Presenter:    Prof. Ayse Tekes, Kennesaw State University (KSU)

Duration: 2h

Abstract. Kinematic and dynamic modeling of mechanisms is essential for optimizing their geometry and controlling their motion. However, deriving the mathematical model becomes increasingly complex as the design’s complexity and degree of freedom of motion increase. Advancements in additive manufacturing and technology have enabled us to design and develop compliant mechanisms and soft robots. Soft robotics is an emerging technology with superiorities over traditionally designed rigid robotics. A soft robot is characterized by several distinctive features such as elastic bodies, increased degree of freedom due to their large deflection, fabrication by unconventional materials, and the inclusion of intrinsic passive elements. Compliant mechanisms, which are considered the center of soft robotics, comprise flexible components that go under elastic deformation to accomplish desired tasks. This inherent property of compliant mechanisms leads to compelling advantages such as creating highly repeatable motion for high precision applications (more like flexible linkages) and possessing a high degree of freedom motion that cannot be achieved by traditional rigid mechanisms (such as soft robots). They form the base of soft robotics, or alternatively, soft robotics can be seen as an application area of high mobility flexible mechanisms. Despite their advantages and superiorities over rigid mechanisms, optimizing the stiffness of flexible links and dynamic properties of complex and high-mobility designs is increasingly challenging. Additionally, the largest challenge in the design and modeling of compliant mechanisms is understanding the deformation of the two bodies when connected along with their interaction in complex cases. Simscape is a toolbox in MATLAB that consists of a library to design and simulate mechanical and electromechanical systems. The toolbox allows the user to design complex rigid, compliant, and soft mechanisms while animating the motion in the mechanics explorer.

This workshop will guide participants through the steps to design and develop models in MATLAB Simscape, a tool that facilitates rapid analysis.

Presenter:     Dr. Soheyla Amirian, University of Georgia

Duration: 4h

Abstract. Artificial intelligence (AI) has already demonstrated very successful performance in a variety of healthcare settings, ranging from disease diagnosis to predicting patient and clinical outcomes. However, the “black-box” nature of many AI algorithms can pose challenges in clinical applications, where AI-powered decisions need to be clearly justified and understood. eXplainable AI (XAI) addresses these concerns by making AI models more explainable, transparent, interpretable, and accountable. As the healthcare industry increasingly adopts AI technologies to improve diagnosis, treatment, and patient care, the need for transparency and interpretability in AI systems has become paramount. This half day tutorial on “eXplainable AI (XAI) in Clinical Applications” will delve into the intersection of AI and healthcare, mainly focusing on the critical aspect of XAI.

Presenter:     Prof. Varadraj Prabhu Gurupur, University of Central Florida

Duration: 2h

Prerequisites: None

Abstract. The workshop will focus on efforts made by the IEEE Standards ICAD workgroup on Data Quality of Electronic Health Records. The workgroup has the following goals: i) developing a method to create unique identifiers for each electronic healthcare vendor; thereby, identifying the electronic health record system used to create the electronic health record, ii) developing a methodology allowing each electronic health record vendor to create identifiers identifying the healthcare provider responsible for creating the electronic health record, iii) introduction of a system to measure the completeness of electronic health records, and iv) identify parameters for measuring the quality of electronic health records. The tutorial will focus on the critical progress made by this work group and invite comments and participation from the participants of the tutorial.

Bio. Varadraj Gurupur, PhD is currently working as an Associate Professor with the School of Health Management and Informatics and has a joint appointment with the Department of Computer Science, and Department of Electrical and Computer Engineering with the University of Central Florida (UCF). He is also the founding member of the Decision Support Systems and Informatics Lab at UCF. Dr. Gurupur received his Doctoral degree in Computer Engineering from the University of Alabama at Birmingham in 2010. He has been actively involved with IEEE since 2009 and was elevated to senior member in 2017. He served as a conference chair for the IEEE Orlando section in 2018, as the secretary in 2019 and as a Vice Chair in 2020. Under his leadership the IEEE Orlando section has received the GOLD recognition from IEEE MGA. Dr. Gurupur is a recipient of two international awards, two national awards, and several regional and institutional awards. This includes the prestigious AHIMA Research Award in the year 2017, and the AHIMA Triumph Award for Innovation in 2021. His core research is focused on software engineering decision support systems for healthcare and education. Dr. Gurupur is also someone who has worked in the healthcare industry for several years. Based on this work experience and academic training he is involved in discovering innovative solutions to difficult problems associated with Electronic Health Records. Dr. Gurupur has more than 100 publications which include: edited book, book chapters, journal articles, conference papers, abstracts, and published reviews. Additionally, he has been involved in many research projects funded by the United States Federal government agencies such as National Science Foundation, and National Institutes of Health

Presenter:     Prof. Sumit Chakravarty, Kennesaw State University

Duration: 4h

Prerequisites: None

Abstract. This workshop on SDR Basics provides a forum for introducing Software Defined Radios primarily to Young Professionals, Undergraduate/Graduate students, and novice users of this tool. We plan to highlight the benefits of using SDR, showcase a few popular SDRs (RTL, Hack RF, Pluto), and provide hands-on interaction with these SDRs using interface platforms like GNU Radio and MATLAB. Additionally, we will discuss the potential use of SDRs in the next generation of communications by implementing wireless communication techniques like beamforming, beam jamming, and joint sensing/communication paradigms on SDRs.

Bio. Dr. Sumit Chakravarty currently works as an Associate Professor of Electrical Engineering with Kennesaw State University. He also serves as the MSECE program coordinator. He completed his doctoral studies from University of Maryland, Baltimore County and his Master of Science from Texas A&M University, Kingsville, both in Electrical Engineering. His PhD dissertation is on analysis of Hyperspectral Signatures and Data. He has multiple peer-reviewed journal publications, conference publications, a book chapter and three granted patents. His area of expertise is Wireless Communications, AI and Signal Processing.

Proposed Agenda:

1. SDR theory and background
2. Use of SDR in listening to common signals
3. SDR capabilities and improvement
4. SDR for radar signal jamming / anti-jamming
   
   1. Generating jamming signals/sending jamming signals
   2. Listening to jamming signals
   3. Analysis of jamming signals using Deep learning/ semantic communications
5. Summary & Conclusions

Presenter:     David Huggins, Georgia Tech Research Institute

Duration: 2h

Abstract. Details available soon