E-Mail:	jinbo bi AT siemens dot com
Mailing Address:	Computer Aided Diagnosis and Knowledge Solutions Siemens Medical Solutions, Inc. 51 Valley Stream Parkway Malvern, PA 19355
Ph.D Advisor:	Kristin P. Bennett
Research Interests:	mathematical programming, machine learning, data mining, kernel methods, support vector machines, feature selection, neural networks, statistical computing, drug discovery, medical imaging

Working Experience

• Siemens Medical Solutions, Inc. USA, Malvern, PA, Sept 2003 until now
  Staff Scientist , develop algorithms that automatically identify and detect structures in human body that are possibly cancerous or that present abnormalities, based on image data from CT, MRI, Ultrasound and other clinical imaging modalities. Applications include heart motion abnormality detection for coronary artery disease, lung nodule detection and colon polyp detection for cancer prognosis, etc.
• NEC Laboratories America, Inc., Princeton, NJ, May 2002 - December 2002
  Research Associate with Dr. Vladimir N. Vapnik, conduct studies and research on rigorous support vector machines (developed a C++ RSVM package), and related feature selection algorithms using mathematical programming techniques
• Rensselaer Polytechnic Institute, Troy, NY, May 2000 - Aug. 2003
  Research Assistant with Dr. Kristin P. Bennett at the Department of Mathematical Sciences, develop algorithms for machine learning, feature/variable selection, and support vector machines using mathematical programming, such as linear programming, quadratic programming, and integer programming. Apply the resulting algorithms to drug discovery, gene expression data analysis and portfolio selection analysis
• Rensselaer Polytechnic Institute, Troy, NY, Aug. 1999 - Apr. 2000
  Teaching Assistant at the Department of Mathematical Sciences, guide students' computer labs using Matlab and C for assignments hold office hours for Numerical computing and Probability theory and statistics
• Beijing Institute of Technology, Beijing, China, Aug. 1996 - Apr. 1999
  Research Assistant with Dr. Cang-Pu Wu at the Department of Automatic Control, conduct research on adaptive control optimization, neural networks, reinforcement learning and computer simulation of control systems

Selected Publications

• An Improved Multi-task Learning Approach with Applications in Medical Diagnosis,
  Jinbo Bi, Tao Xiong, Shipeng Yu, Murat Dundar, Bharat Rao
  Proceedings of the 18th European Conference on Machine Learning (ECML'08), 2008.
• Bayesian Multiple Instance Learning: Automatic Feature Selection and Inductive Transfer,
  Vikas Raykar, Balaji Krishnapuram, Jinbo Bi, Murat Dundar, Bharat Rao
  Proceedings of the 25th International Conference on Machine Learning (ICML'08), 2008.
• Reduction of Lymph Tissue False Positives in Pulmonary Embolism Detection,
  Bernard Ghanem, Jianming Liang, Jinbo Bi, Marcos Salganicoff and Arun Krishnan,
  Proceedings of SPIE Medical Imaging (SPIE'08), 2008.
• Large Scale Diagnostic Code Classification for Medical Patient Records,
  Lucian Vlad Lita, Shipeng Yu, Stefan Niculescu and Jinbo Bi,
  Proceedings of the 3rd International Joint Conference on Natural Language Processing (IJCNLP'08), 2008.
• Automatic Medical Coding of Patient Records via Weighted Ridge Regression,
  Jianwu Xu, Shipeng Yu, Jinbo Bi, Lucian Vlad Lita, Stefan Niculescu and Bharat Rao,
  Proceedings of the 6th International Conference on Machine Learning and Applications (ICMLA'07), 2007.
• LungCAD: A Clinically Approved, Machine Learning System for Lung Cancer Detection,
  R Bharat Rao, Jinbo Bi, Glenn Fung, Marcos Salganicoff, Nancy Obuchowski and David Naidich,
  Proceedings of the 13th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD'07), 2007.
• A Mathematical Programming Formulation for Sparse Collaborative Computer Aided Diagnosis,
  Jinbo Bi and Tao Xiong,
  Proceedings of the 22nd International Conference on Artificial Intelligence (AAAI'07), 2007.
• Joint Optimization of Cascaded Classifiers for Computer Aided Detection,
  Murat Dundar and Jinbo Bi,
  Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'07), 2007.
• Multiple Instance Learning of Pulmonary Embolism Detection with Geodesic Distance along Vascular Structure,
  Jinbo Bi and Jianming Liang,
  Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'07), 2007.
  This paper focuses on the classification approaches used in Siemens research project of pulmonary embolism detection.
• Computer Aided Detection of Pulmonary Embolism with Tobogganing and Multiple Instance Classification in CT Pulmonary Angiography,
  Jianming Liang and Jinbo Bi,
  Proceedings of the 20th International Conference on Information Processing in Medical Imaging (IPMI'07), 2007.
  This paper focuses on the initial identification of suspicious regions for Siemens research project of pulmonary embolism detection.
• Robust Parametric Modeling Approach Based on Domain Knowledge for Computer Aided Detection of Vertebrae Column Metastases in MRI,
  Anna Jerebko, G.P. Schmidt, Xiang Zhou, Jinbo Bi, V. Anand, J. Liu, S. Schoenberg, I. Schmueching, B. Kiefer and A. Krishnan,
  Proceedings of the 20th International Conference on Information Processing in Medical Imaging (IPMI'07), 2007.
• On the Medical Frontier: the 2006 KDD Cup Competition (the submitted version),
  Terran Lane, Bharat Rao, Jinbo Bi, Jianming Liang, Marcos Salganicoff,
  ACM Journal SIGKDD Explorations, 8(2):39-46, Dec 2006.
• Probabilistic Joint Feature Selection for Multi-task Learning ,
  Tao Xiong, Jinbo Bi, Bharat Rao and Vladimir Cherkassky
  Proceedings of SIAM International Conference on Data Mining (SDM'06), 2006.
• Learning Classifiers When the Training Data is not IID,
  Murat Dundar, Balaji Krishnapuram, Jinbo Bi and Bharat Rao,
  Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI'06), 2006.
• Efficient Model Selection for Regularized Linear Discriminant Analysis,
  Jieping Ye, Tao Xiong, Qi Li, Ravi Janardan, Jinbo Bi, Vladimir Cherkassky and Chandra Kambhamettu,
  Proceedings of the ACM Fifteenth Conference on Information and Knowledge Management (CIKM'06), 2006.
• Automatic View Recognition for Cardiac Ultrasound Images,
  Matthew E. Otey, Jinbo Bi, Sriram Krishnan, Bharat Rao, Jonathan Stoeckel, Alan Katz, Jing Han and Srinivasan Parthasarathy,
  Proceedings of the 1st International Workshop on Computer Vision for Intravascular and Intracardiac Imaging at Annual Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'06-CVII), 2006.
• Computer Aided Detection via Asymmetric Cascade of Sparse Hyperplane Classifiers,
  Jinbo Bi, Senthil Periaswamy, Kazunori Okada, Toshiro Kubota, Glenn Fung, Marcos Salganicoff and Bharat Rao,
  Proceedings of the ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD'06), 2006.
• MILES: Multiple-Instance Learning via Embedded Instance Selection,
  Yixin Chen, Jinbo Bi, James Z. Wang,
  IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(12):1-17, 2006.
• Active Learning via Transductive Experimental Design,
  Kai Yu, Jinbo Bi, Volker Tresp,
  Proceedings of the 23rd International Conference on Machine Learning (ICML'06), 2006.
• Sparse Classifier for Automated Heart Wall Motion Abnormality Detection,
  Glenn Fung, Maleeha Qazi, Siriram Krishnan, Jinbo Bi, Bharat Rao, and Alan Katz,
  Special session on "Application of Machine Learning in Medicine and Biology" of The 4th International Conference on Machine Learning and Applications (ICMLA), 2005.
• Semi-supervised Mixture of Kernels via LPBoost Methods,
  Jinbo Bi, Glenn Fung, Murat Dundar, and Bharat Rao,
  Proceedings of the 15th IEEE International Conference on Data Mining (ICDM'05), 2005.
• A Sparse Support Vector Machine Approach to Region-based Image Categorization,
  Jinbo Bi, Yixin Chen and James Wang,
  Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005.
• Sparse Fisher Discriminant Analysis for Computer Aided Detection,
  Murat Dundar, Glenn Fung, Jinbo Bi, S. Sandilya and Bharat Rao,
  Proceedings of SIAM International Conference on Data Mining (SDM'05), 2005.
• Clustering by Maximizing Sum-of-squared Separation Distance,
  Yixin Chen and Jinbo Bi,
  Proceedings of SIAM Data Mining Workshop on Clustering High Dimensional Data and its Applications, 2005.
• Support Vector Classification with Input Data Uncertainty,
  Jinbo Bi and Tong Zhang,
  Advances in Neural Information Processing Systems (NIPS'04), vol. 17, pp 161-168, 2004.
• Column-Generation Boosting Methods for Mixture of Kernels,
  Jinbo Bi, Tong Zhang and Kristin Bennett,
  Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD'04), pp. 521-526, 2004.
• A Fast Iterative Algorithm for Fisher Discriminant using Heterogeneous Kernels,
  Glenn Fung, Murat Dundar, Jinbo Bi and Bharat Rao,
  Proceedings of the 21st International Conference on Machine Learning (ICML'04), 2004.
• Regression Error Characteristic Curves,
  Jinbo Bi and Kristin Bennett,
  in Proceedings of the 20th International Conference on Machine Learning (ICML'03), 2003.
• Multi-Objective Programming in SVMs,
  Jinbo Bi,
  in Proceedings of the 20th International Conference on Machine Learning (ICML'03), 2003.
• Learning with Rigorous Support Vector Machines,
  Jinbo Bi and Vladimir Vapnik,
  in Proceedings of the 16th Annual Conference on Learning Theory (COLT'03), 2003.
• A Geometric Approach to Support Vector Regression,
  Jinbo Bi and Kristin Bennett,
  Neurocomputing, 55(1-2):79-108, 2003.
• Dimensionality Reduction via Sparse Support Vector Machines,
  Jinbo Bi, Kristin Bennett, Mark Embrechts, Curt Breneman and Minghu Song,
  Journal of Machine Learning Research, 3:1229-1243, 2003.
• Prediction of Protein Retention Times in Anion-exchange Chromatography Systems Using Support Vector Machines,
  M. Song, C. Breneman, Jinbo Bi, N. Sukumar, K. Bennett, S. Cramer and N. Tugcu,
  Journal of Chemical Information and Computer Science. 42(6):1347-1357, 2003.
• Descriptor Generation, Selection and Model Building in Quantitative Structure-Property Analysis,
  C. Breneman, K. Bennett, M. Embrechts, S. Cramer, M. Song and Jinbo Bi,
  A book chapter in Experimental Design for Combinatorial and High Throughput Materials Development, J Crawse Ed. 2002.
• Duality, Geometry, and Support Vector Regression,
  Jinbo Bi and Kristin Bennett,
  Advances in Neural Information Processing Systems (NIPS'01), 2001.

Presentations

Conferences

• Joint Optimization of Cascaded Classifiers for Computer Aided Detection, Oral presentation given by Jinbo Bi at IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'07), June 2007.
• CAD Performance Analysis for Pulmonary Nodule Detection on Thin-slice MDCT Scans -- M. Wolf, A. Krishnan, M. Salganicoff, Jinbo Bi, M. Dundar, G. Fung, J. Stoeckel, S. Periaswamy, H. Shen, P. Herzog and D. Naidich, CARS 2005 Computer Assisted Radiology and Surgery , June 2005. (a related paper is published in its proceedings)
• Clinical Evaluation of a Novel Automatic Real-time Myocardial Tracking and Wall Motion Scoring Algorithm for Echocardiography -- A. Katz, S. Krishnan, X. Zhou, B. Georgescu, D. Comaniciu, Jinbo Bi, G. Fung, and J. Liang, American College of Cardiology, March 2005.
• In Silico Screening for the hERG Potassium Channel Affinity -- M. Song, Jinbo Bi, C. M. Breneman, K. P. Bennett, 228th American Chemical Society meeting, Philadelphia, August 2004.
• Developing in silico Carcinogenicity Classification model based on the kernel combination approach -- M. Song, Jinbo Bi, K. P. Bennett, C. M. Breneman, ADMET-1 Conference, San Diego, Febuary 2004.
• Prediction of Protein Retention Times in Anion-exchange Chromatography System using Support Vector Regression -- M. Song, C. M. Breneman, N. Sukumar, K. P. Bennett, Jinbo Bi, S. Cramer and N. Tugcu, 224th American Chemical Society meeting, Boston, August 2002.
• QSPR Model Generation and Validation for Virtual High Throughput Screening -- M. Song, C. M. Breneman, N. Sukumar, Jinbo Bi, K. P. Bennett, S. Cramer, Gordon Conference on Combinatorial & High Throughput Materials Science, Kimball Union Academy, 2002.
• Caco-2 permeability modeling: Feature selection via sparse support vector machines -- C. M. Breneman, K. P. Bennett, Jinbo Bi, Mark J. Embrechts, M. Song, 223rd American Chemical Society meeting , Orlando, April, 2002
• Displacer Efficacy prediction by Electronic Shape/Property-Encode descriptors -- M. Song, Jinbo Bi, A. Ladiwala, W. Deng, N. Sukumar, M. Sundling, S. Cramer, C. M. Breneman, Albany Biotechnology Conference, September 2001.
• Duality, Geometry, and Support Vector Regression -- Jinbo Bi and K. P. Bennett, Advances in Neural Information Processing Systems (NIPS-2001). Vancouver. Dec. 2001
• Dimensionality Reduction and Model Visualization via Sparse Support Vector Machines -- K. P. Bennett and Jinbo Bi, NIPS 2001 Workshop on Feature Selection. Vancouver. Dec. 2001
• SVM, GAFEAT-NN, GA-PLS Modeling of Caco-2 Permeability using Electron Density-based Descriptors -- M. Song, Jinbo Bi, M. Ozdemir, N. Sukumar, M. J. Embrechts, Kristin Bennett, Curt M. Breneman, 222nd American Chemical Society meeting, Chicago, August 2001.
• Support Vector Machines for Pharmaceutical Data Analysis -- Jinbo Bi, The 18th International Conference on Machine Learning (ICML-2001). Williams College. June 2001

Seminars and invited talks

• Princeton University, Machine-Learning Group guided by Dr. Robert Schapire, Oct. 2004 -- Uncertainty Problems in Classification with Ultrasound Images
• Canadian Imperial Bank of Commerce, Customer Behaviour Analytics Group, Apr. 2003 -- Support Vector Machines - Regression, Classification, and Some Applications
• NEC Research Institute, Inc. August 2002 -- Rigorous Support Vector Machine and Feature Selection
• Seminars in Mathematics Department at RPI
• A brief introduction to learning theory and learning algorithms March 2003
• Krylov subspace methods: A technique for partial least squares regression? November 2001

Professional Services

• Reviewer for International Journals
  Journal of Machine Learning Research, Machine Learning Journal, Journal of Artificial Intelligence Research, Data Mining and Knowledge Discovery Journal, European Journal of Operations Research, Neurocomputing, IEEE Trans. on Neural Networks, IEEE Trans. on Pattern Analysis and Machine Intelligence, IEEE Trans. on Systems, Man and Cybernetics (B), Pattern Analysis and Applications Journal
• Reviewer for International Conferences
  ACM International Conference on Data Mining and Knowledge Discovery (SIGKDD), Neural Information Processing Systems (NIPS), International Conference on Machine Learning (ICML), SIAM International Conference on Data Mining (SIAM DM)
• Editorial Review Board Member
  Advances in Chemoinformatics and Computational Methods (ACCM) Book Series
• Reviewer for Grants Proposal
  Louisiana Board of Regents' Research Competitiveness EPSCoR-style Grants Program 2004
• Program Committee Member
  ACM International Conference on Data Mining and Knowledge Discovery (SIGKDD 2005)

Informative Links (Obsolete since the last update was in 2003)