【15-35期 VALSE Webinar活动】
报告题目：Problem-solving Research for Medical Image Analysis and Computer Vision
报告摘要：In this talk, I will discuss three principles of evaluating and conducting first-level research efforts from my own experience: Impactful problems with Inspiring solutions to achieve high Performance (IIP). During this process, why three characteristics are needed: notely Interest, Curiosity and Perseverance (ICP).
嘉宾简介：Le Lu is a Staff Scientist at Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center (NIH-CC) since January 2013. He has been leading three technical thrusts at NIH-CC on employing deep learning (CNN, RNN) for high precision and large scale diagnostic medical image informatics. He is also an adjunct research faculty at Department of Computer Science, the Johns Hopkins University. Before NIH, he had 6+ years industrial R&D experience at Siemens Corporate Research and Siemens Medical Solutions and his last post was a Senior Staff Scientist. His Siemens research efforts resulted in 10+ key product components for Siemens Syngo.Via PEV-Colon and Lung Computer-aided Diagnosis software, besides 26 inventions, 12 patents and 20+ scientific publications. Le Lu finished his Ph.D. in Computer Science, from the Johns Hopkins University in 2006. His research interests on computer vision was developed as a graduate student at Institute of Automation, Chinese Academy of Sciences (1996-1999). He learned how to conduct first class research during his internships at Microsoft Research Asia (mentors: Harry Shum, Zhengyou Zhang and Long Quan) in 1999-2001; and Microsoft Research Redmond (mentor: Kentaro Toyama) in 2004 summer. He is the author or co-author of 70+ journal and conference papers, many appeared in MICCAI/TMI/MedIA/CVPR/ICCV/ECCV/NIPS/ICML/CIKM/ACCV. He has mentored or advised 20 interns, postbac and postdoc young researchers. Details are available at http://www.cs.jhu.edu/~lelu
报告题目：Thinking as a researcher and practicing as an engineer
报告摘要：Research is all about problem solving by innovation, which requires both deep understanding of the problem and solid implementation skills. In this talk, I will share some of my past experiences and observations in both research and product organizations, and discuss with the audience some common topics in research, e.g. understanding the state of the art, choosing topics, the difference between research and product, and the importance of conducting solid evaluation, etc.
嘉宾简介：Lei Zhang is a senior researcher in Microsoft Research, working on visual recognition by leveraging the power of big data and cloud computing. Prior to this, he has been working with Microsoft Research Asia for 12 years as a senior researcher, leading a research team working on visual recognition, image analysis, and large-scale data mining. His years of work on large-scale search-based image annotation has generated many practical impacts in multimedia search, including a highly scalable solution of duplicate image clustering for billions of images. From 2013 to 2015, he moved to Bing Multimedia Search as a principal development manager, helping develop cutting-edge solutions for web-scale image analysis and recognition problems, including image caption generation and high precision image entity linking. He is a senior IEEE member and a senior ACM member, and has served as editorial board members for Multimedia System Journal, as program co-chairs, area chairs, or committee members for many top conferences. He has published 100+ papers and holds 40+ U.S. patents for his innovations in multimedia, computer vision, web search and information retrieval. He earned all his degrees (B.E., M.E. and PhD) in Computer Science from Tsinghua University.
报告题目：How to Do Good Research in Machine Learning?
报告摘要：In this talk, I will share some of my personal thoughts and experience on doing research in the area of machine learning, and discuss on how to publish high-quality papers and develop a career in machine learning.
嘉宾简介：朱军，清华大学计算机系副教授、智能技术与系统国家重点实验室副主任、卡内基梅隆大学Adjunct Faculty。2001到2009年获清华大学计算机学士和博士学位，之后在卡内基梅隆大学做博士后，2011年回清华任教。主要从事机器学习、贝叶斯统计等基础理论、高效算法及相关应用研究，在国际重要期刊与会议JMLR, PAMI, ICML, NIPS等发表学术论文60余篇。受邀担任人工智能与模式识别顶级杂志IEEE TPAMI的编委，担任机器学习国际大会ICML2014地区联合主席, 担任ICML (2014, 2015, 2016)、NIPS (2013, 2015)、UAI (2014, 2015)、IJCAI2015、AAAI2016等国际会议的领域主席。获微软学者、中国计算机学会优秀博士论文奖、中国计算机学会青年科学家奖、国家优秀青年基金、中创软件人才奖等，入选IEEE Intelligent Systems杂志评选的“AI’s 10 to Watch”、国家“万人计划”青年拔尖人才、及清华大学221基础研究人才计划。