimodal imaging combined with stereo electroencephalography (SEEG) to enable localization of the seizure foci and identification of nearby critical anatomy to plan the patient-specific intervention. This will transform epilepsy surgical decision making by translating existing medical data into 3D and 4D visuals; significantly increasing surgeon confidence, intervention planning, and improving patient outcomes. 

From Technology to Humans: Protecting Users of Neural and Medical Implant Technologies Through Resilience and Safety Engineering – NSF’s Smart & Connected Communities program

  • Kevin Fu (Principal Investigator), Northeastern University
  • Wayne P Burleson (Co-Principal Investigator) University of Massachusetts Amherst
  • Julian M Goldman (Co-Principal Investigator) MGH, Harvard University
  • Jennifer R Amos (Co-Principal Investigator), University of Illinois Urbana-Champaign
  • Xuan Zhang (Co-Principal Investigator), Northeastern University

This research will advance community priorities in the areas of safety, security, and human health and wellness pertaining to existing and future neural implant devices. The team includes computer scientists, electrical engineers, MDs, neuroscientists, neural implant community groups, and manufacturers. The partner community groups include patients and their supporting families and caregivers from whom the team will understand the personal impact of neural implant technologies. Expanding engagement with partnered companies who manufacture and medical doctors who use neural implants, the team will address these community challenges and collaboratively deliver a neural implant hardware/software co-design solution that empowers the use and facilitates the safe adoption of emerging neural implant technologies. The research techniques developed for chip security will have applicability to other security related chip-based devices. This project will advance the scientific and technical security and chip hardware design by modeling the operations from a secure and dependable control perspective and developing innovative defense mechanisms that can be applied to emerging smart healthcare devices. Finally, by adding low-resource chip design, the team will advance manufacturing techniques for chip-based devices adding additional security features without impact to overall performance or lifetime.


PATCH of Asclepius: Technology for Cybersecure Healthcare (PATCH) – ARPA-H

  • Kevin Fu (Principal Investigator), Northeastern University
  • Julian M Goldman (Co-Principal Investigator) MGH, Harvard University
  • Jennifer R Amos (Co-Principal Investigator), University of Illinois Urbana-Champaign
  • David Brumely (Co-Principal Investigator), Carnegie Mellon University (CMU)
  • and many more!

Amos is part of the Universal PatchinG and Remediation for Autonomous DEfense (UPGRADE) initiative. Called PATCH, the first 12-month phase of this ambitious project will develop digital twins of healthcare networks to accelerate vulnerability detection and remediation while maintaining uninterrupted patient care.  The vision is to support hospital cybersecurity teams by expediting their ability to comprehensively characterize their hospital’s cyber network, identify vulnerabilities within that network, source remediations to mitigate the vulnerabilities, and accelerate remediation deployment.