Bio and Education

     

Short Bio: Mohamed Elhoseiny is an assistant professor of Computer Science at KAUST. Previously, he was a visiting Faculty at Stanford Computer Science department (2019-2020), Visiting Faculty at Baidu Research (2019), Postdoc researcher at Facebook AI Research (2016-2019). Dr. Elhoseiny did his Ph.D. in 2016 at Rutgers University where also he spent time at SRI International in 2014 ( best intern award ) 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 to understand and generate novel art and fashion. He received an NSF Fellowship in 2014 and the Doctoral Consortium award at CVPR’16. 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, and HBO Silicon Valley. At the first AI Artathon 2020 (part of the Global AI summit), Dr. Elhoseiny served with Luba Elliot and Gene Kogan as a keynote speaker, panelist, and a judge to help qualify 20 out of 50 participating teams to the next stage, the 50 teams were formed from 300 artists and AI engineers who were selected to participate from 2000 applicants. This is 6% qualifying/pre-selection rate. He serve as Area Chair at CVPR21 and ICCV21 and organized CLVL workshops at ICCV’15, ICCV’17, and ICCV’19.



Old Long Bio: Dr. Mohamed Elhoseiny is Assistant Professor of Computer Science at the Visual Computing Center at KAUST (King Abdullah University of Science and Technology) and an AI Research consultant at Baidu Research. 
His primary research interests are in computer vision, the intersection between natural language and vision and computational creativity.

Since Dec 2016, Dr. Elhoseiny has productively collaborated with several researchers at Facebook AI Research including Marcus Rohrbach, Yann LeCun, Devi Parikh, Dhruv Batra, Manohar Paluri, Marc'Aurelio Ranzato, and Camille Couprie. He has also fruitfully teamed up with academic institutions including KULeuven (with Rahaf Aljundi and Tinne Tuytelaars), UC Berkeley (with Sayna Ebrahimi and Trevor Darrell), the University of Oxford (with Arslan Chaudry and Philip Torr), and the Technical University of Munich (with Shadi AlBarqouni and Nassir Navab). Dr. Elhoseiny received his Ph.D. degree from Rutgers University, New Brunswick, in October 2016 under Prof. Ahmed Elgammal. 

His work has been widely recognized. In 2018, he received the best paper award for his work on creative fashion generation at ECCV workshop from Tamara Berg of UNC chapel hill and sponsored by IBM Research and JD AI Research. The work got also featured at the New Scientist Magazine and he co-presented it the Facebook F8 annual conference with Camille Couprie. His earlier work on creative art generation was featured by the New Scientist magazine and MIT technology review in 2017, HBO Silicon Valley TV Series ( season 5 episode 3) in 2018. His Creative AI artwork was featured/presented at the best of AI meeting 2017 at Disney (6000+ audience), Facebook's booth at NeurIPS 2017, and the official FAIR video in June 2018. His work on life-long learning was covered at the MIT technology review in 2018. In Nov 2018 and based on his 5-year work on zero-shot learning, Dr. Elhoseiny made significant participation in the United Nations Biodiversity conference (~10,000 audience from >192 countries and tens of important organization) on how AI may benefit biodiversity which reflects in both disease management and climate change. Dr. Elhoseiny received the Doctoral Consortium award at CVPR 2016 and an NSF Fellowship for his Write-a-Classifier project in 2014.


Education

  • Postdoc Researcher, Computer Vision, Facebook AI Research (FAIR), Dec 2016-Jan 2019,                                                                                                                                                                                                                                         11 papers, best paper award in ECCV18 workshop,  Facebook F8 presentation, United Nation significant participation, major media coverage of four different projects (e.g., MIT Tech review, New Scientist, Silicon Valley TV Series).
  • PhD in Computer Science, Rutgers University  Supervisor: Prof. Ahmed Elgammal – October 2016– GPA 4.00                                                                                                                                                                                                          Thesis: My      research work is on Computer Vision, Machine Learning, Multimedia  and NLP.
  • M.Sc in Computer Science, Rutgers  University  Supervisor: Prof. Ahmed Egammal – 2014 – courses GPA 4.                                                                                                                                                                                    MSc                    report, "Write a Classifier: Zero Shot Learning Using Purely Textual Descriptions", published at ICCV13
  • M.Sc in Computer Systems, Ain Shams University (ASU)  Supervisor: Prof. Taymour Nazmy – 2010 – courses GPA 3.55.                                                                                                                                                                                         Thesis: “High  Performance Activity Monitoring for Scenes including Multiple Agents”, research GPA 4.0
  • BSc in Computer SystemsAin Shams University (ASU)  Supervisor: Prof. Said ElGhoneimy – 2006 – GPA 3.96.



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