东方科技论坛青年学者论坛:人工智能海外博士生研讨会视频回放

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杜少雷

卡内基梅隆大学

Simon Du (杜少雷) is a PhD student in the Machine Learning Department at the School of Computer Science, Carnegie Mellon University, advised by Professor Aarti Singh and Professor Barnabás Póczos. He obtained his B.S. in Engineering Math & Statistics and Electrical Engineering & Computer Science from University of California, Berkeley in 2015. His research interests broadly include topics in theoretical machine learning and statistics, such as deep learning, matrix factorization, convex/non-convex optimization, transfer learning, reinforcement learning, non-parametric statistics and robust statistics. Currently he is also developing methods for precision agriculture.

 

Ravid Schwartz-Ziv

希伯来大学

Ravid is currently a computational neuroscience PhD candidate at  the Hebrew University of Jerusalem at the Machine Learning Lab under the supervision of Prof. Tali Tishby. Ravid received both his B.A and his M.Sc degrees from the Hebrew University of Jerusalem. Ravid’s research interests lie in the intersection of learning, information and optimization, especially in deep neural networks. Ravid's main focus is exploring learning and dynamics via information for both artificial and biological neural network. 

 

张雨倩

哥伦比亚大学

Yuqian Zhang (张雨倩) is a Ph.D. candidate in the Electrical Engineering Department at Columbia University, advised by Professor John Wright. She received her B.S. in Electrical Engineering from Xi’an Jiaotong University. Her research spans across optimization, computer vision, signal processing, and machine learning. Specifically, her primary research interest is to develop efficient, reliable and robust algorithms for applications in computer vision, scientific data analysis, etc.

 

赵俊博

纽约大学

Junbo Zhao (赵俊博) is currently a 2nd year PhD student at CILVR lab at NYU, under the supervision of Professor Yann LeCun. His recent main research interests include deep learning and unsupervised learning, on both domains of vision and language. In recent years, Jake has interned at Facebook AI research team, Clarifai engineering team, NVIDIA autonomous driving team. He graduates from Wuhan University majoring in electrical engineering in 2014 and holds a master degree in data science from NYU.

 

David Wipf

微软研究院首席研究员

David Wipf目前是微软研究院位于北京的可视化计算小组首席研究员;其研究兴趣包括非凸优化、贝叶斯推理、稀疏/结构化算法和深度学习。

顾世翔

剑桥大学博士生

Shixiang Gu (顾世翔) is a PhD candidate at University of Cambridge and Max Planck Institute for Intelligent Systems, where he is jointly co-supervised by Richard E. Turner, Zoubin Ghahramani, and Bernhard Schoelkopf. He holds BASc. in Engineering Science from University of Toronto, where he completed this thesis with Professor Geoffrey Hinton. His research interests span deep reinforcement learning, deep learning, robotics, approximate inference and causality, and his research has been featured by MIT Technology Review and Google Research Blog. He also collaborates closely with Sergey Levine from UC Berkeley/Google and Tim Lillicrap from DeepMind.

 

 

周家骥

卡内基梅隆大学

Jiaji Zhou (周家骥) is a PhD student in the Manipulation Lab of the Robotics Institute at Carnegie Mellon University, co-advised by Matt Mason and Drew Bagnell. His work won the ICRA 2016 Best Conference Paper Award. He has interned at GoogleX self-driving car team, Dato and Toyota Research Institute Manipulation Group.  

 

 

朱玉可

斯坦福大学

Yuke Zhu (朱玉可) is a fifth-year Ph.D. student in Computer Science at Stanford University, advised by Professor Fei-Fei Li and Professor Silvio Savarese. His research focuses on the principles and applications of computer vision, machine learning, and robotics, in particular, visual knowledge and deep reinforcement learning. Prior to coming to Stanford, he received a BEng. degree from Zhejiang University and a BSc. degree from Simon Fraser University, working with Professor Greg Mori. He also collaborates with research labs including Snap Research, Allen Institute for Artificial Intelligence, and Google DeepMind.

 

孔祥宇

Peking University

Xiangyu Kong (孔祥宇) is a fifth-year Ph.D candidate in Computer Science at Peking University, under the supervision of Prof. Yizhou Wang. He also works very closely with Dr. Bo Xin of Microsoft Research Asia. Prior to that, He graduated from Harbin Institute of Technology with a Bachelor of Computer Science. His current research interest includes computer vision, machine learning (in particular, multi-agent deep reinforcement learning) and their applications in video game playing.

田渊栋

Facebook人工智能研究院研究员

Facebook人工智能研究领域的一名研究科学家,致力于研究游戏中的深度强化学习和深层非凸模型的理论分析。他是DarkForest (Facebook电脑Go项目)的首席研究员和工程师。在此之前,他是谷歌自动驾驶汽车团队的软件工程师/研究员。他是2013年ICCV Marr奖的获得者,因其在图像校准中对非凸优化的全局最优解的研究而获奖。

李航

华为诺亚方舟实验室主任

李航现为华为诺亚方舟实验室主任,于2012年加入华为;1990-2001年,供职于NEC公司研究实验室;2001-2012年,在微软亚洲研究院工作;其研究领域包括信息检索、自然语言处理、统计机器学习和数据挖掘。

吕正东

深度好奇™创始人 - CTO

留美计算机博士,新疆公共安全实验室首席专家,深度学习领域(尤其是自然语言处理方向)的国际权威。 2013年初创立华为诺亚方舟实验室的深度学习团队,从零开始建立软件及硬件平台,并在两年内带领诺亚方舟实验室在神经语言智能领域成为国际一流的研究机构。 2016年创立人工智能技术公司深度好奇,将包括神经符号模型在内的多项前沿技术应用于法律、公安、金融领域,大幅提升行业效能。其中,深度好奇的最新研究工作“面向对象的神经规划(OONP)”率先提出了复杂篇章理解的技术框架,获得学界和产业界的高度评价。 在2017年《人工智能杂志》关于神经语言智能的权威综述中引用的大中华区的十项工作中,吕博士及其团队的四项贡献获得了高度评价。 多项基于深度学习的自然语言处理技术专利的发明人,专利覆盖了语义匹配、问答、多轮对话和自动短信回复等。

 

 

胡戎航

加州大学伯克利分校

Ronghang Hu (胡戎航) is a 3rd-year Ph.D. student in computer science at UC Berkeley, working with Prof. Trevor Darrell. He has been working on a variety of topics in computer vision, and most notably joint vision and language tasks such as visual question answering. In 2017 summer, he was a research intern in Facebook AI Research (FAIR) working with Dr. Ross Girshick. He obtained his B.E. degree from Tsinghua University in 2015. Previously in 2013 and 2014, He was a research intern at Institute of Computing Technology, Chinese Academy of Science (ICTCAS) and was advised by Prof. Shiguang Shan and Prof. Ruiping Wang.

 

胡志挺

卡内基梅隆大学

Zhiting Hu (胡志挺) is a PhD student at Machine Learning Department, Carnage Mellon University. His advisor is Prof. Eric Xing. His research is focusing on knowledge-enriched deep learning, Bayesian modeling and inference, large-scale machine learning, and their applications in natural language processing, esp., text generation. His work on harnessing deep neural networks with logic rules was selected as one of the outstanding papers in ACL2016. He is the recipient of 2017 IBM Fellowship.

 

彭昊

华盛顿大学

Hao Peng (彭昊) is a second year Ph.D. student in Computer Science and Engineering at the University of Washington, advised by Prof. Noah Smith. He works on natural language processing and machine learning, and is particularly interested in broad-coverage semantics. Previously, Hao received B.S. from Peking University in 2016 (with hornor), and also visited University of Edinburgh and Microsoft Research Asia.

 

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