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Lightning Talk
Lightning Talks 4B-1
Alexandra Senderovich · Zhijie Deng · Navid Ansari · Xuefei Ning · Yasmin Salehi · Xiang Huang · Chenyang Wu · Kelsey Allen · Jiaqi Han · Nikita Balagansky · Tatiana Lopez-Guevara · Tianci Li · Zhanhong Ye · Zixuan Zhou · Feng Zhou · Ekaterina Bulatova · Daniil Gavrilov · Wenbing Huang · Dennis Giannacopoulos · Hans-peter Seidel · Anton Obukhov · Kimberly Stachenfeld · Hongsheng Liu · Jun Zhu · Junbo Zhao · Hengbo Ma · Nima Vahidi Ferdowsi · Zongzhang Zhang · Vahid Babaei · Jiachen Li · Alvaro Sanchez Gonzalez · Yang Yu · Shi Ji · Maxim Rakhuba · Tianchen Zhao · Yiping Deng · Peter Battaglia · Josh Tenenbaum · Zidong Wang · Chuang Gan · Changcheng Tang · Jessica Hamrick · Kang Yang · Tobias Pfaff · Yang Li · Shuang Liang · Min Wang · Huazhong Yang · Haotian CHU · Yu Wang · Fan Yu · Bei Hua · Lei Chen · Bin Dong

Wed Dec 07 05:00 PM -- 05:15 PM (PST) @
in Featured Papers Panels 4B »

Q&A on RocketChat immediately following Lightning Talks

Author Information

Alexandra Senderovich (Higher School of Economics)
Zhijie Deng (Shanghai Jiao Tong University)
Zhijie Deng

Zhijie Deng joined Qing Yuan Research Institute of Shanghai Jiao Tong University as a tenure-track assistant professor in July 2022. He obtained the Ph.D. degree from Department of Computer Science and Technology, Tsinghua University in June 2022, under the supervision of Prof. Bo Zhang and Prof. Jun Zhu.

Navid Ansari (Max Planck Institute for Informatics)
Xuefei Ning (Tsinghua University)
Yasmin Salehi (McGill University)

I am a graduate machine learning researcher and a recent Electrical and Computer Engineering Master's graduate from McGill University. My scientific background lies in Electrical Engineering, Software Engineering, Biomedical Engineering, and Computer Science. Specifically, my Master’s degree involved advanced courses in Mathematics and Computer Science, with a focus on Machine Learning. My previous research work has been on the application of Graph Representation Learning in Natural Language Processing, Physics, and Medicine.

Xiang Huang (University of Science and Technology of China)
Chenyang Wu (Nanjing University)
Kelsey Allen (DeepMind)
Jiaqi Han (Tsinghua University)
Nikita Balagansky (Tinkoff)
Tatiana Lopez-Guevara (DeepMind)
Tianci Li (Nanjing University)
Zhanhong Ye (Peking University)
Zixuan Zhou (Tsinghua University, Tsinghua University)
Feng Zhou (Renmin University of China)
Ekaterina Bulatova (Higher School of Economics)
Daniil Gavrilov (Tinkoff)
Wenbing Huang (Tsinghua University)
Dennis Giannacopoulos (McGill University)
Hans-peter Seidel (Max-Planck Institute)
Anton Obukhov (ETH Zurich)
Kimberly Stachenfeld (DeepMind)
Hongsheng Liu (Huawei Technologies Ltd.)
Jun Zhu (Tsinghua University)
Junbo Zhao (Tsinghua University, Tsinghua University)
Hengbo Ma (University of California, Berkeley)
Nima Vahidi Ferdowsi (Saarland Informatics Campus, Max-Planck Institute)
Zongzhang Zhang (Nanjing University)
Zongzhang Zhang

I am now an associate professor at the School of Artificial Intelligence, Nanjing University.

Vahid Babaei (Max Planck Institute for Informatics)
Jiachen Li (Stanford University)
Alvaro Sanchez Gonzalez (DeepMind)
Yang Yu (Nanjing University)
Shi Ji (University of Chinese Academy of Sciences)
Maxim Rakhuba (HSE University)
Tianchen Zhao (Beihang University)
Yiping Deng (Tsinghua University, Tsinghua University)
Peter Battaglia (DeepMind)
Josh Tenenbaum (MIT)

Josh Tenenbaum is an Associate Professor of Computational Cognitive Science at MIT in the Department of Brain and Cognitive Sciences and the Computer Science and Artificial Intelligence Laboratory (CSAIL). He received his PhD from MIT in 1999, and was an Assistant Professor at Stanford University from 1999 to 2002. He studies learning and inference in humans and machines, with the twin goals of understanding human intelligence in computational terms and bringing computers closer to human capacities. He focuses on problems of inductive generalization from limited data -- learning concepts and word meanings, inferring causal relations or goals -- and learning abstract knowledge that supports these inductive leaps in the form of probabilistic generative models or 'intuitive theories'. He has also developed several novel machine learning methods inspired by human learning and perception, most notably Isomap, an approach to unsupervised learning of nonlinear manifolds in high-dimensional data. He has been Associate Editor for the journal Cognitive Science, has been active on program committees for the CogSci and NIPS conferences, and has co-organized a number of workshops, tutorials and summer schools in human and machine learning. Several of his papers have received outstanding paper awards or best student paper awards at the IEEE Computer Vision and Pattern Recognition (CVPR), NIPS, and Cognitive Science conferences. He is the recipient of the New Investigator Award from the Society for Mathematical Psychology (2005), the Early Investigator Award from the Society of Experimental Psychologists (2007), and the Distinguished Scientific Award for Early Career Contribution to Psychology (in the area of cognition and human learning) from the American Psychological Association (2008).

Zidong Wang (Zhejiang University)
Chuang Gan (UMass Amherst/ MIT-IBM Watson AI Lab)
Changcheng Tang (Beijing Novauto Co. Ltd)
Jessica Hamrick (DeepMind)
Kang Yang (Huazhong University of Science and Technology)
Tobias Pfaff (DeepMind)
Yang Li (University of Chinese Academy of Sciences)
Shuang Liang
Min Wang (Huawei Technologies Ltd.)
Huazhong Yang (Tsinghua University, Tsinghua University)
Haotian CHU (Huawei)
Yu Wang (Tsinghua University)

Yu Wang received his B.S. degree in 2002 and Ph.D. degree (with honor) in 2007 from Tsinghua University, Beijing. He is currently a Tenured Associate Professor with the Department of Electronic Engineering, Tsinghua University. His research interests include brain inspired computing, application specific hardware computing, parallel circuit analysis, and power/reliability aware system design methodology. Dr. Wang has authored and coauthored over 150 papers in refereed journals and conferences. He has received Best Paper Award in FPGA 2017, ISVLSI 2012, and Best Poster Award in HEART 2012 with 8 Best Paper Nominations. He is a recipient of IBM X10 Faculty Award in 2010. He served as TPC chair for ICFPT 2011 and Finance Chair of ISLPED 2012-2016, and served as program committee member for leading conferences in these areas, including top EDA conferences such as DAC, DATE, ICCAD, ASP-DAC, and top FPGA conferences such as FPGA and FPT. Currently he serves as Co-EIC for SIGDA E-Newsletter, Associate Editor for IEEE Transactions on CAD and Journal of Circuits, Systems, and Computers. He also serves as guest editor for Integration, the VLSI Journal and IEEE Transactions on Multi-Scale Computing Systems. He is a recipient of NSFC Excellent Young Scholar，and is now serving as ACM distinguished speaker. He is an IEEE/ACM senior member.

Fan Yu (University of Science and Technology of China)
Bei Hua (University of Science and Technology of China)
Lei Chen (Hong Kong University of Science and Technology)
Bin Dong (Peking University)

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