Prof. Sanjay Sarma is MIT’s Vice President for Open Learning and the Fred Fort Flowers and Daniel Fort Flowers Professor of Mechanical Engineering. Dr. Sarma founded the Auto-ID Center at MIT (now MIT Auto-ID Labs) and developed many of the key technologies behind the EPC suite of RFID standards now used worldwide. He was also the the founder and CTO of OATSystems, which was acquired by Checkpoint Systems (NYSE: CKP) in 2008. He sits on the boards of GS1, EPCglobal and several startup companies. Dr. Sarma received his Bachelors from the Indian Institute of Technology, his Masters from Carnegie Mellon University and his PhD from the University of California at Berkeley. In between degrees, Sarma worked at Schlumberger Oilfield Services in Aberdeen, UK, and at the Lawrence Berkeley Laboratories in Berkeley, California. He has authored over 50 academic papers in computational geometry, sensing, RFID, automation and CAD, and is the recipient of numerous awards for teaching and research including the MacVicar Fellowship, the Business Week eBiz
Dr. Rahul Bhattacharyya is a Research Scientist at the MIT Auto-ID Laboratory. He obtained a Bachelors and Masters Integrated Dual Degree in Civil Engineering from the Indian Institute of Technology Bombay in 2006 and a Ph.D. in Systems Engineering from the Massachusetts Institute of Technology in 2012. His research interests broadly encompass the development and integration of technologies that form the framework for the Internet of Things. He is particularly interested in low-cost, pervasive wireless sensor design using smart materials and novel antenna designs and predictive analytics for fault detection using machine-learning techniques. Rahul has served various roles on the organizing committee of the IEEE International Conference on RFID 2010-15 and was technical program co-chair of the 4th International Conference on the Internet of Things. He currently holds membership of the IEEE and the International Society for Structural Health Monitoring of Intelligent Infrastructure.
Dr. Stephen Ho is a Research Scientist in the MIT Auto-ID Laboratory. His research interests center around the application of information towards improving systems, processes, and manufacturing. His Ph.D. research evaluated the impact of rich RFID information on warehouse operations and the opportunities for increased efficiency that stem from additional information. His current research focuses on transportation efficiency stemming from automated systems and collaborative opportunities. Stephen obtained his Bachelor of Science in Mechanical Engineering in 1996 from Cornell University and his Master of Science (1999) and Doctor of Philosophy (2004) from the Massachusetts Institute of Technology in Mechanical Engineering.
Dr. Rich Fletcher leads a student team within Professor Sanjay Sarma’s AutoID Lab that applies machine learning algorithms, phones, and other mobile technologies to global health as well as mental health. Fletcher has been working in global health at MIT for over 20 years, with academic appointments at Massachusetts General Hospital and Harvard Medical School.
Dr. Alexandre Urpi is a postdoctoral associate at the MIT Auto-ID lab, where he specializes in human-computer interaction, 3D computer vision, and augmented reality. His research focuses on capturing and transferring human expertise through hybrid brain–computer and gaze-based interfaces. During his PhD at the lab, supported by “La Caixa” Fellowship, Alex developed systems that use eye-tracking and EEG signals to uncover tacit knowledge—insights we possess but often cannot verbalize—and demonstrated their potential to enhance human training, feedback, and AI models. His work bridges cognitive science and sensing technologies across a wide range of applications, including AI-augmented AR training tools, surgical augmented reality systems, wearable biosignal monitoring, and brain-controlled virtual environments. He has also identified critical security vulnerabilities in brain–computer interface systems, highlighting the need for more robust safeguards in neurotechnology. With a multidisciplinary background spanning academia, healthcare, and industry, Alex’s work advances how machines interpret, respond to, and learn from human behavior.
Heyi Li is a PhD student in Mechanical Engineering at the Auto ID Labs, Massachusetts Institute of Technology, Cambridge, MA, USA. She received the B.S. degree in Microelectronics Science and Engineering from the Southern University of Science and Technology (SUSTech), Shenzhen, Guangdong, China in 2021 and M.Sc. degree in Mechanical Engineering from Massachusetts Institute of Technology, Cambridge, MA, USA. She is interested in RFID sensors and machine learning (ML) integration for Internet of things (IoT). In her free time, Heyi enjoys dancing, figure skating and badminton.
Dr. Fátima Villa-Gonzalez is a graduate student at Tecnun Engineering School, University of Navarra, Spain, currently doing research at the Auto-ID La, Massachusetts Institute of Technology, Cambridge MA, USA. She joined the MIT Auto-ID Lab in 2019 as a visiting student to complete her master’s thesis. She received a B.S. degree in Telecommunications Systems Engineering and a M.Sc. degree in Telecommunications Engineering from Tecnun Engineering School in 2017 and 2019 respectively. Her research interests include microwave, antennas, chipped and chipless RFID sensors, electronic circuits and digital signal processing.