Date: May 6 (Wednesday), 2015, 14:00 ~ 18:00 Venue: Room No. 201, Engineering Building 2, Yonsei University, Seoul, Korea

Transcription

1 Microsoft Research Yonsei University Joint Workshop Date: May 6 (Wednesday), 2015, 14:00 ~ 18:00 Venue: Room No. 201, Engineering Building 2, Yonsei University, Seoul, Korea PROGRAM Time 14:00 ~ 14:10 14:10 ~ 14:40 Program Opening Remark (Prof. Won Woo Ro, School of Electrical & Electronic Engineering, Yonsei University) Dr. Zhengping Qian (Researcher, System Research Group, ) Keynote 1 Systems Research on Big-Data Platforms at Microsoft 14:40 ~ 15:10 Dr. Chin-Yew Lin (Principal Researcher and Research Manager, Knowledge Mining group, ) Keynote 2 Solving Math Number Word Problem What can NLP, Knowledge Engineering and Machine Learning contribute? 15:10 ~ 15:30 Coffee Break 15:30 ~ 16:00 16:00 ~ 16:30 Dr. Kun Tan (Senior Researcher, Wireless and Networking Group, ) Keynote 3 Massive MIMO Research in MSRA Dr. Tao Mei (Lead Researcher, Media Computing Group and Multimedia Search and Mining Group, ) Keynote 4 When Multimedia Information Retrieval Meets Big User Data 16:30 ~ 17:00 Dr. Steve Lin (Senior Researcher, Internet Graphics Group, ) Keynote 5 Intrinsic Image Decomposition and Its Application to Facial Image Enhancement 17:00 ~ 18:00 Introduction of Microsoft Research Collaborating Labs

2 Keynote 1 Dr. Zhengping Qian Researcher System Research Group Title : Systems Research on Big-Data Platforms at Microsoft Big-Data applications impose significant challenges in computing infrastructures. In this talk, I will introduce some of our recent projects on the systems support for Big-Data computation at Microsoft Research, in collaboration with product teams. Our journey begins with understanding real production systems at Microsoft: focusing on efficient batch processing (Dryad) and effective sharing of cluster resources (Apollo). Based on the experience gained, we identified and enabled new capabilities such as matrix computation (MadLINQ) and real-time streaming (TimeStream, SCOPE Streaming). I will focus on the abstractions for building related Big-Data systems, as well as the design choices we made according to the real, production requirements and workloads at Microsoft. I will also briefly talk about other related work in the Systems Research Group at. Dr. Zhengping Qian received his Ph.D. from South China University of Technology and joined Microsoft Research Asia as a researcher in His research interests are in distributed and data-parallel computation, as well as emerging and/or challenging applications. Dr. Qian won the Best Paper Award in EuroSys Currently, he enjoys identifying general abstractions for building Big-Data systems.

3 Keynote 2 Dr. Chin-Yew Lin Principal Researcher and Research Manager Knowledge Mining Group Title : Solving Math Number Word Problem What can NLP, Knowledge Engineering and Machine Learning contribute? With the availability of personal agents such as Cortana, Siri and Google Now, it seems a world of humans and machines communicate and solve problems together in natural language is not far away. The scene of freely chatting with HAL in 2001: A Space Odyssey and Samantha in Her could happen to us seems within reach. The question is are we ready to go there? Do we have sufficient and necessary technologies to make it happen? In this talk, I will use solving math number word problem as an example to show how the emerging NLP, knowledge engineering and machine learning technologies can pay the way to this holy grail and what challenges that we have to address to travel down the path. Dr. Chin-Yew Lin is a Principal Researcher and Research Manager of the Knowledge Mining group at Microsoft Research Asia. His research interests are knowledge mining, social computing, question answering, and automatic summarization. Recently, his main research directions are: (1) developing a semantic computing framework for real world applications and services including automatic acquisition of semantic knowledge, machine reading for semantic indexing, and automatic understanding of user intents; and (2) developing big social data analytics platform and services Project Soul. Building on experiences learned from Project Soul, his team is developing technologies to automatically learn social interaction knowledge from large-scale real world online data and transform unstructured and semi-structured web data into structured data to enable semantic computing. The goal is to enable context-aware interactive knowledge-enriched applications powered by intelligent data in the cloud. He developed automatic evaluation technologies for summarization, QA, and MT. In particular, he created the ROUGE automatic summarization evaluation package. It has become the de facto standard in summarization evaluations. ROUGE has been chosen as the official automatic evaluation package for Document Understanding Conference since Before joining Microsoft, he was a senior research scientist at the Information Sciences Institute at University of Southern California (USC/ISI). He was the program co-chair of ACL 2012 and program co-chair of AAAI 2011 AI & the Web Special Track. He is an Action Editor of Transactions of ACL and a member of the Editorial Board of Computational Linguistics.

4 Keynote 3 Dr. Kun Tan Senior Researcher Wireless and Networking Group Title : Massive MIMO Research in MSRA In this talk, I will first give a brief overview of wireless and networking group and then focus on the massive MIMO research in MSRA. Massive MIMO is an active research area and holds the promise to give another order of magnitude capacity improvement compared to existing wireless technologies. I will introduce the latest progress in this direction and also discuss the remaining challenges. Dr. Kun Tan is a Senior Researcher in Wireless and Networking Group, MSR Asia and leading the networking and wireless research. Previously, he has worked on various areas in networking, from application layer to physical layer. He is the inventor of Compound TCP, which is shipped in Windows Operating System. He also led the development of Sora software radio system, which is one of the most popular SDR platforms in use. He has a long publication list on top conferences, like SIGCOMM, Mobicom, NSDI etc., where he also won a number of community awards, such as Best Paper Award in NSDI 09 and Best Demo Award in SIGCOMM 10.

5 Keynote 4 Dr. Tao Mei Lead Researcher Media Computing Group, Multimedia Search and Mining Group Title : When Multimedia Information Retrieval Meets Big User Data Multimedia information retrieval has been studied for decades. Previous research has focused on content-based understanding, indexing and ranking from large scale multimedia data. With the popularity of commercial search engines as well as social networks, users are contributing huge amount of click data on the Web. Along with this trend, multimedia information retrieval is witnessing a new paradigm shift from content-based retrieval to leveraging user data for more effective yet efficient retrieval. In this talk, we will show several research projects which leverage big user data to conduct multimedia retrieval. In particular, we will demonstrate that how big user data can be used for 1) video understanding and embedding, 2) predicting popularity and trending search, and 3) reranking. Dr. Tao Mei is a Lead Researcher with Microsoft Research, Beijing, China. His current research interests include multimedia information retrieval and computer vision. He has authored or co-authored over 100 papers in journals and conferences, 10 book chapters, and edited three books. He holds 13 U.S. granted patents and more than 20 in pending. Tao was the recipient of several paper awards from prestigious multimedia journals and conferences, including the IEEE Circuits and Systems Society Circuits and Systems for Video Technology Best Paper Award in 2014, the IEEE Trans. on Multimedia Prize Paper Award in 2013, and the Best Paper Awards at ACM Multimedia in 2009 and 2007, etc. He is an Associate Editor of IEEE Trans. on Multimedia, ACM/Springer Multimedia Systems, and Neurocomputing. He is the General Co-chair of ACM ICIMCS 2013, the Program Co-chair of IEEE ICME 2015, IEEE MMSP 2015 and MMM He received the B.E. degree in automation and the Ph.D. degree in pattern recognition and intelligent systems from the University of Science and Technology of China, Hefei, China, in 2001 and 2006, respectively.

6 Keynote 5 Dr. Steve Lin Senior Researcher Internet Graphics Group Title : Intrinsic Image Decomposition and Its Application to Facial Image Enhancement The decomposition of an image into its intrinsic components, namely an albedo and a shading layer, is a fundamental task in computer vision which can facilitate a variety of applications such as segmentation and shapefrom-shading. In this talk, we will present an introduction to this problem and describe contributions we have made toward this goal on different forms of input, including single images, image sequences, and RGB-D video. We will also present our work on intrinsic image decomposition for human faces, and show how such decompositions can be used to enhance the appearance of facial images through the efficient and realistic application of virtual cosmetics. Dr. Steve Lin received the BSE degree in electrical engineering from Princeton University, and the PhD degree in computer science and engineering from the University of Michigan. He is presently a senior researcher in the Internet Graphics group of. He served as a Program Co-Chair for the International Conference on Computer Vision (ICCV) 2011 and is serving on the editorial board of the International Journal of Computer Vision (IJCV). His research interests include computer vision, image processing, and computer graphics.