Address KAUST

Peter Wonka
CEMSE
Building 1, office 2108
4700 King Abdullah University of Science and Technology
Thuwal 23955-6900
Kingdom of Saudi Arabia

Research

Research Areas:

• Deep Learning for Visual Computing
• Computer Vision
• Machine Learning
• Computer Graphics
• Occasionaly: Visualization, Remote Sensing, Image Processing, Data Mining

Current keywords: deep learning, machine learning, machine learning for visual computing, generative modeling, 3D generative modeling, generative diffusion models, generative adverserial networks, unsupervised learning, 3D computer vision, 3D reconstruction, 3D vision and language, neural fields, inverse problems, depth prediction, laser scanning, layout synthesis, shape modeling, sampling, image and video editing using generative models

Additional keywords for current or past research: urban planning, computational design, procedural modeling, interactive editing, geometry processing, architectural geometry, geo-spatial visualization, surface sampling, surface remeshing, image analysis, texture synthesis, texture analysis, lighting design, machine learning for graphics, applications, optimization, deep learning

Keywords - example tools used in previous research: machine learning, deep learning, more deep learning, diffusion, autoregressive models, generative adverserial networks, graphical models, gaussian process regression, optimization, integer programming, mixed integer programming, ADMM, quadratic programing, heuristic optimization, quadratic assignment, functional maps, graph-cuts

Current Group: Students, Post-docs, and Research Scientists

• Ruichen Zheng (previous school: Imperial College, UK)
• Jianqi Chen (previous school: Beihang University, China)
• Diego Eustachio Farchione (previous school: University of Pisa, Italy)
• Fedor Rodionov (previous school: State University of Nizhni Novgorod, Russia)
• Wenqing Cui (previous school: Harbin Institute of Technology, China)
• Zhenyu Li (previous school: Harbin Institute of Technology, China)
• Jian Shi (previous school: The University of Leicester, UK)
• Qian Wang (previous school: Wuhan University, China)
• Aleksandar Cvejic (previous school: Novi Sad University, Serbia)
• Ahmed Abdelreheem (previous school: Cairo University, Egypt)

• Yunlu Chen, Post-doc (PhD: University of Amsterdam, Netherlands )
• Xiangjun Tang, Post-doc (PhD: Zhejiang University, China )
• Biao Zhang, Post-doc (PhD: KAUST)

• Ramzi Idoughi, Research Scientist (PhD: University of Toulouse, France )
• Michael Birsak, Research Scientist (PhD: TU Vienna, Austria)

The university (country) listed in brackets is where the group member came from before joining KAUST. This list is just to give you an idea on the current group decomposition.

KAUST Alumni: Students, Post-docs, and Research Scientists

• Shariq Bhat, PhD 2024, (previous school: National Institute of Technology, Srinagar, India), next employment: research scientist at Adobe[thesis]
• Rameen Abdal, PhD 2023, (previous school: National Institute of Technology, Srinagar, India), next employment: post-doc at Stanford [thesis]
• Biao Zhang, PhD 2023, (previous school: Xi'an Jiaotong University, China), next employment: post-doc at KAUST [thesis]
• Ivan Skorokhodov, PhD 2023, (previous school: Yandex School of Data Analysis, Russia), next employment: research scientist at Snap [thesis]
• Peihao Zhu, PhD 2023, (previous school: Chinese Academy of Science, China), next employment: research scientist at Bytedance [thesis]
• Anna Fruehstueck PhD 2023, (previous school: Technical University of Vienna, Austria), next employment: research scientist at Adobe, [thesis]
• Wamiq Reyaz Para, PhD 2023, (previous school: National Institute of Technology, Srinagar, India), next employment: [thesis]
• Jing Ren, PhD 2021, (previous school: Oxford, UK), next employment: post-doc at ETH Zuerich, [thesis]
• Yazeed AlHarbi, PhD 2021, (previous school: Purdue, USA), next employment: research scientist at SDAIA, KSA, [thesis]
• Lama Affara, PhD 2018, (previous school: AUB, Lebanon), next employment: Assistant Prof. at Beirut Arab University, [thesis]

• Yanze Zhu (previous school: Xi'an Jiaotong University, China)
• Matvey Morozov (previous school: Moskov Institute of Physics and Technology)
• Dinmukhamed Sagynbay, MS 2023, (previous school: Nazarbayev University)
• Jichen Lu, MS 2023, next employment: PhD at KAUST
• Ali Al Nasser, MS 2023, next employment: PhD at KAUST
• Tian Yu, MS, (previous school: Harbin Institute of Technology, China), next emploment: PhD at KAUST

• Abdelrahman Eldesokey, Post-doc (PhD: Linkoeping, Sweden), next employment: KAUST
• Abdalla Ahmed, Post-doc (PhD: Konstanz, Germany)
• Ibraheem AlHashim, Post-doc, (PhD: Simon Frasier University, Canada), next employment: research scientist at SDAIA, KSA
• Yiqun Wang, Post-doc, (PhD: Chinese Academy of Sciences), next employment: Associate Prof. at Chongqing University, China
• Dongming Yan, research scientist, current employment: Full Prof. at Chinese Academy of Sciences, China
• Liangliang Nan, research scientist, current employment: Associate Prof. at TU Delft, Netherlands
• Yipeng Qin, post-doc, next employment: lecturer at Cardiff University, UK

The university (country) listed in brackets is where the group member came from before joining KAUST. This list is just to give you an idea on the current group decomposition.

Note for Students and Post-docs interested in joining my group

Goal of the research group The main goal of the research group is for students, post-docs, research scientists, and faculty to collaborate on and publish impactful research. Since most positions in the group are temporary, another important goal is that group members find a good job after leaving the group in academia or industry. Therefore, we would like to give students and post-docs the opportunity to focus on publishing impactful first author publications and students to seek out suitable research focused internships in industry.

What background is a good match for my research? I look at multiple criteria when evaluating a student, mainly: reputation of the undergraduate (graduate) school, GPA, the quantitative GRE score, mathematics skills (grades in mathematics courses), and programming skills (including the design of systems and algorithms, design of experiments, debugging, ...). The students that I recruit are typically either very good in mathematics, programming, or both. A nice bonus is the knowledge of visual computing, research experience, or publications. I am looking for students who are interested in the areas of deep learning, machine learning, computer vision, or computer graphics.

Publications: currently, for my research I typically target publications in the following venues. Mainly computer vision, computer graphics, and machine leanring; occasionally visualization and remote sensing. The publication venues are not an exclusive list.

• computer vision (ECCV, ICCV, CVPR, IEEE PAMI)
• machine learning (NeurIPS, ICLR)
• computer graphics (ACM Siggraph, ACM Siggraph Asia, ACM TOG, IEEE TVCG)
• visualization (IEEE Visualization, IEEE TVCG)
• remote sensing (IEEE TGRS).

How to contact me? If you are interested to join as a student please send me an email including a CV and a recent transcript.

Note for post-docs: If you are interested to join as a post-doc, please send a CV including your GPA and publication list. Almost all post-docs I previously hired had publications in some of the venues highlighted above or very related publication venues.

• basic machine learning, e.g. coursera (Machine Learning, Andrew Ng)
• deep learning, e.g. coursera (Deep Learning Specialization), udactity nanodegree, fastai, or Stanford
• optimization, e.g. Boyd's convex optimization courses
• linear algebra, e.g. Gilbert Strang on youtube, Boyd's linear dynamical systems