Vasanth Rajendran of Amazon

Biography:

Vasanth Rajendran is an accomplished Engineering Lead and Researcher at Amazon, where he has been a driving force behind the technical evolution of Amazon Retail since 2019. Specializing in Artificial Intelligence, Machine Learning, and large-scale distributed systems, he currently oversees the technical architecture for some of the world’s most-visited digital surfaces, including Amazon Search, Product Detail Pages, and Browse. His work is centered on building high-concurrency, low-latency systems that bridge the gap between complex backend infrastructure and seamless customer experiences. Throughout his tenure at Amazon, Vasanth has spearheaded several high-impact initiatives, such as architecting distributed ML pipelines for search ranking that significantly reduced search abandonment and increased incremental revenue. He also designed region-aware infrastructure for product pages to deliver personalized content across diverse geographies and languages, leading to measurable gains in conversion and operational efficiency. By replacing static browse surfaces with fully automated, signal-driven machine learning pipelines, he has played a pivotal role in shifting Amazon toward a more dynamic, trend-aware discovery model. Beyond his engineering leadership, Vasanth is a respected figure in the global AI research community. He frequently serves as a reviewer for prestigious conferences like NeurIPS, ICLR, and IEEE, and has shared his expertise as a judge for student hackathons at MIT and UC Berkeley. His recent research into safety-assured frameworks for LLM autonomy in e-commerce—featured at the NeurIPS 2025 Workshop—reflects his commitment to the ethical and robust deployment of next-generation AI. Vasanth holds a Master of Science in Information Systems from the University of Illinois at Chicago and a Bachelor’s degree in Computer Science from Anna University.

David Aronchick of Expanso

CEO, Expanso

Biography:

David Aronchick is the CEO of Expanso, the company behind the open-source project Bacalhau, which enables fast, cost-efficient, and secure computation by running jobs where data is generated. A veteran of the tech industry, David has played a pivotal role in shaping modern cloud-native and machine learning ecosystems. Previously, he led Compute over Data at Protocol Labs and the Open Source Machine Learning Strategy at Microsoft Azure. During his time at Google, David spearheaded product management for Kubernetes, led the launch of the Google Kubernetes Engine (GKE), and co-founded the Kubeflow project. His background also includes leadership roles at Amazon and Chef, as well as co-founding three startups. When not working to improve distributed computing, David can be found skiing, exploring global cuisine, or spending time with his children.

Kaiqi Zhao of Oakland University

Assistant Professor CSE - Director, Efficient AI Lab, Oakland University

Biography:

Kaiqi Zhao is a tenure-track assistant professor in the Computer Science and Engineering Department at Oakland University, Michigan, since August 2024. She is the director of Efficient AI Lab. She earned her Ph.D. degree in the School of Computing and Augmented Intelligence at Arizona State University. Central to her research is innovating in model compression techniques to automatically and efficiently generate small, high-performance, and hardware-efficient machine learning/deep learning models, catalyzing the advancement of AI on edge devices. As the first author, she has published peer-reviewed papers at top-tier AI conferences, e.g., CVPR, AISTATS, ICASSP (Oral), and InterSpeech (Oral), and top-tier edge computing conferences, e.g., ACM/IEEE SEC (Best Poster Award). As a co-author, she has also published papers at top-tier system conferences, e.g., IEEE ICDCS, and prestigious edge computing conferences, e.g., USENIX HotEdge and USENIX OpML. She has been actively contributing to the research community by serving as a U.S. National Science Foundation (NSF) Reviewer (2025), Program Committee (PC) member for AAAI (2026-2023) and EdgeCAV (2025), Technical Program Committee (TPC) member for IEEE/ACM BDCAT, and the Conference Ph.D. Forum chair for ACM/IEEE SEC (2021). She has also served as invited reviewers for top-tier AI conferences, including NeurIPS (2022–2025), ICML (2022–2025), ICLR (2024–2025), AAAI (2023–2025), AISTATS (2024–2025), ICASSP (2024–2025), Interspeech (2023–2025), and AAMAS (2026), as well as for leading journals such as the IEEE Internet of Things Journal (Impact Factor: 11.1), IEEE Transactions on Knowledge and Data Engineering (Impact Factor: 10.4), IEEE Transactions on Neural Networks and Learning Systems (Impact Factor: 10.2), IEEE Transactions on Mobile Computing (Impact Factor: 9.2), IEEE Transactions on Circuits and Systems for Video Technology (Impact Factor: 8.3), and IEEE Transactions on Intelligent Vehicles (Impact Factor: 8.2).

Ajay Prasad of Dassault Systems

Biography:

Ajay Prasad is a Product Lifecycle Management (PLM) professional based out of the Metro Detroit area with 21+ years of experience & expertise in the implementation and technical sales of ENOVIA PLM across various industries. Ajay has a Bachelor of Engineering degree in Industrial Engineering & Management from RV College of Engineering, Bangalore, India and Master of Science in Computer Science from the University of Birmingham, UK. After graduating, he worked in mainframes technology and later in PLM, implementing and customizing ENOVIA solutions across industries like automotive, healthcare & industrial equipment working with customers across the globe. Ajay currently works as an ENOVIA Worldwide Industry Process Expert at Dassault Systemes being responsible for technical sales and go to market of ENOVIA PLM. He serves as a bridge between field teams, customers and product R&D in pre and post sales situations to foster customer success and adoption of ENOVIA PLM. He is also the "Knowledge and Know How Manager" responsible for securing data sources needed for developing AI powered experiences in ENOVIA PLM. Besides his career as a PLM professional, Ajay is also a Senior Member of IEEE and part of the Southeastern Michigan (SEM) section. He is also a US Patent holder and has published a technical paper in SAE besides authoring technical articles and opinions in Engineering.com and IEEE SEM Wavelengths.

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Raghu Nallapati of General Motors

Biography:

Raghu C Nallapati is a distinguished researcher and embedded software professional dedicated to shaping the future of transportation through advanced embedded systems and Artificial Intelligence. With 11 years of extensive experience in the automotive domain, Raghu has established himself as a leader in Software Defined Vehicle (SDV) architecture, embedded controls, autonomous, and law-enforcement technologies. Currently, Raghu is a Software Team Lead at General Motors, where he oversees Body Controls and Exterior Lighting Module software for next-generation platforms like the Blazer EV and Corvette. His technical command spans the full lifecycle of embedded development and release, from architectural design using AUTOSAR to rigorous testing across CAN, LIN, and Ethernet protocols. Beyond his corporate achievements, Raghu is a dedicated academic researcher pursuing a Doctor of Engineering in AI in Automotive at the University of Michigan. His doctoral work investigates the application of AI in law enforcement vehicles. He conducts this research in collaboration with the Law Enforcement Product Council (LEPC), focusing on predictive maintenance and situational awareness tools for policing. Raghu is committed to professional service and technical stewardship. He is an Associate Member of the International Association of Chiefs of Police (IACP), an IEEE Senior Grade Member, and an SAE Professional Member. As an active leader in the engineering community, he reviews technical paper manuscripts for SAE and various IEEE conferences. Additionally, as Chair of the IEEE SA P3734 working group officers for Artificial Intelligence-Enabled Performance and Safety Requirements in Police Vehicles, he plays a pivotal role in establishing industry standards for the safe deployment of AI in transportation.

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Sharan Kalwani of Oakland University

Biography:

Dr. Kalwani, A seasoned scientific, technical and computing professional, Sharan has spent over 30+ years’ experience in high performance computing, engineering applications, infrastructure, simulation, benchmarking, networking, operations, technical support and project management. He is a senior member of IEEE, ACM, SEMCO, ASEI. He has published a book on the topic: "UNIX and TCP/IP network security"; and is now working on his second text, about a new computer programming language. He also serves as one of the writers/editors of the IEEE Southeastern Michigan Sections monthly newsletter - Wavelengths. He has also served as Vice-Chair of IEEE Sustech 2023, IEEE Sustech 2022, IEEE SusTech 2021 Global Conferences and is the on the organizing committee for Online Forum for Climate Change Technologies 2023, 2024 and 2025 . He is the recipient of: * 2018 IEEE MGA Achievement award and * 2024 Engineering Society of Detroit (ESD) Anne O. Fletcher Award for his various contributions towards technical activities. On X he can be found @skalwani

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