She is an Associate Professor at Yong Loo Lin School of Medicine, National University of Singapore. She will give a talk on the human neural bases of visual processing functions through the lens of brain encoding and decoding, which is part of her research interest. She is also interested in the associated vulnerability patterns in aging and neuropsychiatric disorders using psychophysical techniques and machine learning approaches. She is currently a Council Member and a previous Program Committee member of the Organization of Human Brain Mapping. She serves on the advisory board of Cell Reports Medicine and as an editor of multiple journals including Human Brain Mapping, NeuroImage, and Communications Biology.  https://neuroimaginglab.org/members.html

He is an Assistant Professor in the Osaka University. His research interest is the intersection of Computational Neuroscience and Artificial Intelligence. During Ph.D., he worked on reliable techniques for predicting diverse individual differences from whole-brain functional connectivity using functional magnetic resonance imaging (fMRI) at ATR Brain Information Communication Research Laboratory. More recently, he is working on understanding a dynamic computation during complex decision making tasks with machine learning technique in the Oxford Centre for Human Brain Activity at the University of Oxford, and Department of Psychology at the University of Tokyo.

She is a tenure-track faculty at the Max Planck Institute for Software Systems. Her research sits at the nexus of Machine Learning, Natural Language Processing, and Neuroscience, aiming to create computational models that elucidate how the brain processes language, which in turn can enhance natural language processing systems. She spearheads the BrAIN (Bridging AI and Neuroscience) group at the institute and is keen on recruiting talented postdoctoral, PhD, and research interns. Before her time at MPI-SWS, she was a C.V. Starr Fellow at the Princeton Neuroscience Institute, collaborating with Ken Norman and Uri Hasson on understanding the involvement of episodic memory in language comprehension. She obtained her Ph.D. from Carnegie Mellon University, interlinking Machine Learning and Neural Computation. Here, she was mentored by Leila Wehbe and Tom Mitchell for her thesis titled "Bridging Language in Machines with Language in the Brain." Preceding her doctoral journey, she earned a B.S. in both Computer Science and Cognitive Science from Yale University.

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