Instructors: Samuel Pinilla, Email: Spinilla@ieee.org. Kumar Vijay Mishra, Email: kvm@ieee.org.

Abstract: This short course provides an accessible introduction to invex optimization from a signal processing perspective. While convex formulations are widely used due to their guarantees of global optimality, they rely on idealized assumptions-such as noiseless measurements and precisely modeled priors-that often do not hold in real-world scenarios. In practice, measurement noise is pervasive, and convex regularizers may inadequately capture key data properties like sparsity, low-rankness, smoothness, or anomalies. Although non-convex constrained optimization methods often yield superior reconstruction quality compared to their convex counterparts, ensuring global optimality remains a fundamental challenge. Invex optimization offers a promising alternative, as an invex function guarantees that any critical point is a global minimizer. This short course explores recent advances in invex optimization for constrained inverse problems, covering theoretical foundations, algorithmic developments, and practical applications across various domains, including machine learning, imaging, and signal processing. A key focus is signal restoration, a crucial inverse problem with applications spanning physics, medical imaging, and engineering. Ensuring global optimality in such problems is essential for obtaining the most accurate solutions within given constraints. This short course aims to foster interdisciplinary collaboration, bridging different areas of signal processing and deepening our understanding of nonconvex inverse problems.

Outline
Half-day

• Fundamentals in convex optimization
• Optimization methods
• Advances in invex optimization
• Invexity Applications in Image/Signal Processing and Machine Learning
• Discussion/Q&A

Samuel Pinilla received the B.S. degree (cum laude) in Computer Science in 2014, the B.S. degree in Mathematics, and the M.S degree in Mathematics from Universidad Industrial de Santander, Bucaramanga, Colombia in 2016 and 2017, respectively. His Ph.D. degree from the Department of the Electrical and Computer Engineering, Universidad Industrial de Santander, Bucaramanga, Colombia. He is a senior data scientist at the Rutherford Appleton Laboratory, United Kingdom. In the past, Dr. Pinilla held Visiting Postdoctoral Researcher positions at Tampere University 2020-2021 and worked as a fellow research associate at The University of Manchester 2021-2022. His research interests focus on the areas of high-dimensional structured signal processing, machine learning, scalable AI, and (non)convex optimization methods. Dr. Pinilla is the recipient of the Eloy Valenzuela Prize for his doctoral studies, the International Conference on Acoustics, Speech and Signal Processing top 3% Paper Recognition in 2023.

Kumar Vijay Mishra obtained a Ph.D. in electrical engineering and M.S. in mathematics from The University of Iowa in 2015, and M.S. in electrical engineering from Colorado State University in 2012, while working on NASA's Global Precipitation Mission Ground Validation (GPM-GV) weather radars. He received his B. Tech. summa cum laude (Gold Medal, Honors) in electronics and communication engineering from the National Institute of Technology, Hamirpur (NITH), India in 2003. He is a Senior Fellow at the United States DEVCOM Army Research Laboratory; Research Scientist at the Institute for Systems Research, The University of Maryland, College Park under the ARL-ArtIAMAS program; Technical Adviser to Singapore-based automotive radar start-up Hertzwell; and honorary Research Fellow at SnT - Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg. Previously, he had research appointments at the Electronics and Radar Development Establishment (LRDE), Defence Research and Development Organisation (DRDO) Bengaluru; IIHR - Hydroscience & Engineering, Iowa City, IA; Mitsubishi Electric Research Labs, Cambridge, MA; Qualcomm, San Jose; and Technion - Israel Institute of Technology. Dr. Mishra has served as the Distinguished Lecturer (DL) of various societies: IEEE Communications Society (2023-2024), IEEE Aerospace and Electronic Systems Society (AESS) (2023-2024, 2025, 2026), IEEE Vehicular Technology Society (2023-2025, 2025-2027), and IEEE Geoscience and Remote Sensing Society (2024-2025). He has been a Virtual DL of IEEE Future Networks Initiative (2022) and Traveling Lecturer of Optica (2025-). He is the recipient of the IEEE Signal Processing Society Pierre-Simon Laplace Early Career Technical Achievement Award (2024), Special Mention for the IEEE AESS M. Barry Carlton Award (2023), IET Premium Best Paper Prize (2021), IEEE T-AES Outstanding Editor (2021, 2023, 2024), U. S. National Academies Harry Diamond Distinguished Fellowship (2018-2021), American Geophysical Union Editors' Citation for Excellence (2019), Royal Meteorological Society Quarterly Journal Editor's Prize (2017), Viterbi Postdoctoral Fellowship (2015, 2016), Lady Davis Postdoctoral Fellowship (2017), DRDO LRDE Scientist of the Year Award (2006), NITH Director's Gold Medal (2003), and NITH Best Student Award (2003). He has received Best Paper Awards at IEEE MLSP 2019 and IEEE ACES Symposium 2019. Dr. Mishra is Chair (2023-2026) of the International Union of Radio Science (URSI) Commission C, Chair (2025-) of IEEE AESS Technical Working Group on Integrated Sensing and Communications (ISAC-TWG), and Vice-Chair (2021-present) of the IEEE Synthetic Aperture Standards Committee, which is the first SPS standards committee. He has been Chair (2023-2025) of the IEEE SPS Synthetic Apertures Technical Working Group. He has been an elected member of three technical committees of IEEE SPS: SPCOM, SAM, and ASPS, and IEEE AESS Radar Systems Panel. He is Editor-in-Chief of River Rapids Series in Radar Systems, Signal Processing, Antennas and Electromagnetics (2025-). He has been Senior Area Editor of IEEE Transactions on Signal Processing (2024-), Associate Editor of IEEE Transactions on Aerospace and Electronic Systems (2020-) and IEEE Transactions on Antennas and Propagation (2023-). He has been a lead/guest editor of several special issues in journals such as IEEE Signal Processing Magazine, IEEE Journal of Selected Topics in Signal Processing, IEEE Journal on Selected Areas in Communications, and IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. He is the lead co-editor of several books on signal processing and radar: Signal Processing for Joint Radar-Communications (Wiley-IEEE Press, 2024), Next-Generation Cognitive Radar Systems (IET Press Electromagnetics and Radar Series, 2023), Advances in Weather Radar Volumes 1, 2 & 3 (IET Press Electromagnetics and Radar Series, 2023), and Handbook of Statistics 55: Multidimensional Signal Processing (Elsevier). His research interests include radar systems, signal processing, remote sensing, and electromagnetics.

Instructors: Austin Egert, Email: austin.egert@arcfield.com. Jeff Steward, Email: jeff.steward@arcfield.com

Abstract: Dive into the exciting world of ionospheric physics in this engaging half-day course! We'll explore how scientists observe and model the ionosphere to improve HF communications.

Starting with observation strategies, you'll get hands-on experience analyzing real ionospheric data. Next, we'll uncover the secrets of ionosondes - cool instruments that 'sound out' the ionosphere. You'll learn to read ionograms like a pro and understand the difference between vertical and oblique soundings.

But wait, there's more! We'll venture into the cutting-edge realm of assimilative ionosphere models. Don't worry if that sounds complex - we'll break it down step-by-step. You'll see how these models use HF signals to create a clearer picture of the ionosphere and improve our ability to predict signal paths through raytracing. We will also introduce data assimilation and how that can be used to find optimal estimates of space weather forcing parameters and geophysical state.

Throughout the course, you'll participate in interactive demonstrations and practical exercises. By the end, you'll understand how all these pieces fit together to help us communicate better using HF signals.

Whether you're a curious student, an early-career scientist, or a seasoned researcher, this course offers a fun and accessible introduction to advanced ionospheric techniques. Join us for an electrifying journey through the upper atmosphere!

Outline
Half-day

1. Introduction
   1. Overview of the course
   2. Quick look at the ionosphere layers
   3. Brief introduction to ionospheric propagation and its importance in HF communications
2. Observing Strategies
   1. Different methods of observing the ionosphere
   2. Importance of observations in HF communications
3. Ionosondes
   1. What are ionosondes and how do they work?
   2. Types of ionosondes: Verticals and Obliques
   3. Interpreting ionograms
   4. Hands-on activity: Manual scaling with SAO-X
4. Vertical and Oblique Soundings
   1. Detailed explanation of vertical soundings
   2. Applications and limitations of vertical soundings
   3. Oblique soundings: principles and advantages
   4. Comparing vertical and oblique soundings
   5. Case study: Analyzing real-world vertical and oblique sounding data
5. A Brief Introduction to Data Assimilation
   1. Data assimilation concepts
   2. The Kalman Filter family
   3. The Variational (Var) family
   4. Hybrid methods
6. Assimilative Ionosphere Models
   1. Introduction to assimilative modeling
   2. Using HF signals in assimilative ionosphere models
   3. Applying assimilative ionosphere models in raytracing
   4. Practical exercise: Using a simple assimilative model for raytracing
7. Conclusion and Q&A

Austin Egert has extensive experience modeling planetary science, ionospheric physics, and over-the-horizon radar. That means he fights with computer languages and has won enough times to become a scientist. He has also spent many hours cathartically scaling ionograms while listening to dubstep or heavy metal opera. That ultimately landed him with Orion Space Solutions where he happily continues fusing bass-heavy music with space physics.

Jeff Steward has been called the Michelangelo of data assimilation, which sounded like a complement until he remembered that's one of the Ninja Turtles. But since he does like pizza, he decided that's alright. After his Ph.D. at Florida State, Jeff worked at NASA JPL and NCAR doing data assimilation of satellite data. He now works at Orion Space Solutions learning about space weather and applying data assimilation there.

Instructor: Charles Baylis, Email: Charles_Baylis@baylor.edu

Abstract: This workshop overviews radio spectrum management and innovation, providing radio scientists understanding of basic issues and challenges in spectral coexistence. Topics include an overview of spectrum management practices, challenges in spectrum sharing for different types of wireless systems (communication, radar, and passive scientific systems), present movements and decisions, and areas of ongoing and needed innovation. The workshop will allow radio scientists to gain a holistic understanding of challenges and practices in spectrum management and coexistence, informing them in designing radio systems to succeed in the ever-complicated spectral environment.

Outline
Half-day

• Overview of Radio Spectrum Issues
• Spectrum Regulations
• Current Regulatory Activities Panel
• Break
• User Communities Panel
• Technology Innovations Panel
• Adjourn

Dr. Charles Baylis serves as a Professor of Electrical and Computer Engineering at Baylor University and Director of SMART Hub, a Department of Defense Spectrum Innovation Center consisting of 25 researchers across 15 universities. Dr. Baylis has served at Baylor since 2008, where he co-founded and still directs the Wireless and Microwave Circuits and Systems Program. He received the Ph.D. in Electrical Engineering from the University of South Florida in 2007 and served on the USF faculty from 2007-2008 before joining Baylor. His research interests are reconfigurable microwave circuits and systems to enable adaptive spectrum sharing, as well as the intersection of spectrum policy and technology.

Instructors: Sima Noghanian, Email: sima_noghanian@ieee.org. Ifana Mahbub, Email: Ifana.Mahbub@UTDallas.edu.

Abstract: Wireless power transfer (WPT) is a transformative alternative to traditional battery-powered biomedical devices, which often require surgical replacement. By using implanted coils and antennas, WPT enables continuous, non-invasive power delivery for applications such as implantable sensors, drug delivery systems, and neurostimulators. Two main WPT methods are magnetic coupling and radiative transfer, each with trade-offs in efficiency and depth. Designing effective systems involves addressing challenges like miniaturization, biocompatibility, and safety, particularly with regard to Specific Absorption Rate (SAR) limits. This workshop will cover fundamental concepts of WPT for biomedical applications, compare magnetic and radiative transfer methods, and discuss current challenges and research directions. It will also include modeling and simulation techniques, safety considerations, and experimental validation approaches to equip participants with practical knowledge for designing efficient and safe WPT systems.

Outline
Half-day

• Introduction to WPT
• Tissue Dielectric Properties
• Inductive WPT and Examples
• Radiative WPT and Examples
• Power Transfer Efficiency
• Metasurfaces and Power Focusing
• Simulation Consideration
• Specific Absorption Rate (SAR) Analysis
• Thermal Analysis
• Summary

Sima Noghanian is currently a Distinguished Hardware Engineer at CommScope Ruckus Networks. She is also an Antenna/RF consultant with Neuspera Medical Inc and StrokeDx. Dr. Noghanian received a Ph.D. from the University of Manitoba in 2001, and a Post-Doctoral Fellowship from the Natural Sciences and Engineering Research Council of Canada, which she took at the University of Waterloo. From 2002 to 2018 she served as an Electrical Engineering faculty in: the Sharif University of Technology, Iran (2002), the University of Manitoba, Canada (2003-2008), and the University of North Dakota, USA (2008 - 2018). She also served as the Chair of the Electrical Engineering Department at the University of North Dakota (2014 - 2016). She was an Electromagnetic Application Engineer with PADT Inc. (2019 - 2020) and a Principal Antenna Design Engineer at Wafer LLC (2020 - 2021).

Dr. Noghanian is a senior member of IEEE, a fellow of the Applied Computational Electromagnetics Society (ACES), and a senior member of URSI Commissions B and K. Dr. Noghanian currently serves as the Associate Editor of IEEE Transactions on Antennas and Propagation, IEEE Open Journal of Antennas and Propagation, IEEE Antennas and Propagation Magazine, IET Microwave, Antennas and Propagation, Frontiers in Antennas and Propagation. and as an area editor for the Elsevier International Journal of Electronics and Communications. She is a member of the IEEE Antennas and Propagation Society (AP-S) Administration Committee (2023-2025), Chair of the Technical Committee on Antenna Measurement (TCAM), Vice Chair of AP-S Constitution and Bylaws Committee, Chair of USNC-URSI Commission K, and Vice President of ACES. She is an AP-S Distinguished Lecturer (2024-2026). She is also a Distinguished Lecturer of IEEE AP-S.

Ifana Mahbub is an Associate Professor and the Texas Instruments Early Career Chair Awardee in the Department of Electrical and Computer Engineering at the University of Texas at Dallas, where she leads the Integrated Biomedical, RF Circuits and Systems Laboratory (iBioRFCASL). Her research spans wireless power transfer for implantable and wearable biomedical devices, IoT systems, UAVs, and long-range power beaming using microwave and millimeter-wave technologies. She is particularly focused on developing scalable, efficient, and safe wireless energy delivery systems that enable untethered operation in dynamic or infrastructure-limited environments.

Dr. Mahbub received her B.Sc. degree (2012) in Electrical and Electronic Engineering from the Bangladesh University of Engineering and Technology, and her Ph.D. degree (2017) in Electrical Engineering from the University of Tennessee, Knoxville. She is the recipient of several prestigious honors, including the NSF CAREER Award (2020), DARPA Young Faculty Award (2021), and the DARPA Director's Fellowship (2023).

She currently serves as Vice-Chair for the USNC-URSI Commission K and as an Associate Editor for the IEEE Transactions on Antennas and Propagation. She is also a full member of the IEEE MTT-S Technical Committee 25 (Wireless Power Transfer and Energy Conversion) and the IEEE AP-S Technical Committee on Health and Medicine.