Something helped me to get here:

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I received my Ph.D. degree in Computer Science from Johns Hopkins University in May 2007, and my advisor is Prof. Gregory D. Hager. I focused on statistical learning based computer vision during my time in Hopkins from August 2001 to September 2006. I really enjoyed my student life in Baltimore which is a truly beautiful city in North America. I used to watch Hopkins Lacrosse Team playing in the first half of the year, and Baltimore Raven on NFL for the second part of the year. Need to mention, my advisor is also a great friend in daily life too.

 

It may not be well known but Hopkins does have many faculty members who share interests on computer vision. My thesis committee members are Profs Gregory Hager, Michael Kazhdan, Laurent Younes and Jianbo Shi (UPenn). I collaborated with Prof. Rene Vidal (JHU) from time to time and spent a wonderful summer internship with Dr. Kentaro Toyama at MSR Redmond. I also benefited from Profs. Donald Geman, Sanjiv Khudanpur, Fred Jelinek and many other professors classes and weekly seminars of Center of Imaging Science at JHU.

 

Before Hopkins I was with Dr. Harry Shum at visual computing group MSRA from December 1999 to July 2001, I worked on 3D reconstruction and face tracking projects where I also partially collaborated with Prof. Long Quan at HKUST and Dr. Zhengyou Zhang at MSR. More importantly, I developed my interests on statistical methods for computer vision. I am indebted to my first academic advisor, Dr. Zhanyi Hu who introduced and taught me into computer vision field, during 1997 to 1999 at NLPR, Institute of Automation, CAS. My five month visit to Dr. HT Tsui at CUHK in 1999 was also an unforgettable period of time where I spent a lot of time wondering how to do good research.

 

Since October 2006 to now, I have been working as a Research Scientist in Siemens Corporate Research, Inc., Princeton, New Jersey. I also closely collaborate with Siemens CAD group at Malvern, PA from Day One. I currently focus on solving medical imaging problems, such as topological structure parsing, anatomic structure detection and segmentation using general computer vision and applied machine learning techniques. So I am living at the intersection of Medical Imaging, Computer Vision and Machine Learning. No need to say, I am fortunate enough to collaborate with many wonderful colleagues (Drs. Adrian Barbu, Matthias Wolf, Jinbo Bi, Maneesh Dewan, and), for so far productive results. Still the goal to be achieved is using Principled Approaches to Solve Everyday Challenges in medical diagnosis via 2D/3D/4D imaging. Is it interesting?!