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1. Undergraduate Robotics Education with General Instructors Using a Student-Centered Personalized Learning Framework

   Wu, R; Dascalu, S; Zhu, Z; Feil-Seifer, D; Ringler, M; Hutchins, B; Rosof, L; Shill, P; Jamali, H; Harris, F (June 2024, ASEE 2024 Conference)

   Recent advancements in robotics, including applications like self-driving cars, unmanned systems, and medical robots, have had a significant impact on the job market. On one hand, big robotics companies offer training programs based on the job requirements. However, these training programs may not be as beneficial as general robotics programs offered by universities or community colleges. On the other hand, community colleges and universities face challenges with the required resources, especially qualified instructors, to offer students advanced robotics education. Furthermore, the diverse backgrounds of undergraduate students present additional challenges. Some students bring extensive industry experience, while others are newcomers to the field. To address these challenges, we propose a student-centered personalized learning framework for robotics. This framework allows a general instructor to teach undergraduate-level robotics courses by breaking down course topics into smaller components with well-defined topic dependencies, structured as a graph. This modular approach enables students to choose their learning path, catering to their unique preferences and pace. Moreover, our framework's flexibility allows for easy customization of teaching materials to meet the specific needs of host institutions. In addition to teaching materials, a frequently-asked-questions document would be prepared for a general instructor. If students' robotics questions cannot be answered by the instructor, the answers to these questions may be included in this document. For questions not covered in this document, we can gather and address them through collaboration with the robotics community and course content creators. Our user study results demonstrate the promise of this method in delivering undergraduate-level robotics education tailored to individual learning outcomes and preferences. 

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2. Work in Progress: Developing an AI-Enhanced Immersive Curriculum for Environmental Robotics

   https://doi.org/10.1109/EDUNINE62377.2025.10981342  

   Peterson, Eric; Bogosian, Biayna; Vassigh, Shahin; Murad-Reis, Gregory; Polyzou, Agoritsa; Narula, Bhavleen Kaur (March 2025, IEEE)

   A convergence of technology advancements including spatial computing, augmented reality (AR), and artificial intelligence (AI) can now support the personalization of learning environments and dynamically respond to learner performance data with personalized feedback. Augmented Learning for Environmental Robotics (ALERT), leverages advances in technology to research, develop, and test an augmented reality-enhanced (AR) curriculum for learning how to develop and use robotic environmental monitoring tools for collecting data on environmentally sensitive construction sites. With this project, our research team aims to develop the ALERT curriculum as an immersive learning environment, implement automation processes that dynamically adjust to learner performance, and address a pressing problem in the construction sector with recent advances in small robotics and remote sensing. 

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3. Real-Time Operating Systems for Cyber-Physical Systems: Current Status and Future Research

   https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics50389.2020.00080  

   Serino, Anthony; Cheng, Liang (November 2020, IEEE International Conference on Cyber Physical and Social Computing (CPSCom-2020))

   null (Ed.)

   This paper studies the current status and future directions of RTOS (Real-Time Operating Systems) for time-sensitive CPS (Cyber-Physical Systems). GPOS (General Purpose Operating Systems) existed before RTOS but did not meet performance requirements for time sensitive CPS. Many GPOS have put forward adaptations to meet the requirements of real-time performance, and this paper compares RTOS and GPOS and shows their pros and cons for CPS applications. Furthermore, comparisons among select RTOS such as VxWorks, RTLinux, and FreeRTOS have been conducted in terms of scheduling, kernel, and priority inversion. Various tools for WCET (Worst-Case Execution Time) estimation are discussed. This paper also presents a CPS use case of RTOS, i.e. JetOS for avionics, and future advancements in RTOS such as multi-core RTOS, new RTOS architecture and RTOS security for CPS. 

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4. Advances in Artificial Intelligence-Based Medical Devices for Healthcare Applications

   https://doi.org/10.1007/s44174-025-00379-1  

   Tettey-Engmann, Felix; Parupelli, Santosh_Kumar; Bauer, Steven_R; Bhattarai, Narayan; Desai, Salil (May 2025, Biomedical Materials & Devices)

   Abstract Medical devices play a crucial role in modern healthcare, providing innovative solutions for diagnosing, preventing, monitoring, and treating ailments. Artificial Intelligence is transforming the field of medical devices, offering unprecedented opportunities through diagnostic accuracy, personalized treatment plans, and enhancing patient outcomes. This review outlines the applications of artificial intelligence-based medical devices in healthcare specialties, especially in dentistry, medical imaging, ophthalmology, mental health, autism spectrum disorder diagnosis, oncology, and general medicine. Specifically, the review highlights advancements such as improved diagnostic accuracy, tailored treatment planning, and enhanced clinical outcomes in the above-mentioned applications. Regulatory approval remains a key issue, where medical devices must be approved or cleared by the United States Food and Drug Administration to establish their safety and efficacy. The regulatory guidance pathway for artificial intelligence-based medical devices is presented and moreover the critical technical, ethical, and implementation challenges that must be addressed for large-scale adoption are discussed. The review concludes that the intersection of artificial intelligence with the medical device domain and internet-enabled or enhanced technology, such as biotechnology, nanotechnology, and personalized therapeutics, enables an enormous opportunity to accelerate customized and patient-centered care. By evaluating these advancements and challenges, the study aims to present insights into the future trajectory of smart medical technologies and their role in advancing personalized, patient-centered care. 

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5. Adding Domain-Specific Features to a Text-Editor to Support Diverse, Real-World Approaches to Time Management Planning

   https://doi.org/10.1145/3544548.3581536  

   Wiese, Jason; Lund, John R.; Kabir, Kazi Sinthia (April 2023, ACM)

   Many tools are designed to support users in maintaining or developing strong time management practices. Abandonment of these specialized tools is common, in favor of returning to a more general-purpose unstructured tool. How can designs leverage the familiarity of general-purpose tools and the advantages of specialized ones? We explore if applying a time-management-specific understanding of conventions and interactions within unstructured plaintext can be a successful approach to designing support for these tasks. We report the results of two field deployments (combined n=29) of “Plan” - a mobile application with a notes-application-based interface designed to support the practice of Time Management Planning. We show that modest, domain-specific modifications of general-purpose designs can facilitate users’ pre-existing workflows and nudge them towards better practices while leaving interfaces familiar and flexible. However, those with minimal planning experience desired additional structure. 

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