Join us for “Robust, Trustworthy, and Efficient Multimodal Learning” a keynote presentation by Dr. Ngan Le, College of Engineering – Electrical Engineering & Computer Science, MizzouForward faculty candidate.  Dr. Le will present on her research for approximately 40-minutes with a 20-minute question and answer session to follow.

Dr. Le is an Assistant Professor and Director of the Artificial Intelligence & Computer Vision (AICV) Lab in the Department of Electrical Engineering & Computer Science at the University of Arkansas. She previously held a Postdoctoral position at Carnegie Mellon University (CMU), where she also earned her Ph.D. and Master’s degrees in electrical & computer engineering. Her research focuses on robust, trustworthy, and efficient multimodal learning, addressing challenges such as trusted decision-making, imperfect data, and real-time applications. She has contributed to the fields of Machine Learning, Computer Vision, Robotics, Healthcare, Remote Sensing and holding six patents and co-authoring over 130 papers in top-tier conferences and journals. Dr. Le has served as an Associate Editor for Machine Learning with Applications and has taken on leadership roles in major conferences, including Asilomar, MICAD, ACCV, and IJCAI. She has also organized workshops and tutorials at prestigious venues like MICCAI and ACCV and has been actively involved in initiatives supporting Women in Computer Vision and Women in MICCAI.

Dr. Le’s research in robust, trustworthy, and efficient multimodal learning significantly advances the fields of Machine Learning, Computer Vision, Robotics, Healthcare, Remote Sensing by addressing critical real-world challenges. Her work enhances the reliability and accountability of AI systems by tackling imperfect data, enhancing interpretability, and improving the efficiency across multiple modalities, including image, video, point cloud, volumetric data, time series, and remote sensing. With applications spanning healthcare, renewable energy, precision agriculture, autonomous systems, and beyond, her contributions not only push the boundaries of AI capabilities but also foster user trust and responsible technology adoption. Through her extensive publication record and multiple patents, Dr. Le continues to shape the future of multimodal AI, ensuring its adaptability, scalability, and real-world applicability.

You can access Dr. Le’s CV via OneDrive here:    NganLe_CV_Feb25.pdf     (University log in required to access).

After the keynote, please provide candidate feedback with our brief survey.