[] Google search for the term ‘software defined vehicles’ returned about 646M results in 0.33 seconds. The automotive industry is awash with this new buzz phrase. In their report “Rewiring car electronics and software architecture for the Roaring 2020s,” futurists from McKinsey & Company are heralding sweeping industry transformation both technically and commercially. We, GM, are making a splash with our Ultifi Platform that reimagines what it means to own and experience a vehicle and to grow revenue beyond vehicle sales. But what does all this mean for our vehicles – where the rubber meets the road, literally?! This talk will explore the software defined future from a vehicle point of view. Using examples of core vehicle functions like motion control – embedded software that makes our vehicles stop, turn & go – we will dive into the challenges and opportunities that lie ahead and how we can all engage and shape this exciting future. Co-sponsored by: University of Michigan Ann Arbor - Student Branch Speaker(s): Ankur Ganguli Agenda: 3:00 - 3:05 - Sign in and welcome , chapter and section business and announcements 3:10 - 4:00 - Invited Speaker Lecture 4:00 - 5:00 – Q & A; networking Room: 2365, Bldg: Leinweber Computer Science & Information Building, 2200 Hayward St, Ann Arbor, Michigan, United States, 48109

Workshop Overview Location: UM-Dearborn (ELB 2390) Duration: 1.5 hours Target Audience: Graduate students and early-career engineers Format: Interactive with group exercises This hands-on workshop equips graduate students and young professionals with systematic approaches to engineering problem solving, covering the complete process from problem definition to solution implementation. Participants will learn industry-standard techniques including FMEA, 8D, root cause analysis, and decision-making frameworks while applying these methods through interactive case studies and team exercises. The session emphasizes practical skill development, helping attendees avoid common problem-solving pitfalls and build confidence in tackling complex technical challenges. Attendees will leave with immediately applicable tools and a structured framework for approaching engineering problems in both academic and professional settings. Co-sponsored by: Department of Electrical & Computer Engineering - University of Michigan @ Dearborn Room: ELB 2390, Dearborn, Michigan, United States, 48128

Title of the talk: Improving Software Quality: Strategies, Techniques, and Tools for Test Evolution Description: Maintaining high software quality requires test suites that keep up with frequent code changes, yet developers still struggle with deciding which tests to update, how to strengthen existing tests, and how to identify tests that no longer add value. This talk highlights three research contributions that address these challenges in test evolution. The first part introduces a technique that identifies tests affected by code changes in Continuous Integration and recommends tests that may need updates, making test maintenance more efficient. The second part compares manual test amplification with automated approaches, including techniques powered by Large Language Models. These automated methods substantially improve code coverage and bring complementary strengths, though their results still require validation. The final part presents insights into how and why developers delete tests. Most deletions are small and incremental and driven by project-specific needs, and current automated reduction techniques recover only some redundant tests. Together, these studies provide a data-driven view of how tests evolve and present techniques that support more effective and efficient test maintenance. Speaker: Prof. Ajay Jha, North Dakota State University Short bio: Dr. Ajay Jha is an Assistant Professor at North Dakota State University. Before joining NDSU, he spent over two years as a Postdoctoral Researcher at the University of Alberta and three years at Kyungpook National University, where he also earned his Ph.D. in 2017. He brings more than five years of industry experience, during which he co-founded two startups and worked as a business development manager in two organizations. At NDSU, he leads the Software Testing and Maintenance (STAM) Lab, where his research focuses on mining large-scale software repositories to uncover real-world challenges in software quality, reliability, and maintainability, and on developing new techniques and tools to address these issues. He has served as a session chair, program committee member, and reviewer for leading conferences and journals, including MSR, ICSME, IEEE TSE, and ACM TOSEM. Co-sponsored by: EECS, South Dakota State University Speaker(s): , Ajay Jha Room: 218, Bldg: Daktronics Engineering Hall, DEH 218, South Dakota State University, Brookings, South Dakota, United States, 57006

Title of the talk: Enhancing Localization Trustworthiness in GPS-Challenged Autonomous Systems   Abstract: Autonomous vehicles (AVs) and unmanned aerial vehicles (UAVs) rely extensively on GPS for navigation, leaving them exposed to spoofing and other localization attacks that can misdirect autonomous systems and undermine operational safety. This talk presents a structured progression of research aimed at strengthening localization security, beginning with single-sensor approaches that leverage inertial measurements and visual cues to detect inconsistencies between vehicle motion, reported GPS coordinates, and environmental context. Building on the insights gained from single-sensor modalities, the research advances toward multi-modal localization security, integrating information from LiDAR, cameras, IMUs, and geospatial map data to more reliably detect compromised positioning signals, particularly in GPS-challenged or adversarial environments. The talk also highlights emerging attack surfaces in both AV and UAV ecosystems, including vulnerabilities in broadcast identification, cooperative perception, and multi-modal AI models. Collectively, this work demonstrates how fused sensing and AI-driven analysis can significantly enhance the resilience and trustworthiness of next-generation autonomous systems. Speaker: Prof. Peng Jiang, University of Nebraska at Omaha Short Bio: Dr. Peng Jiang is an Assistant Professor of Cybersecurity at the University of Nebraska at Omaha (UNO). His research lies at the intersection of artificial intelligence and cybersecurity, with a particular focus on designing intelligent, adaptive systems that detect and mitigate emerging threats in wireless communications, autonomous vehicles, and other cyber–physical systems. He holds a B.S. in Communication Engineering from Chongqing University of Posts and Telecommunications (2014) and both an M.E. and Ph.D. in Electrical and Computer Engineering from Old Dominion University (2017 and 2024, respectively).He has received several awards and honors, including an NSF CISE Research Initiation Initiative (CRII) Award in 2025, the University of Nebraska at Omaha Research and Creative Activity Award in 2025, and the PEARC 2025 Best Paper Award. Co-sponsored by: EECS, South Dakota State University Speaker(s): Peng Jiang, Room: 218, Bldg: Daktronics Engineering Hall, DEH 218, South Dakota State University, Brookings, South Dakota, United States, 57006