
Rising Stars in AI Symposium 2023
Following on the success of the first Annual 'Rising Stars in AI' Symposium 2022, the AI initiative at KAUST (the university with the highest impact per faculty, located on the Red Sea) is hosting its second iteration of the Symposium between 19th and 21st Feb, 2023. This is event geared towards young researchers (including PhD students, PostDocs, and early career faculty) who have recently published significant works at leading AI venues. It is a great opportunity for attendees to discuss and exchange exciting AI research ideas. The Symposium organizing committee will select a number of speakers based on their research profile. Selected speakers will have the opportunity to give presentations about their work recently accepted at major AI conferences such as NeurIPS, ICML, ICLR, CVPR, ECCV, ICCV, EMNLP, ACL, among others.
Speakers are encouraged to start with an introduction aimed at non-AI experts and follow up with in-depth technical details. There will also be plenty of time for discussions and social activities.
The symposium will be held at KAUST in Building 19, Hall 2, on February 19-21 with (limited) in-person attendance, and those selected for the symposium as speakers will have their flights and hotel expenses covered.
The applications as speakers are now closed. To attend the symposium (in-person only), please fill out this form.
Agenda
Arabian Standard Time (UTC+3)
Day 1 - Sunday, February 19th, 2023
Time | Speaker | Presentation |
---|---|---|
08:15 - 09:00 | Breakfast | |
09:00 - 09:05 | Prof. Larry Carin (KAUST) | Opening Remarks by KAUST Provost |
09:05 - 09:20 | Prof. Bernard Ghanem (KAUST) | Presentation of the AI Initiative |
09:20 – 09:40 | Prof. Jürgen Schmidhuber (KAUST) | Overview of Prof. Jürgen Schmidhuber's Research Laboratory |
09:40 – 10:00 | Jingfeng Zhang (RIKEN, Japan) | Adversarial Learning: Foundations and Applications |
10:00 – 10:20 | Noor Sajid (University College London) | Deep active inference |
10:20 – 11:00 | Coffee Networking Break | |
11:00 – 11:20 | Arnav Chavan (Indian Institute of Technology & MBZUAI) | Efficient Neural Architecture Design strategies for vision-based deep learning systems. |
11:20 – 11:40 | Karttikeya Mangalam (UC, Berkeley) | Towards Long-Term Video Understanding with Vision Transformers |
11:40 – 12:00 | Soufiane Hayou (NUS) | Principled scaling of deep residual neural networks |
12:00 – 13:20 | Lunch Break | |
13:20 – 13:40 | Haotong Qin (ETH Zürich CVL & Beihang University) | Network Binarization toward Hardware-friendly Deep Learning |
13:40 – 14:00 | Jakub Grudzien (UC, Berkeley) | Mirror Learning: Towards A General Solution To Policy Optimization |
14:00 – 14:20 | Sarit Khirirat (MBZUAI) | A flexible framework for communication-efficient machine learning |
14:20 – 15:00 | Coffee Networking Break | |
15:00 – 15:20 | Dengping Fan (ETH) | Accurate Dense Prediction: Algorithms and Applications |
15:20 – 15:40 | Oguzhan Fatih Kar (EPFL) | 3D Common Corruptions and Data Augmentation |
15:40 – 16:00 | Walid Magdy (University of Edinburgh) | A brief history of AI in NLP, the Arabic NLP story” |
16:00 – 16:40 | Spotlight Presentation | |
16:40 – 17:20 | Poster Session | |
19:00 – 22:00 | Gala Dinner (invitation only) |
Day 2 - Monday, February 20th, 2023
Time | Speaker | Presentation |
---|---|---|
08:15 - 09:00 | Breakfast | |
09:00 - 09:20 | Prof. Bernard Ghanem (KAUST) | Overview of Prof. Bernard Ghanem's Research Laboratory |
09:20 – 09:40 | Jiancheng Yang (EPFL) | Neural 3D Representation in Health Intelligence |
09:40 – 10:00 | Puneet Mathur (University of Maryland) | Visual-Linguistic Document Structure Understanding and Manipulation |
10:00 – 10:20 | Ilyas Fatkhullin (ETH) | Stochastic Policy Gradient Methods: Improved Global Convergence and Sample Complexity |
10:20 – 11:00 | Coffee Networking Break | |
11:00 – 11:20 | Amartya Sanyal (ETH & Max Planck Institute) | Impact of Limited and Noisy Data on Trustworthy Machine Learning |
11:20 – 11:40 | Wenxuan Wu (Oregon State University) | PointConvFormer: Revenge of the Point-based Convolution |
11:40 – 12:00 | Gautam Kamath (University of Waterloo) | Differentially Private Fine-tuning of Language Models |
12:00 – 13:20 | Lunch Break | |
13:20 – 13:40 | Dimitris Spathis (Nokia Bell Labs and University of Cambridge) | Self-Supervised Learning for Health Signals |
13:40 – 14:00 | Giuseppe Loianno (New York University) | Learning Models and Representations for Super Autonomous Robots |
14:00 – 14:20 | Hrayr Harutyunyan (University of Southern California) | On Information Captured by Neural Networks: Connections with Memorization and Generalization |
14:20 – 14:40 | Coffee Networking Break | |
14:40 – 15:20 | Spotlight Presentations | |
15:20 – 16:00 | Poster Session |
Day 3 - Tuesday, February 21th, 2023
Time | Speaker | Presentation |
---|---|---|
08:15 - 09:20 | Breakfast | |
09:20 – 09:40 | Phillip Lippe (University of Amsterdam) | Learning Causal Variables from Temporal Observations |
09:40 – 10:00 | Tao Yu (NUS and USTC) | Mask-based Latent Reconstruction for Reinforcement Learning |
10:00 – 10:20 | Fanghui Liu (EPFL) | Robustness in Deep Learning: The Good (width), the Bad (depth), and the Ugly (initialization) |
10:20 – 11:00 | Coffee Networking Break | |
11:00 – 11:20 | Hazel Doughty (University of Amsterdam) | How Do You Do It? Fine-Grained Action Understanding with Pseudo-Adverbs |
11:20 – 11:40 | Mirco Mutti (University of Bologna) | Convex Reinforcement Learning |
11:40 – 12:00 | Pascal Mettes (University of Amsterdam) | Hyperbolic Visual Understanding |
12:00 – 13:20 | Lunch Break | |
13:20 – 13:40 | Usman Naseem (University of Sydney) | Figurative Language Modelling for Health Mention Classification on Social Media |
13:40 – 14:00 | Tan Wang (Nanyang Technological University) | Equivariant Similarity for Vision-Language Foundation Models |
14:00 – 14:20 | Yali Du (King's College London) | Cooperative Multi-Agent Learning in a Complex World: Challenges and Solutions |
14:20 – 15:00 | Coffee Networking Break | |
15:00 – 15:40 | Spotlight Presentation | |
15:40 – 16:20 | Poster Session | |
16:20 – 17:00 | Panel Discussion |