Vision-CAIR stands for Computer Vision- "C" Artificial Intelligence Research. "C" is for Content or Creative since we cover in our lab both Vision Content AI research and Vision- Creative AI research. We Vision-CAIR about AI. A few highlights of the research areas and the work we do in our lab.
- Video on United Nations Biodiversity Conference (10,000 Audience with tens of important organizations like UNESCO, WWF, etc)
- Video on Creative Fashion Generation at the high-impact Facebook F8 Conference
- Imagination Inspired Vision (Presentation connecting Zero-Shot Learning and Creative AI; delivered in a variety of important venues).
I am looking for passionate AI researchers to join my group (multiple openings) at the beautiful KAUST campus on the red sea. In particular, I am looking for strong PhD/MS Students and Postdocs (fully funded) interested in working on Vision-CAIR. Interns and short-term visiting researchers are also welcome to reach out. I highly recommend reading Eric Feron's note on Ph.D. characterization.
- You will be part of the Visual Computing Center at KAUST.
- Our school is among the top 10 world-wide in Computer Vision & Graphics according to csranking.org and has world-class experts in different AI areas with whom you will be able and encouraged to interact and collaborate.
- KAUST is recognized as one of the fastest growing research universities in the world [1,2].
- You will have access to world-class compute equipment of more than 1000 GPUs.
- Housing Expenses is completely or at least partially covered till a limit.
- Your financial costs (tuition fees, salary, travel to conferences, equipment) will be covered.
- KAUST community is very diverse with more than 100 nationalities from all over the globe and school is located in the beautiful city of Thuwal on the shores of the red sea.
I look for students with these skills.
- good verbal communication (for daily interaction)
- good written communication (for daily interaction)
- clarity of thought / systematic thinking
- attention to detail
- good professional writing skills (e.g., able to write a reasonable abstract or a paper draft)
- reliability / accountability
- good coding skills
- Subject: [position] [time], where [position] = MS, Ph.D., intern, etc., [time] = Fall 20xx, Spring 20xx, May-December 20xx, etc.
- [Research Experience] 2-3 sentence description (total <100 words) of any past experience in Computer Vision and Machine Learning
- [Research Interests] 2-3 sentence description (total <100 words) of topics in Computer Vision and Machine Learning that you are interested in working on going forward
- [References, required for MS/PhD Applicants]: Please also share a list of 2 references if you are applying for Masters and 3 references if you are applying for a PhD
- [Github and Code ] Link to your GitHub page. Also, links to any of the code repositories that you believe are among the best you have done
- [Sample Outputs of Past projects] Links to sample outputs/pieces of any of your past projects
- [Webpage] Link to your webpage
- [CV] Link to your CV
- [Background] List three highlights from your personal or professional background – past experiences, projects, GPA, past institution, past mentors/advisors – anything you believe I should make sure I don’t miss.
- [Strengths] What do you believe is your biggest strength? What percentile would you place yourself at in this regard amongst your peers?
- [Weaknesses] What do you believe is your biggest weakness? What percentile would you place yourself at in this regard amongst your peers? How have you been working on overcoming them?
Postdoctoral Research Fellow - Computer vision, AI, machine learning
The Computer Vision-Core Artificial Intelligence Research (Vision-CAIR) group of Prof. Mohamed Elhoseiny at the CS Program of the King Abdullah University of Science and Technology (KAUST) is looking for a postdoctoral researcher in the area of computer vision, AI, and machine learning. The Research Vision-CAIR group performs research and develops computational approaches to the following research themes:
(a) learning efficiency, computational creativity (zero, few-shot, and long-tail learning of 2D and 3D vision tasks. This also includes efficient generative models that are capable of generating and understanding unseen art and fashion in 2D and 3D);
(b) continual learning (e.g., alleviating catastrophic forgetting in various learning settings including recognition RL);
(c) vision and language (this overlaps with the former themes as 2D and 3D vision is often integrated with language).
Key requirements include good communication (verbal, writing, etc) and an excellent publication record in high-quality journals and/or conference proceedings such as CVPR, ICCV, NeurIPS, ICML, ICLR, ECCV, Nature, TPAMI, and AAAI. It is an opportunity to develop core algorithmic advances and aim at publishing them at these top venues. More details about the position can be found here.
Next cut-off date: August 15, 2023
Applications will be analyzed as they are received, so early application is advised.
Thank you for your interest!