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Lunch break and poster
Felix Sattler · Khaoula El Mekkaoui · Neta Shoham · Cheng Hong · Florian Hartmann · Boyue Li · Daliang Li · Sebastian Caldas Rivera · Jianyu Wang · Kartikeya Bhardwaj · Tribhuvanesh Orekondy · YAN KANG · Dashan Gao · Mingshu Cong · Xin Yao · Songtao Lu · JIAHUAN LUO · Shicong Cen · Peter Kairouz · Yihan Jiang · Tzu Ming Hsu · Aleksei Triastcyn · Yang Liu · Ahmed Khaled Ragab Bayoumi · Zhicong Liang · Boi Faltings · Seungwhan Moon · Suyi Li · Tao Fan · Tianchi Huang · Chunyan Miao · Hang Qi · Matthew Brown · Lucas Glass · Junpu Wang · Wei Chen · Radu Marculescu · tomer avidor · Xueyang Wu · Mingyi Hong · Ce Ju · John Rush · Ruixiao Zhang · Youchi ZHOU · Françoise Beaufays · Yingxuan Zhu · Lei Xia

Author Information

Felix Sattler (Fraunhofer HHI)
Khaoula El Mekkaoui (Aalto university)
Neta Shoham (Edgify)
Cheng Hong (Alibaba Group)
Florian Hartmann (Google Research)
Boyue Li (Carnegie Mellon University)
Daliang Li (Harvard University)
Sebastian Caldas Rivera (Carnegie Mellon University)
Jianyu Wang (Carnegie Mellon University)
Kartikeya Bhardwaj (Arm Inc.)
Tribhuvanesh Orekondy (Max Planck Institute for Informatics)
YAN KANG (Webank)
Dashan Gao (Hong Kong University of Science and Technology)
Mingshu Cong (The University of Hong Kong)
Xin Yao (Tsinghua University)
Songtao Lu (University of Minnesota Twin Cities)
JIAHUAN LUO (South China University of Technology)
Shicong Cen (Carnegie Mellon University)
Peter Kairouz (Google)

Peter Kairouz is a Google Research Scientist working on decentralized, privacy-preserving, and robust machine learning algorithms. Prior to Google, his research largely focused on building decentralized technologies for anonymous broadcasting over complex networks, understanding the fundamental trade-off between differential privacy and utility of learning algorithms, and leveraging state-of-the-art deep generative models for data-driven privacy and fairness.

Yihan Jiang (University of Washington Seattle)
Tzu Ming Hsu (MIT)
Aleksei Triastcyn (EPFL)
Yang Liu (Tencent)
Ahmed Khaled Ragab Bayoumi (Cairo University)
Zhicong Liang (Hong Kong University of Science and Technology)
Boi Faltings (EPFL)
Seungwhan Moon (Carnegie Mellon University)
Suyi Li (The Hong Kong University of Science and Technology)
Tao Fan (Webank)
Tianchi Huang (Tsinghua University)
Chunyan Miao (Nanyang Technological University)
Hang Qi (Google)
Matthew Brown (Google Research)
Lucas Glass (IQVIA)
Junpu Wang (University of Pennsylvania)

I am a theoretical physicist. Now I am working on various topics in machine learning and deep learning.

Wei Chen (Carnegie Mellon University)
Radu Marculescu (Carnegie Mellon University)
tomer avidor (edgify)
Xueyang Wu (The Hong Kong University of Science and Technology)
Mingyi Hong (University of Minnesota)
Ce Ju (WeBank Co., Ltd.)
John Rush (Google)

I come from a pure mathematics background, formerly a harmonic analyst and mathematical physicist. I transferred to machine learning on the software side after grad school, and joined Google in 2018, working on federated learning. I am a main author of TensorFlow Federated; ask me about it!

Ruixiao Zhang (Tsinghua university)
Youchi ZHOU (WeBank)
Françoise Beaufays (Google)

Françoise Beaufays is a Principal Scientist at Google, where she leads a team of engineers and researchers working on speech recognition and mobile keyboard input. Her area of expertise covers deep learning, language modeling and other technologies related to natural language processing, with a recent focus on privacy-preserving on-device learning. Françoise studied Mechanical and Electrical Engineering in Brussels, Belgium. She holds a PhD in Electrical Engineering and a PhD minor in Italian Literature, both from Stanford Uni

Yingxuan Zhu (Futurewei Technologies)
Lei Xia (Intel china)

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