Speakers (To be updated)

Rogerio Feris is a principal scientist and manager at the MIT-IBM Watson AI lab. He is generally interested in teaching machines to see, listen, and read, with little or no supervision, like humans do. His work has not only been published in top AI conferences, but has also been integrated into multiple products, and covered by media outlets such as the New York Times, ABC News, and CBS 60 minutes.

Dr. Kozlov is a Data scientist of Intel. He worked on applications of machine learning to extreme weather forecasting for aviation industry. His current interests are personalisation and natural language processing in finance industry. On the scientific front he have led and contributed to 26 projects in atomic and plasma physics, biochemistry, X-ray imaging, statistics and data analysis.

Jiaheng Liu received the BE degree in Software Engineering from Beihang University, Beijing, China, in 2019. He is currently pursuing the Ph.D. degree from the School of Computer Science and Engineering, Beihang University, Beijing, China. His current research interests include computer vision and pattern recognition.

Dr. Xiangyu Yue had research experiences at Google Research, Google [X] Robotics, Baidu AI Lab, Tencent AI Lab, etc. His research broadly spans across machine learning, transfer learning, label-efficient learning, computer vision, with applications in autonomous driving, robotics, medical imaging, etc. He received the prestigious Lotfi A. Zadeh Prize awarding outstanding Ph.D. graduates in EECS department at UC Berkeley. 

Piotr Koniusz is a senior research scientist in Machine Learning Research Group at Data61/CSIRO (former NICTA) and a senior honorary lecturer at Australian National University (ANU). His interests include graph neural networks, visual category/action recognition, zero-, one- and few shot learning, contrastive learning, domain adaptation, RKHS, deep learning.

Nian Liu is currently a research scientist with the Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE. His research interests include computer vision-related topics and deep learning, especially saliency detection, few-shot learning, and autonomous driving (3D detection, map segmentation, etc., with multi-view camera and lidar data)

Dongjin Song have broad research interests in machine learning, data mining, deep learning, federated learning, and related applications for time series representation, similarity search, prediction/forecasting, and anomaly detection. He is also interested in graph representation learning with applications to link prediction, node classification, recommendation, dynamic systems, etc. 

Daquan Zhou's research interests include architecture design, compression optimization and automatic search of deep learning neural networks. He has published several papers at ICLR, ICML, ICCV, CVPR, NeruIPS and other computer vision and machine learning top conferences. He was involved in the design of Singapore's first commercial satellite at the National Laboratory of Defense Science and Technology.

Ziwei Liu's research revolves around computer vision/graphics, machine learning, and robotics. He has published over 50 papers on top-tier conferences and journals in relevant fields, including CVPR, ICCV, T-PAMI, .etc. He is the recipient of Microsoft Young Fellowship, ICCV Young Researcher Award. He is also the lead contributor of several renowned computer vision benchmarks and softwares. 

Dr. Wang is an Associate Professor and Faculty Fellow in the Department of Electrical & Computer Engineering at Northeastern University. His research interests include Real-time and energy-efficient deep learning and artificial intelligence systems, model compression of deep neural networks, neuromorphic computing and non-von Neumann computing paradigms.