Uploaded June 2023 | Updated September 2026, 1 day ago
Bio: Mohamed Elhoseiny is an assistant professor of Computer Science at KAUST., He has become a senior member of IEEE since Fall 2021 and AAAI since Spring 2022. He is also a member of the international Summit community. Previously, he was a visiting Faculty at Stanford Computer Science department (2019-2020), Visiting Faculty at Baidu Research (2019), and a Postdoc researcher at Facebook AI Research (2016-2019). Dr. Elhoseiny did his Ph.D. in 2016 at Rutgers University, where he was part of the art & AI lab and spent time at SRI International in 2014 and at Adobe Research (2015-2016). His primary research interest is in computer vision and especially in efficient multimodal learning with limited data in zero/few-shot learning and Vision & Language. He is also interested in Affective AI and especially in understanding and generating novel visual content (e.g., art and fashion). He received an NSF Fellowship in 2014, the Doctoral Consortium award at CVPR’16, best paper award at ECCVW’18 on Fashion and Design. His zero-shot learning work was featured at the United Nations, and his creative AI work was featured in MIT Tech Review, New Scientist Magazine, Forbes Science, and HBO Silicon Valley. He has served as an Area Chair at major AI conferences, including CVPR21, ICCV21, IJCAI22, ECCV22, ICLR23, and CVPR23, and organized CLVL workshops at ICCV’15, ICCV’17, ICCV’19, and ICCV’21.
Bio: Mohamed Elhoseiny is an assistant professor of Computer Science at KAUST., He has become a senior member of IEEE since Fall 2021 and AAAI since Spring 2022. He is also a member of the international Summit community. Previously, he was a visiting Faculty at Stanford Computer Science department (2019-2020), Visiting Faculty at Baidu Research (2019), and a Postdoc researcher at Facebook AI Research (2016-2019). Dr. Elhoseiny did his Ph.D. in 2016 at Rutgers University, where he was part of the art & AI lab and spent time at SRI International in 2014 and at Adobe Research (2015-2016). His primary research interest is in computer vision and especially in efficient multimodal learning with limited data in zero/few-shot learning and Vision & Language. He is also interested in Affective AI and especially in understanding and generating novel visual content (e.g., art and fashion). He received an NSF Fellowship in 2014, the Doctoral Consortium award at CVPR’16, best paper award at ECCVW’18 on Fashion and Design. His zero-shot learning work was featured at the United Nations, and his creative AI work was featured in MIT Tech Review, New Scientist Magazine, Forbes Science, and HBO Silicon Valley. He has served as an Area Chair at major AI conferences, including CVPR21, ICCV21, IJCAI22, ECCV22, ICLR23, and CVPR23, and organized CLVL workshops at ICCV’15, ICCV’17, ICCV’19, and ICCV’21.
