Bio and Education



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.

Short 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 at Silicon Valley AI Lab (SVAIL). He received his PhD from Rutgers university under Prof. Ahmed Elgammal in October 2016 then spent more than two years at Facebook AI Research(FAIR) until January 2019 as a Postdoc Researcher. His primary research interests are in computer vision and especially about learning about the unseen or the least unseen by recognition (e.g., zero-shot learning) or by generation (creative art and fashion generation). Under the umbrella of how AI may benefit biodiversity, Dr. Elhoseiny's 6-years long development of the zero-shot task on major vision conferences was featured in the United Nations biodiversity conference in November 2018 (~10,000 audience from >192 countries). His creative AI research projects were recognized at the ECCV18 workshop on Fashion and Art with the best paper award, media coverage at the New Scientist Magazine and MIT Tech review (2017, 2018), 20 min speech at the Facebook F8 conference (2018), and coverage at HBO Silicon Valley TV Series (2018), and the official FAIR video (2018).

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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