Mohamed Elhoseiny is an Associate Professor of Computer Science at KAUST, and is a senior member honoree of AAAI and IEEE. Previously, he was a visiting Faculty at Stanford Computer Science Department (Oct 2019-March 2020), a Visiting Faculty at Baidu Research (March-October 2019), and a Postdoc researcher at Facebook AI Research (Nov 2016- Jan 2019). Dr. Elhoseiny earned his Ph.D. in 2016 from 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 and 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, the Best Paper award at ECCVW’18 on Fashion and Design,and was selected as an MIT 35 under 35 semi-finalist in 2020. 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 CV/AI conferences, including CVPR21, ICCV21, IJCAI22, ECCV22, ICLR23, CVPR23, ICCV’23, NeurIPS23, ICLR’24, CVPR’24, ECCV’24, SG Asia’24 and has organized Closing the Loop Between Vision and Language workshops at ICCV’15, ICCV’17, ICCV’19, ICCV’21, ICCV’23. In an unplanned participation, he won 🏆 third place at the data+AI summit hackathon at San Francisco held end of may 2024 (200 participants) with a multimodal LLM hack called HomeGPT.