The Intersection of Artificial Intelligence and Human Intelligence (IAIHI)

Keynote Speakers

 

Dr. Islem Rekik
Director, BASIRA Lab, Imperial College London, UK
Bio: Islem Rekik is the Director of the Brain And SIgnal Research and Analysis (BASIRA) laboratory (http://basira-lab.com/) and an Associate Professor at Imperial College London (Innovation Hub I-X). Together with BASIRA members, she conducted more than 90 cutting-edge research projects cross-pollinating AI and healthcare —with a sharp focus on brain imaging and neuroscience. She is also a co/chair/organizer of more than 20 international first-class conferences/workshops/competitions (e.g., Affordable AI 2021-22, Predictive AI 2018-2023, Machine Learning in Medical Imaging 2021-23, WILL competition 2021-22). Dr Rekik has been awarded prestigious international research fellowships including the EU Marie-Curie Fellowship in 2019 and the TUBITAK 2232 for Outstanding Experienced Researchers during 2020-2022. In addition to her 130+ high-impact publications, she is a strong advocate of equity, inclusiveness and diversity in research. She is the former president of the Women in MICCAI (WiM), the co-founder of the international RISE Network to Reinforce Inclusiveness & diverSity and Empower minority researchers in Low-Middle Income Countries (LMIC) and a committee member of the AFRICAI network. She is in the organizing committee of MICCAI 2022 (Singapore), 2023 (Vancouver) and 2024 (Marrakesh).

 

Dr. Xiaofu He
Assistant Professor, Columbia University, USA
Bio: Dr. Xiaofu He is an Assistant Professor of Clinical Neurobiology at Columbia University Irving Medical Center. He has a broad background in computer science, machine learning, neuroscience, and brain imaging (http://www.columbia.edu/~xh2170/). Dr. He received his PhD in pattern recognition and intelligent systems from Shanghai Jiao Tong University. Before pursuing his postdoctoral training, Dr. He was an Assistant Professor in the Computer Science Department at East China Normal University. During his postdoctoral training at Georgia Health Sciences University, Dr. He developed expertise in computational modeling and visual electrophysiology. Later at Columbia University, Dr. He extended his research to the field of brain imaging including structural MRI, functional MRI (fMRI), and diffusion tensor imaging (DTI). His research interests include developing brain imaging data analysis tools, exploring new diagnosis and prediction methods using machine learning including deep learning, and investigating potential treatments using real-time fMRI/ /EEG neurofeedback, which he is currently applying to psychiatric disorders.

 

Dr. Xiang Li
Assistant Professor, Massachusetts General Hospital and Harvard Medical School, USA
Bio: Dr. Xiang Li is an Assistant Professor of Radiology at the Massachusetts General Hospital and Harvard Medical School. He received his bachelor’s degree from the School of Electronic Information and Electrical Engineering at Shanghai Jiaotong University and his Ph.D. degree from the Department of Computer Science at the University of Georgia, advised by Distinguished Research Professor Tianming Liu. After graduation, Dr. Xiang Li joined Massachusetts General Hospital and Harvard Medical School as Research Fellow, with mentorship from Dr. James Thrall, Chairman Emeritus of MGH Department of Radiology, along with Dr. Quanzheng Li, the director of MGH/HMS Center for Advanced Medical Computing and Analysis. Dr. Xiang Li's research focus includes developing artificial intelligence solutions for analyzing healthcare data, especially fusion across imaging and non-imaging data, and developing medical informatics systems for smart data management and AI deployment in the clinical workflow. He is the founding chair of the International Workshop on Multiscale Multimodal Medical Imaging. He has received multiple funding support from NIH for his research on multi-modal imaging fusion and clinical decision support.