Time: 10:00-11:00, Sep. 5
Location: SIST 1A 200
Host: Prof. Jingyi Yu
In this talk, I will first give a brief introduction on graph matching, which is a combinatorial problem in nature. Then we will show a deep network based pipeline for addressing the graph matching problem via deep learning. The model involves learning of the graph node embedding, cross-graph affinity learning, and a Sinkhorn layer for solving the linear assignment task. We will also discuss some working paper on joint matching and link prediction among two or multiple graphs. In the end, some discussion will be given on the future work and outlook for connecting graph matching with machine learning.
Dr. Junchi Yan is currently an Independent Research Professor (PhD Advisor) with Department of Computer Science and Engineering, Shanghai Jiao Tong University. He is also affiliated with The Artificial Intelligence Institute of SJTU and an adjunct professor with the School of Data Science, Fudan University. Before that, he was a Research Staff Member with IBM Research - China where he started his career since April 2011. He obtained the Ph.D. at the Department of Electronic Engineering of Shanghai Jiao Tong University, China. His work on graph matching received the ACM China Doctoral Dissertation Nomination Award and China Computer Federation Doctoral Dissertation Award. His research interests are machine learning, data mining and computer vision. He serves as an Associate Editor for IEEE ACCESS, (Managing) Guest Editor for IEEE Transactions on Neural Network and Learning Systems, Pattern Recognition Letters, Pattern Recognition, Vice Secretary of China CSIG-BVD Technical Committee, and on the executive board of ACM China Multimedia Chapter. He has published 50+ peer reviewed papers in top venues in AI and has filed 20+ US patents. He wins the Distinguished Young Scientist of Scientific Chinese for year 2018.
嚴駿馳博士現任上海交通大學計算機系與人工智能研究院特別研究員（博導），交大ACM班項目副主任（負責AI方向），復旦大學大數據學院校外研究生導師。主持包括國家自然科學基金、以及與招行、銀聯、騰訊、京東、平安等在內多項合作研究項目。曾于IBM（北京、紐約、上海）任職7年。加入上海交大之前，任IBM中國研究院主管研究員（認知物聯網首席科學家）和復旦大學大數據學院校外導師，主導了多項人工智能技術在國內外大型企業和政府創新應用的研發與落地。近年來的研究工作致力于精細化數據建模與機器學習，在結構信息匹配與識別方面發表NIPS,CVPR,ICCV,ECCV,ACM-MM,AAAI,TIP,TCYB,TPAMI論文20余篇；在時序信息建模與學習發表NIPS,SIGIR,KDD,AAAI,IJCAI發表論文20余篇。授權美國發明專利15項，連續兩屆被評為IBM全球發明大師?，F任中國圖象圖形學學會視覺大數據專委會副秘書長、ACM中國SIGMM執委、IEEE TNNLS期刊責任客座編輯、Pattern Recognition期刊客座編輯、IEEE ACCESS期刊編委，曾任IBM美國沃森研究中心、日本國立情報學研究所、騰訊/京東人工智能實驗室等機構訪問學者。嚴駿馳博士也是2018年度科學中國人杰出青年科學家獎和2016年度CCF優博的獲得者。