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.

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).

Sharan Kalwani of IEEE Southeastern Michigan

These days it is getting fashionable to practically attach or prefix everything with the acronym AI (Artificial Intelligence) to it. What is little known is the huge compute power and infrastructure behind it all. This talk is designed to reveal a little bit of what is behind the curtains.

Biography:

Sharan Kalwani is an industry technology specialist with 25+ years of experience. Sharan has degrees in both Engineering and Computer Science. He has worked in many diverse areas and is a sought after speaker at many conferences and seminars, such as Supercomputing, HPC Advisory Council, SIAM, Infiniband Trade Association, AITP, etc. Sharan is a senior member of IEEE, an Emeritus member of Michigan!UNIX/user group (mug.org), member of Association for Computing Machinery (ACM), ASEI, ASEE and also leads the SIG-Linux section of SEMCO.org. He enjoys teaching, holds an Adjunct Faculty position at local educational sites. He has published one book "Linux and Internet Security" and is now working on his second text, about a new computer programming language. He is a recipient of the:

* 2018 IEEE MGA Achievement award,
* 2021 IEEE Region 4 Jack Sherman award,
* 2022 Robert Neff Section award, and
* 2023 IEEE Region 4 Outstanding Service award
* 2024 Engineering Society of Detroit (ESD) Anne Fletcher award

all for his contributions towards a diverse spectrum of member-centric activities.

He has been the Chair of the IEEE Southeastern Michigan Section since December 2021 and has held various officer roles for many of the Southeastern Michigan Units over the years. He also serves as one of the writers/editors of the Sections monthly newsletter - Wavelengths. He has also served as Vice-Chair of IEEE Sustech 2023, IEEE Sustech 2022, IEEE SusTech 2021 Global Conferences, IEEE Online Forum on Climate Change Technologies (OFCCT).

Email:

Dalong Li of Torc Robotics

Biography:

Dr. Dalong Li, PhD, serves as the Head of AI Data, Perception, and Auto‑Labeling at Torc Robotics, where he leads global teams advancing data‑centric AI, automated curation, and large‑scale ground‑truth generation for autonomous driving. His expertise spans 2D and 3D perception, sensor fusion, HD‑map creation, and cloud‑native machine‑learning pipelines that support safety‑critical AV development. He has driven major innovations in self‑supervised learning, adversarial robustness, and simulation‑based deep learning, shaping next‑generation perception systems. Before joining Torc, he led machine‑learning teams across North America, APAC, and EMEA at Stellantis, delivering production‑grade AD/ADAS capabilities. Earlier in his career at FCA, he spearheaded AI programs in active learning, lidar perception, and functional safety for automated‑driving systems. Dr. Li holds more than ten patents in autonomous‑driving technologies and continues to influence the field through his technical leadership. He is a frequent speaker at AV20, AutoSens, and other industry forums, sharing insights on perception, data‑centric AI, and scalable annotation pipelines. His career also includes impactful roles at Continental, Motorola, and Hewlett Packard Enterprise, where he contributed to foundational work in embedded intelligence and large‑scale data systems. Widely recognized for building high‑performance AI teams, he consistently delivers solutions that bridge cutting‑edge research with real‑world deployment.

John Paul Kepros

Biography:

Dr. John Paul Kepros, MD, MBA, CPE, is a physician‑engineer whose career bridges clinical medicine, systems engineering, and AI‑driven healthcare transformation. He trained at the University of Iowa’s Carver College of Medicine and has more than two decades of clinical experience, including trauma surgery and research leadership. His work focuses on improving healthcare quality through high‑reliability systems thinking and advanced analytics. As a Certified Physician Executive, he advises organizations on integrating AI into clinical operations and quality improvement. He is known for uniting engineering precision with medical judgment to redesign care delivery. Dr. Kepros helps hospital leaders and technology teams navigate digital transformation in high‑stakes environments. His expertise spans clinical variability reduction, patient‑safety engineering, and organizational leadership. He is a sought‑after speaker on AI strategy, healthcare quality, and the human‑technology interface. His writing explores the future of medicine, physician leadership, and the cultural shifts required for innovation. Based in East Lansing, Michigan, he continues to shape the next era of intelligent, resilient healthcare systems.

Sunil Chathaveeti

CEO Mintmesh Corporation

Biography:

Sunil Chathaveetil is an accomplished technology and business leader with deep roots in Michigan’s automotive and mobility ecosystem. With more than two decades of experience, he has built a strong reputation for guiding organizations through digital transformation, fostering strategic partnerships, and championing innovation across the automotive value chain. His work reflects a rare blend of technical insight and business acumen, enabling teams and enterprises to navigate complex technological shifts with clarity and purpose. Beyond his leadership roles, Sunil is a recognized voice in the community, known for articulating why the automotive industry remains one of the most powerful launchpads for innovation. With a network of 5,000+ followers and 500+ professional connections, he actively contributes to Michigan’s engineering and technology landscape through mentorship, thought leadership, and industry engagement. His career continues to amplify the region’s legacy as a global hub for mobility and engineering excellence.