P1040874.jpg

Vision Problems from two face images?

Stereo?

Aging?

Color from Gray?

Face Recognition?

Novel View Rendering?

More???

 

 

           P1040914.jpg


Brief Bio:

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I have moved to National Institutes of Health, Clinical Center, Radiology and Imaging Science Department, pursuing how to push modern medical image understanding and semantic parsing to fit into revolutionary  clinical workflow practices. There are four key ingredients: software and hardware code development platforms; close R&D collaboration with physicians-in-the-loop; evaluation & validation via large scale clinical imaging datasets; and mapping the recent progresses in statistical learning, machine learning, computer vision and video computing (from 2D/3D to 3D and 4D) towards medical imaging. 

 

I was a Senior Staff Scientist, Image Analytics and Informatics, at Siemens Corporate Research, from Nov. 2011 until Jan. 2013. I was a Staff Scientist at Siemens Computer Aided Diagnosis (CAD) Group, Siemens Medical Solutions at Malvern, Pennsylvania, from Nov. 2009 to Oct. 2011. I worked as a Research Scientist in Siemens Corporate Research (SCR), a Division of Siemens Corporation, Princeton, New Jersey from Oct. 2006 to Oct. 2009, closely collaborating with CAD group. I enjoyed working with a number of excellent Siemens colleagues and interns for a very productive period of time (6.28 years). Our efforts result in 10+ deployed Siemens medical imaging product deliveries, 10 US/WO patents (granted & pending), 27 provisional patents and 20+ scientific publications.

 

I received my Ph.D. degree of Computer Science from Johns Hopkins University in May 2007 and my advisor is Prof. Gregory D. Hager. I also worked closely with Prof. Laurant Younes and Prof. Rene Vidal at Hopkins. I interned twice at Microsoft Research Beijing and Redmond during 2000~2001, and 2004 summer with Dr. Harry (Heung-Yeung) Shum and Dr. Kentaro Toyama, respectively. I was a graduate student with Dr. Zhanyi Hu at NLPR, CAS, Beijing, China.

 

Ph.D. in Computer Science, Johns Hopkins University, Baltimore, Maryland, May 2007 (Advisor: Gregory D. Hager)

MSE in Computer Science, Johns Hopkins University, Baltimore, Maryland, May 2004 (Advisor: Gregory D. Hager)

Internship at Microsoft Research Beijing & Redmond, 2000-2001, 2004 (Mentors: Harry Shum, Kentaro Toyama, Zhengyou Zhang, Long Quan)


Visiting Student in Chinese University of Hong Kong (Advisors: Hung-Tat Tsui, Zhanyi Hu)

Graduate Student in Pattern Recognition and Intelligent Systems, NLPR, Institute of Automation, CAS, 1996~1999 (Advisor: Zhanyi Hu)

B.E. in ME & Automation Control, Beijing Polytechnic University, Beijing, China, July 1996

 


Recent Activities:

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Program / Paper Review Committee: IEEE CVPR, 2014, 2013, 2012, 2011, 2010, 2009; IEEE ICCV 2013, 2011, 2009; ECCV 2012, 2010; MICCAI 2013, 2012, 2011, 2010, 2009

ACCV 2012, 2010, 2009

Paper Reviewer: IEEE Trans. PAMI, IEEE Trans. Image Processing, IEEE Trans. Medical Imaging, Pattern Recognition, Pattern Recognition Letter; PLOS One

Wokshop Co-organizer: IEEE CVPR Medical Computer Vision Workshop, 2012; NIPS workshop on Machine Learning for Clinical Data Analysis and Healthcare, 2013


Recent Talks:

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Talk at MICCAI 2010 on Vertebra Segmentation and Identification, Sept. 2010, Beijing, China (ppt)

Talk at Computational and Visualization Challenges in the New Era of Virtual Colonoscopy Meeting, MICCAI, Sept. 06, 2008, New York

RSNA Talk on ICV detection for Colon CAD (Annual Meeting of Radiology Society of North America, Nov. 2007, Chicago)

ICML Talk on Clustering (International Conference of Machine Learning, June 2006, Pittsburgh), (ppt)

CVPR Talk on Nonparametric Robust Visual Tracking (IEEE Conference on Computer Vision and Pattern Recognition, June 2007, Minneapolis), (ppt, zip)

I Gave a Tech Talk at Google in May 2006! The video was an overview of my graduate research on image patch representations/modeling for visual recognition and tracking. During the past year, some parts have been updated.


Research Interests:

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Learning based 3D Volumetric, Surface, Curve Parsing for Medical Diagnosis
(13+)

New Classification Paradigms for Computer-aided Diagnosis (MICCAI 2011, CVPR 2011, Ongoing)

Discriminative/Generative Feature Learning for Computer-aided Diagnosis (Ongoing)

Structure Parsing for Medical Imaging and Analysis (ICCV 2009, MICCAI 2009, MICCAI 2010, Ongoing)

Supervised Learning Approach for Medical Imaging and Analysis (CVPR 2008, ECCV 2008, CVPR 2010, CVPR 2011, Ongoing)

Supervised Discriminative Dimension Reduction (Ongoing)

Online Appearance Modeling for Tracking and Recognition (NIPS 2006, CVPR 2007)
New Clustering Method for Visual Data (ICML 2006)
Scene Analysis and Category Recognition (CVPR 2005)
Articulated Object Motion Modeling and Recognition (NIPS 2004)
Efficient Particle Filtering using RANSAC (FPIV 2004, IVC 2006)   
Real-time Video Mosacing with Medical and Non-medical Applications (CVPR 2003 Demo)
Graphical Models and Tree-Structured Object Tracking (
Life time interest, but never get a chance to do it, :-)) )

Publications (peer-refereed major conferences and journals):

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2013

Jianhua Yao, Hector Munoz, Joseph E. Burns, Le Lu, Karen Kurdziel, Ronald D. Summers, "Computer Aided Detection of Spinal Degenerative Osteophytes on Sodium Fluoride PET/CT", Computational Methods and Clinical Applications for Spine Imaging Workshop, MICCAI 2013

Qian Wang*, Le Lu, Dijia Wu, Noha El-Zehiry, Dinggang Shen, S. Kevin Zhou, "Automatic and Reliable Segmentation of Spinal Canals in Low-Resolution, Low-Contrast CT Images", Computational Methods and Clinical Applications for Spine Imaging Wokshop, MICCAI 2013

Quan Wang*, Dijia Wu, Le Lu, Meizhu Liu, S. Kevin Zhou, "Semantic Context Feature Boosting for Learning-Based Knee Cartilage Segmentation in 3D MR Images", MCV'2013: Medical Computer Vision Workshop, MICCAI 2013

Le Lu, Pandu Devarakota, Siddharth Vikal, Dijia Wu, Yefeng Zheng, Matthias Wolf, "Computer Aided Diagnosis using Multilevel Image Features on Large-Scale Evaluation", MCV'2013: Medical Computer Vision Workshop, MICCAI 2013

Le Lu, Bing Jian, Dijia Wu, Matthias Wolf, "A New Algorithm of Electronic Cleansing for Weak Faecal-Tagging CT Colonography", MLMI'2013: Machine Learning in Medical Imaging Workshop, MICCAI 2013

Shijun Wang, Brandon Peplinski, Le Lu, Weidong Zhang, Jianfei Liu, Zhuoshi Wei, Ronald D. Summers, "Sequential Monte Carlo Tracking for Marginal Artery Segmentation on CT Angiography by Multiple Cue Fusion", MICCAI'2013: 16th International Conference on Medical Image Computing and Computer Assisted Intervention, Nagoya, Japan

Evrim Turkbey,
Le Lu, JianHua Yao, Zhuoshi Wei, Ronald D. Summers, "Computer-aided Detection of Colitis in Computed Tomography Examinations", Oral presentation, RSNA 2013

Jianhua Yao, H. Munoz, J.E. Burns, K.A. Kurdziel, P.L. Choyke, Le Lu, et al., "Detection Bertebral Degenerative Diesease on 18F-NaF PET/CT Using a Novel Cortical Shell Map",
Oral presentation, RSNA 2013

Automatic Spinal Canal Segmentation Using Cascaded Random Walks, Qian Wang*, Le Lu, Dijia Wu, S. Kevin Zhou, Non-Provisional US Patent Application, 2013P03587US01.


2012

Chi Li*, Le Lu, Gregory D. Hager, Jianyu Tang, Hanzi Wang, Robust Object Tracking in Crowd Dynamic Scenes Using Explicit Stereo Depth, ACCV'2012: The 11th Asian Conference on Computer Vision, Volume 3, pages 71-85, Daejeon, Korea

Jun Ma*, Le Lu, Hierarchical Segmentation and Identification of Thoracic Vertebra Using Learning-based Edge Detection and Coarse-to-fine Deformable Model, Journal of Computer Vision and Image Understanding, Special Issue of Shape Modeling, Volume 117, issue 9, September 2013, pages 1072-1083

Automatic Spatial Context Based Multi-Object Segmentation in 3D Images, Quan Wang*, Dijia Wu, Meizhu Liu, Le Lu, S. Kevin Zhou, Non-Provisional US Patent Application, 2012P28295US01.


2011

Meizhu Liu*, Le Lu, Xiaojing Ye, Shipeng Yu, Heng Huang, Coarse-to-fine Classification using Parametric and Nonparametric Models for Computer-Aided Diagnosis, CIKM'2011: 20th ACM Conference on Information and Knowledge Management, October 2011, Glasgow, UK (the short version)

 

The Formula of something "WoW" that works magically (then supposedly): "simple intuitive, or counter-intuitive design accept" + "fine engineered implementation" = "think globally, act locally" = "Good vision/idea, fine engineering"

 

Meizhu Liu*, Le Lu, Xiaojing Ye, Shipeng Yu, Marcos Salganicoff, Sparse Classification for Computer Aided Diagnosis Using Learned Dictionaries, MICCAI'2011: 14th International Conference on Medical Image Computing and Computer Assisted Intervention, September 2011, Toronto, Canada

 

Meizhu Liu*, Le Lu, Jinbo Bi, Vikas Raykar, Matthias Wolf, Marcos Salganicoff, Robust Large Scale Prone-Supine Polyp Matching Using Local Features: A Metric Learning Approach, MICCAI'2011: 14th International Conference on Medical Image Computing and Computer Assisted Intervention, September 2011, Toronto, Canada

 

Le Lu, Jinbo Bi, Matthias Wolf, Marcos Salganicoff, Effective 3D Object Detection and Regression Using Probabilistic Segmentation Features in CT Images, CVPR'2011: IEEE Conference on Computer Vision and Pattern Recognition, June 2011, Colorado Springs, USA

 

Jinbo Bi, Dijia Wu*, Le Lu, Meizhu Liu*, Yimo Tao*, Matthias Wolf, AdaBoost on Low-Rank PSD Matrices for Metric Learning with Applications in Computer Aided Diagnosis, CVPR'2011: IEEE Conference on Computer Vision and Pattern Recognition, June 2011, Colorado Springs, USA

 

Matching of Regions of Interests Across Multiple Views, Meizhu Liu*, Le Lu, Vikas Raykar, Matthias Wolf, Marcos Salganicoff, Non-Provisional US Patent Application, filled on October 4th, 2011.

 

2010

Le Lu, Matthias Wolf, Jinbo Bi, and Marcos Salganicoff, "Correcting Misalignment of Automatic 3D Detection by Classification: Ileo-cecal Valve False Positive Reduction in CT Colonography", MICCAI-MCV'2010: Medical Computer Vision: Recognition Techniques and Applications in Medical Imaging, joint with 13th International Conference on Medical Image Computing and Computer Assisted Intervention, Springer Verlag, Sept. 2010, Beijing, China.

 

Jun Ma*, Le Lu, Yiqiang Zhan, Xiang Sean Zhou, Marcos Salganicoff and Arun Krishnan, "Hierarchical Segmentation and Identification of Thoracic Vertebra Using Learning-based Edge Detection and Coarse-to-fine Deformable Model", MICCAI'2010: 13th International Conference on Medical Image Computing and Computer Assisted Intervention, Sept. 2010, Beijing, China (Oral).

 

Dijia Wu*, Le Lu, Jinbo Bi, Yoshihisa Shinagawa, Kim Boyer, Arun Krishnan and Marcos Salganicoff, "Stratified Learning of Local Anatomical Context for Lung Nodules in CT Images", CVPR'2010: IEEE Conference on Computer Vision and Pattern Recognition, June 2010, San Francisco, CA.

 

Systems and Methods for Automatic Vertebra Edge Detection, Segmentation and Identification in 3D Imaging, Le Lu, Marcos Salganicoff, Yiqiang Zhan, Xiang Zhou, and Jun Ma*, Non-Provisional US Patent Application 12/978,434, filled on September 13th, 2010, US Patent granted, 8,437,521#, May 7th, 2013.

       

Systems and Methods for Multilevel Nodule Attachment Classification in 3D CT Lung Images, Jinbo Bi, Le Lu, Marcos Salganicoff, Yoshihisa Shinagawa, and Dijia Wu*, Non-Provisional US Patent Application 12/880,385, filled on September 13th, 2010.

 

Multi-level Contextual Learning of Data, Dijia Wu*, Le Lu, Jinbo Bi, Yoshihisa Shinagawa, and Marcos Salganicoff, Non-Provisional US Patent Application 12/962,901, filled on December 8th, 2010.

 

2009

Le Lu, Jinbo Bi, Shipeng Yu, Zhigang Peng, Arun Krishnan and Xiang Sean Zhou, "A Hierarchical Learning Approach for 3D Tubular Structure Parsing in Medical Imaging", ICCV'2009: 12th International Conference on Computer Vision, September 29-October 2, 2009, Kyoto, Japan.

 

Le Lu, Matthias Wolf, Jianming Liang, Murat Dundar, Jinbo Bi and Marcos Salganicoff, "A Two-level Approach Towards Semantic Colon Segmentation: Removing Extra-colonic Findings", MICCAI'2009: 12th International Conference on Medical Image Computing and Computer Assisted Intervention, vol. 1, pp. 1009-1016, September 20-24, 2009, London, UK.

 

Yimo Tao*, Le Lu, Maneesh Dewan, Albert Y. Chen*, Jason Corso, Marcos Salganicoff, and Arun Krishnan, "Multi-level Ground Glass Opacity Detection and Segmentation in CT Lung Images", MICCAI'2009: 12th International Conference on Medical Image Computing and Computer Assisted Intervention, vol. 1, pp. 715-723, September 20-24, 2009, London, UK.

 

User Interface for Polyp Annotation, Segmentation, and Measurement in 3D Computed Tomography Colonography, Le Lu, Adrian Barbu, Matthias Wolf, Sarang Lakare, Luca Bogoni, Marcos Salganicoff, and Dorin Comaniciu, Non-provisional US Patent Application 20090080747, US Patent Granted, 8,126,244#, 2012.

 

Method and System for Polyp Segmentation for 3D Computed Tomography Colonography, Le Lu, Adrian Barbu, Matthias Wolf, Sarang Lakare, Luca Bogoni, Marcos Salganicoff, and Dorin Comaniciu, Non-provisional US Patent Application 20090074272, US Patent Granted, 8,184,888#, 2012, WO Patent WO/2009/038,647

 

INTERFACE UTILISATEUR POUR UNE ANNOTATION, UNE SEGMENTATION, ET UNE MESURE DE POLYPE EN COLOSCOPIE VIRTUELLE 3D, Le LU, A BARBU, M WOLF, S LAKARE, L BOGONI, M SALGANICOFF, D COMANICIU, WO Patent WO/2009/042,034

 

2008

Le Lu, Adrian Barbu, Matthias Wolf, Jianming Liang, Luca Bogoni, Marcos Salganicoff, and Dorin Comaniciu, "Simultaneous Detection and Registration for Ileo-Cecal Valve Detection in 3D CT Colonography", ECCV'2008: European Conference on Computer Vision, October, 2008, Marseille, France.

 

Le Lu, Adrian Barbu, Matthias Wolf, Jianming Liang, Marcos Salganicoff, and Dorin Comaniciu, "Accurate Polyp Segmentation for 3D CT Colonography Using Multi-Staged Probabilistic Binary Learning and Compositional Model", CVPR'2008: IEEE Conference on Computer Vision and Pattern Recognition, June, 2008, Anchorage, USA.

 

Method and System for Detection and Registration of 3D Objects Using Incremental Parameter Learning, Adrian Barbu, Le Lu, Luca Bogoni, Marcos Salganicoff, and Dorin Comaniciu, Non-provisional US Patent Application 20080211812, US Patent Granted, 8,068,654#, November 29th, 2011.

 

2007

Le Lu, "Image and Video Exploration by Classification and Clustering Using Global and Local Visual Features", PH.D. Thesis, Computer Science Department, Johns Hopkins University, Baltimore, Maryland, USA, April 2007. (ACM Link)

 

Le Lu and Gregory D. Hager, "A Nonparametric Treatment on Location/Segmentation Based Visual Tracking", CVPR'2007: IEEE Conference on Computer Vision and Pattern Recognition (Oral), June, 2007, Minneapolis, USA.

 

2006

Le Lu and Gregory D. Hager, "Dynamic Background/Foreground Segmentation From Images and Videos using Random Patches", NIPS'2006: Neural Information Processing and System, Vancouver, B.C. Canada, Dec. 2006.

Le Lu and Rene Vidal, "Combined Central and Subspace Clustering on Computer Vision Applications", ICML'2006: International Conference of Machine Learning, June 2006, Pittsburgh, USA.

Le Lu, Xiangtian Dai and Gregory D. Hager, "Efficient Particle Filtering Using RANSAC with Application to 3D Face Tracking", Journal of Image and Vision Computing, vol 24, issue 6, pp.581-592, June 2006.

2005

Le Lu, Kentaro Toyama and Gregory D. Hager, "A Two Level Approach for Scene Recognition", CVPR'2005: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 2005, San Diego, USA.

Two lessons learned: Lesson 1 (Image patch level Modeling): There is no way, in general, to distinguish the scene category properly for every given image patch without contextual information. Even with contextual constraints, it is still a very difficult problem if working with a large amount of "real" customer pictures, not professional photos like CorelDraw database. We try to argue that a mixture probability density function is trainable for image patches with stability in terms of modeling/discrimination. For a high level, like scene recognition, task, we can further learn the importance of each patch based material class in proportion to its confusion factor across different scene categories. Lesson 2 (Both levels): Given a complex, high dimensional distribution of data samples, try to learn a mixture density model (considering smoothness offered by a density function) in an efficient and discriminative way f needed. For a recognition/classification task, try to integrate discriminative information within the overall generative (density) framework.

2004

Le Lu, Gregory D. Hager and Laurent Younes, "A Three Tiered Approach for Articulated Object Action Modeling and Recognition", NIPS'2004: Neural Information Processing and System, Vancouver, B.C. Canada, Dec. 2004. (a version with slightly more details)

Le Lu, Xiangtian Dai and Gregory D. Hager, "A Particle Filter without Dynamics for Robust 3D Face Tracking", IEEE Workshop of Face Processing in Video jointed with CVPR'2004, June 2004, Washington DC, USA.

Long Quan , Yichen Wei , Le Lu and Heung-Yeung Shum, "Constrained planar motion analysis by decomposition",  Journal of Image and Vision Computing, vol 22, issue 5, pp. 379-389, May 2004. 

2003

Xiangtian Dai, Le Lu and Gregory D. Hager, "Real-time Video Mosaicing with Adaptive Parameterized Warping", Demo Program, CVPR'2003: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, May 2003, Midson, USA.

2002

Le Lu and Hung-Tat Tsui, "Algebraic Characteristic, Geometric Interpretation and Degeneracy Analysis of Planar Motions, with Applications to Camera Self-calibration ", extended version submitted to Journal of Pattern Recognition.

Le Lu and Hung-Tat Tsui, "Algebraic Characteristic and Geometric Interpretation of Planar Motions and their Applications to Camera Self-calibration", ACCV'2002: the 5th Asian Conference on Computer Vision, Jan. 2002, Melbourne, Australia (initially invited for a special issue of International Journal of Image and Graphics for ACCV 2002, 10 out of all submissions)

2001

Le Lu, Zhengyou Zhang, Heung-Yeung Shum, Zhicheng Liu and Hong Chen, Model- and Exemplar-based Robust Head Pose Tracking Under Occlusion and Varying Expression, IEEE Workshop on Models versus Exemplars in computer Vision jointed with CVPR'2001, Dec. 2001, Hawaii, USA. 

Long Quan, Le Lu, Heung-Yeung Shum and M. Lhuillier, Concentric Mosaic(s), Planar Motion and 1D Cameras, ICCV'2001: The 8th international Conference on Computer Vision, pp.193-200, Jul. 2001, Vancouver, Canada.

Le Lu and Zhanyi Hu, "A New Factorization Technique for Projective Reconstruction", Chinese Journal of Electronics, (English Version), No.2, pp.196-202, Feb 2001.

2000

Le Lu, Hung-Tat Tsui and Zhanyi Hu, "A Novel Planar Motion Detection Method and the Robust Estimation of 1D Trifocal Tensor", ICPR'2000: The 15th International Conference on Pattern Recognition, Vol. 3, pp.815-818, Sept. 2000, Barcelona, Spain. (ACM Library link)

Le Lu, Zhanyi Hu and Hung-Tat Tsui, "Sub-sequence Factorization - an Efficient Approach for Projective Reconstruction", ACCV'2000: The 4th Asian Conference on Computer Vision, pp.1052-1057, Jan. 2000, Taipei, Taiwan, China

Publications (Technical Report and Peer Reviewed Abstracts):

Le Lu, A. Barbu, M. Wolf, J. Liang, S. Lakare, L. Bogoni, M. Salganico, D. Comaniciu, A. Krishnan, A Supervised Learning Approach for Fast and Accurate Polyp Segmentation/Measurement in Virtual Colonoscopy, MICCAI: Workshop on Computational and Visualization Challenges in the New Era of Virtual Colonoscopy, New York, USA, 2008. (15 Minutes Talk)

L. Bogoni, M. Wolf, A. Barbu, S. Lakare, M. Dundar, Le Lu, Learning-based Component for Suppression of False Positives located on the Ileo Cecal Valve: Evaluation of Performance on 802 CTC Cases, RSNA: Radiology Society of North America Annual Meeting, Chicago, USA, 2007. (12 Minutes Talk)

S. Lakare, M. Wolf, L. Bogoni, A. Barbu, M. Dundar, Le Lu, M. Salganico, Evaluation of a Learning-based Component for Suppression of False Positives Located on the Ileo Cecal Valve or Rectal Tube, ISVC: the 9th International Symposium on Virtual Colonoscopy, Boston, 2007.

Le Lu, "Real-time Video Mosaicing with Adaptive Parameterized Warping", Computational Interaction and Robotics Lab, Technical report, Computer Science Department, Johns Hopkins University, 2003.  (example and code)

Affiliations:

_______________________________________________________________________________________________________

Radiology and Imaging Science, National Institutes of Health Clinical Center, 01/2013-now

Image Analytics and Informatics, Siemens Corporate Research, 11/2011-01/2013

Computer Aided Diagnosis Group, Siemens Medical Solutions, 11/2009-10/2011

Integrated Data Systems Dept., Siemens Corporate Research, Inc. 10/2006-11/2009

Computer Science Dept., Johns Hopkins University, 08/2001-09/2006

Interactive Visual Media Group, Microsoft Research, Redmond, (Intern), 06/2004-08/2004

Visual Computing Group, Microsoft Research, Beijing, (Intern), 12/1999-07/2001

Electronic Engineering Dept., Chinese University of Hong Kong (Visiting student), 03/1999-08/1999

National Laboratory of Pattern Recognition, Institute of Automation, CAS, 09/1996-12/1999

 

Mentors (collaborators):

_______________________________________________________________________________________________________
Prof. Laurent Younes, Center of Imaging Science, Johns Hopkins university
Prof. Rene Vidal, Center of Imaging Science, Johns Hopkins University
Dr. Kentaro Toyama, Microsoft Research, summer 2004
Prof. Long Quan, HKUST, 2000
Dr. Zhengyou Zhang, Microsoft Research, 2000-2001

Dr. Harry Shum, Microsoft Research Asia, 2000-2001

 

Colleagues & Interns (collaborators):

_______________________________________________________________________________________________________
Dr. Adrian Barbu (SCR->FSU), Dr. Jinbo Bi (SMS->UCONN), Dr. Matthias Wolf, Dr. Bing Jian (SMS->Google), Dr. Jianming Liang (SMS->ASU), Dr. Shipeng Yu, Dr. Yiqiang Zhan, Dr. Zhigang Peng, Dr. Maneesh Dewan (SMS->Google), Dr. Dorin Comaniciu, Dr. Sean Xiang Zhou, Dr. Marcos Salganicoff, Dr. Arun Krishnan;

 

*Interns: Dr. Albert Y.C. Chen (2008, U of Buffalo), Yimao Tao (2008, VT->Microsoft Health Solution), Dr. Dijia Wu (2009, RPI->Siemens Corporate Research->Microsoft), Dr. Jun Ma (2009, JHU->GE Healthcare-> Siemens Molecular Imaging), Dr. Meizhu Liu (2010, UFL->Siemens Corporate Research->Yahoo! Labs), Chi Li (2011, XMU->JHU), Dr. Qian Wang (2012, UNC->STJU), Quan Wang (2012, RPI, co-mentored with Dijia Wu), David Allen (2013, UT Dallas), Ari Seff (2013- , UFL)

 

 

Contacts:

 

10 Center Drive, 1C515

Bethesda, MD 20837, USA