invited speakers

Title: Impedance Modification of Infrared Antennas
Dr. Glenn D. Boreman Prof and Chair, Dept. of Physics & Optical Science Director, Center for Optoelectronic & Optical Commun. University of North Carolina at Charlotte, Charlotte NC 28223-0001 Email: gboreman (at) charlotte.edu
Summary: Wave impedance on IR-frequency transmission lines is measured at 30 THz using a scanning-tunneling microscope. We experimentally demonstrate designs meant to increase the IR-antenna impedance so as to provide a better match to high-impedance sensors. We will also provide an update on the recent establishment of the College of Science at Charlotte.	Glenn Boreman, Ph.D.
Speaker Biography: Glenn Boreman is, since 2011, Professor and Chair of the Department of Physics & Optical Science at the University of North Carolina at Charlotte. From 1984 to 2011 he was on the faculty of the University of Central Florida. He has supervised 27 PhD students to completion, and has held visiting research positions at Imperial College (London), Universidad Complutense (Madrid), ETH (Zürich), and the Swedish Defense Research Agency (Linköping). He received the BS in Optics from the University of Rochester, and the PhD in Optics from the University of Arizona. Prof. Boreman is coauthor of the graduate textbooks Infrared Detectors and Systems and Infrared Antennas and Resonant Structures, and author of Modulation Transfer Function in Optical & Electro-Optical Systems and Basic Electro-Optics for Electrical Engineers. He has published more than 200 refereed journal articles in the areas of infrared sensors and materials, optics of random media, and image-quality assessment. He is a fellow of SPIE, IEEE and OSA. Prof. Boreman served as the 2017 President of SPIE.

Title: Developing an Autonomous All-Terrain Vehicle - Control and Perception
Prof. James M. Conrad Professor and Associate Chair Dept. of Electrical and Computer Engineering UNC Charlotte, 9201 University City Blvd, Charlotte, NC 28223 Email: jmconrad@charlotte.edu
Abstract: Autonomous vehicles are coming! Well, they are already here, but you can expect them to be more prevalent in the coming years. The range of these types of vehicles today include automobiles, 18-wheel trucks/trailers, farm equipment, and construction equipment. All of these rely on maps, GPS and other technologies (LIDAR, Camera) for localization and obstacle avoidance, but they typically do not build their own maps. Therefore, in GPS-denied environments, they are “driving blind”. Dr. Conrad’s research uses LIDAR and camera data to assist in navigation in GPS-denied environments, particularly in forest environments. He will present information about how his research team has created an autonomous All-terrain vehicle (ATV) that can autonomously drive on paths in a forest. He will also present on the technology his team has developed to allow an ATV to follow people or vehicles in any environment.	James Conrad, Ph.D.
Speaker Biography: James M. Conrad received his bachelor's degree in computer science from the University of Illinois, Urbana, and his master's and doctorate degrees in computer engineering from North Carolina State University. He is currently a professor at the University of North Carolina at Charlotte. He also serves as the ECE Department Associate Chair for Computer Engineering and Undergraduate Director. He has served as an assistant professor at the University of Arkansas and as an instructor at North Carolina State University. He has also worked at IBM, Ericsson/Sony Ericsson, and BPM Technology. Dr. Conrad is a Professional Engineer, a Senior Member of the IEEE and a Certified Project Management Professional (PMP). He served on the IEEE Board of Directors as Region 3 director for 2016-2017, and again as a director in 2020 when he also served as IEEE-USA President. He also served as IEEE-Eta Kappa Nu Honor Society President in 2022. He is the author of numerous books, book chapters, journal articles, and conference papers in the areas of embedded systems, robotics, parallel processing, and engineering education.

Title: Tackling Road Congestion through Machine Learning, Hierarchical Graphs, and Just-in-Time Congestion Response
Megan L Johnson - Mathematics   SUNY Fredonia, NY, USA Contributors: Syed Ali Haider (SUNY Fredonia), Sahar Idwan (The Hashemite University, Zarqa, Jordan), Junaid. A. Zubairi (SUNY Fredonia), and Wael Etaiwi (Princess Sumaya University for Technology, Amman, Jordan).
Summary: Road congestion poses a colossal problem for urban centers, resulting in a significant loss of productivity, unnecessary amounts of fossil fuel waste, and harmful reductions in emergency response time. While congestion may never be eliminated, leveraging AI and IoT can help cities reduce and prevent gridlock. This talk will explore the interrelated aspects of congestion mapping, management, and mitigation in Smart Cities through machine learning and graph-based approaches. We aim to provide insights into the cutting-edge solutions to address traffic congestion and improve urban residents' overall quality of life in Smart Cities.	Megan Johnson, Ph.D.
We will begin by discussing machine learning approaches to mapping congestion and training navigation systems to avoid real-time road congestion. We will use simulated and actual data from the New York Department of Transport for a portion of Manhattan to demonstrate this road congestion avoidance scheme. In addition, this talk will examine a hierarchical graph-based method to reduce the number of node-based computations and an algorithm to compute the ideal path between source and destination nodes. In doing so, we will discuss how hierarchical graphs provide a structured representation of road networks, enabling a more targeted and responsive approach to congestion management. Our talk will conclude by discussing an algorithm that leverages real-world data and dynamic routing to ensure first responders reach their destinations faster, potentially saving lives. Guidance from the National Fire Protection Association indicates that a 6-minute arrival time should be standard when responding to emergencies. Fire and emergency departments are rarely able to achieve this standard in dense urban cities because of almost constant traffic congestion. This novel, just-in-time approach aims to clear congestion along the preferred route to the emergency scene. Implementing this algorithm in Smart Cities could save lives and decrease property loss.
Speaker Biography: Dr. Megan Johnson is an Assistant Professor in the Department of Mathematical Sciences at The State University of New York at Fredonia. Her research focuses on vector representations of persistent homology and their use in machine learning. Dr. Johnson's research interests also include designing and implementing computational algorithms for topological data analysis, clustering, and data science in general. She recently joined the faculty at SUNY Fredonia following a postdoc at Binghamton University and the successful completion of her Ph.D. at the University at Buffalo, SUNY, where she received a Doctoral Dissertation Fellowship Award.

Title: Increasing internet bandwidth for IoT with silicon photonics enabled by GeSn alloys
Jay Mathews, Ph.D. Department of Physics and Optical Science University of North Carolina at Charlotte Charlotte, NC, USA
Abstract: The Internet of Things will require increasing internet bandwidth to handle the increase in data transmission from the large number of devices that will be connected. Photonic integrated circuits could be used to enhance routing speeds for fiber optic networks. By using silicon as the platform, costs can belowered due to mass manufacturing and monolithic integration. GeSn alloys grown on Si could be used to help achieve this goal as a material for infrared light generation and detection.	Jay Mathews, Ph.D.
Speaker Biography: Dr. Jay Mathews is currently an Associate Professor in the Department of Physics and Optical Science at the University of North Carolina at Charlotte. He obtained his BS with double major in Physics and Mathematics from Colorado State University in 2007, and he received his PhD in Physics from Arizona State University in 2011. Following graduation, Dr. Mathews was awarded a fellowship in the National Academy of Sciences Research Associateship Program, where he performed research for US Army CAPCOM Benét Laboratories in Watervliet, NY. In 2013, he joined the Physics department at University of Dayton, where he served as Assistant and then Associate Professor. He joined the faculty at UNC Charlotte in 2023. Dr. Mathews’ research is focused on photonic materials and devices. He received an Air Force Office of Scientific Research Young Investigator Award in 2016, and he was awarded the 2019 Diversity and Inclusion Advocacy Recognition prize from Optica (formerly OSA).

Title: Next Gen Video for Humans and Machines
Hari Kalva, Ph.D. - Interim Chair and Professor   Department of Electrical Engineering and Computer Science,   Florida Atlantic University
Abstract: Video-enabled sensors are powerful devices that, together with video analytics, can serve as multi-function sensors. A video sensor can be used to detect, count, identify, and classify humans and/or objects and even their actions. Large scale use of low-cost video devices requires efficient machine processing for timely and efficient decision support. The large amount of video generated by such devices requires significant network, storage, and computing resources.	Hari Kalva, Ph.D.
New approaches to compression, analysis, and scalability that target machines are being developed. This new area referred to as video coding for machines (VCM) focuses on video representation, compression, and analytics targeting machine consumption of video. This talk provides an overview of VCM, challenges, and recent developments in ISO and ITU standardization efforts to address these challenges.
Speaker Biography: Hari Kalva, is the Interim Chair and Professor in the Department of Electrical Engineering and Computer Science at the Florida Atlantic University. Kalva is a renowned expert in visual computing with a focus on applications in video compression, communication, intelligent surveillance, health care, and environmental conservation. He holds 65 patents and over 100 pending patent applications. Kalva has made key contributions to ISO/ITU video technology standards related to compression, representation, and analytics. His inventions include several standards essential patents that have been licensed and used in virtually all modern video streaming products and services. He has published over 150 peer-reviewed articles and authored two books. Kalva received his Ph.D. in Electrical Engineering from Columbia University in 2000, M.S. in Computer Engineering from Florida Atlantic University, and a B.Tech. in Electronics and Communications Engineering from N.B.K.R. Institute of Science and Technology, S.V. University, India in 1991. Kalva is a Senior Member of the IEEE and a Fellow of the National Academy of Inventors.