Associate Professor, Department of Statistics, Florida
Currently Serving as Graduate Student Director.
Please note that I am not in the admissions committee, so I cannot answer any admissions related questions.
- Machine Learning
- Medical Imaging
- Computer Vision
- Feature Selection with Annealing - A generic method for feature selection and model learning
that outperforms boosting and methods based on sparsity inducing penalties such as L1, SCAD, and MCP. (arxiv)
- Two-round EM - Theoretical guarantees for an EM algorithm for estimating mixtures of
binary templates corrupted by Bernoulli noise.(arxiv)
- Face Detection with a 3D Model. (arxiv)
- Artificial Prediction Markets - An online learning
method inspired from economics that learns a model
that minimizes the KL divergence to the distribution on the training examples, for
- Active Random Fields
- A MRF based model trained together with a fast and suboptimal
inference algorithm achieves
thousands of times speedup without loss in accuracy.
- Marginal Space
Learning - A learning-based optimization method that achieves
many orders of magnitude speedup for object detection in large parameter spaces.
- Graph Partition by
Cuts - A fast stochastic graph partition algorithm. that samples a probability model using low level cues to speed up
- S. Liu, A. Barbu. Unsupervised Learning of Mixture Models with a Uniform Background Component.
- L. Sun, A. Barbu. Online Learning with Model Selection. (arxiv, slides)
- G. Dawer, A. Barbu. Relevant Ensemble of Trees. (arxiv)
- N. Lay, Y. Tsehay, R. Cheng, S. Gaur, A. Barbu, L. Lu, B. Turkbey, P. Choyke , P. Pinto, R. Summers.
A Decomposable Model for Prostate Cancer Detection in Multi-Parametric MRI. MICCAI, 2018, Granada, Spain
- H. Mou, A. Barbu. Accurate Dictionary Learning with Direct Sparsity Control. ICIP 2018, Athens, Greece
- J. Anaya, A. Barbu. RENOIR - A Dataset for Real Low-Light Image Noise Reduction. Journal of Visual Comm. and Image Rep. 51, No. 2, 144-154, 2018 (arxiv,
- A. Gupta, A. Barbu. Parameterized Principal Component Analysis. Pattern Recognition 78, No. 6, 215–227, 2018
- A. Barbu, N. Lay, G.Gramajo. Face Detection with a 3D Model. "Academic Press Library in Signal Processing Volume 6: Image and Video Processing and Analysis and Computer Vision".
pp 237-259, 2018. Editors: R. Chellappa and S. Theodoridis.(arxiv, link)
- A. Barbu. A Directed Graph Approach to Active Contours. ICIP 2017 (pdf)
- A. Barbu, Y. She, L. Ding, G. Gramajo. Feature Selection with Annealing for Computer Vision and Big Data Learning. IEEE PAMI, 39, No. 2, 272-286, 2017.
- A. Barbu, L. Lu, H. Roth, A. Seff, R.M. Summers. An Analysis of Robust Cost Functions for CNN in Computer-Aided Diagnosis. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 2016.
- L. Ding, A. Barbu. Scalable Subspace Clustering with Application to Motion Segmentation. Current Trends in Bayesian Methodology with Applications, Chapman & Hall/CRC Press.
Editors: Dipak K. Dey, Umesh Singh and A. Loganathan. pp 267-286, 2015 (pdf)
- A. Barbu, T.F. Wu, Y. N. Wu. Learning Mixtures of Bernoulli Templates by Two-Round EM with
Performance Guarantee. Electronic Journal of Statistics 8, No. 2, 3004-3030, 2014 (pdf, arxiv)
- A. Barbu, M. Pavlovskaia, S.C. Zhu. Rates for Inductive Learning of Compositional Models. AAAI Workshop Replearn 2013
- A. Barbu. Multi-Path Marginal Space Learning for Object Detection.
Academic Press Library in Signal Processing: Volume 4: Image, Video Processing and Analysis,
Hardware, Audio, Acoustic and Speech Processing. pp 271-291, 2013
- A. Barbu. Hierarchical Object Parsing from Structured Noisy Point Clouds. IEEE PAMI, 35, No. 7, 1649-1659, 2013.
(pdf, arxiv, slides)
- L. Ding, A. Barbu, A. Meyer-Baese. Learning a Quality-Based Ranking for Feature Point Trajectories. ACCV 2012
- L. Ding, A. Barbu, A. Meyer-Baese. Motion Segmentation by Velocity Clustering with Estimation of Subspace Dimension. ACCV Workshop DTCE 2012
- A. Barbu, N. Lay. An Introduction to Artificial Prediction Markets for Classification.
Journal of Machine Learning Research, 13, 2177-2204, 2012.
- A. Barbu, M. Suehling, X. Xu, D. Liu, S. K. Zhou, D. Comaniciu. Automatic Detection and Segmentation of Lymph Nodes from CT Data.
IEEE Trans Medical Imaging, 31, No. 2, 240-250, 2012.(pdf)
- W. Wu, T. Chen , A. Barbu, P. Wang, N. Strobel, S. Zhou, D. Comaniciu.
Learning-based Hypothesis Fusion for Robust Catheter Tracking in 2D X-ray Fluoroscopy.
CVPR 2011 (pdf)
- F. Bunea and
A.Barbu. Dimension reduction and variable selection in case control
regularized likelihood optimization. Electronic Journal of Statistics, 3,
- A. Barbu. Training an Active Random Field for Real-Time
Image Denoising. IEEE Trans. Image Processing, 18,
November 2009. (pdf,
- S. Seifert, A.
Barbu, S. Zhou, D. Liu, J. Feulner, M. Huber, M. Suehling, A.
Cavallaro, D. Comaniciu.
Hierarchical parsing and semantic navigation of full body CT data. SPIE
Medical Imaging, 2009 (pdf)
- Y. Zheng,
A. Barbu, B. Georgescu, M. Scheuering and D. Comaniciu.
Four-Chamber Heart Modeling and Automatic Segmentation for 3D Cardiac CT Volumes Using Marginal Space
Learning and Steerable Features. IEEE Trans Medical Imaging, November
Lu, A. Barbu, M. Wolf, J. Liang, M. Salganicoff,
D. Comaniciu. Accurate Polyp Segmentation for 3D
CT Colonography Using Multi-Staged Probabilistic Binary Learning and
Compositional Model. CVPR 2008.(pdf)
- A. Barbu, V.
Athitsos, B. Georgescu, S. Boehm,
P. Durlak, D. Comaniciu. Hierarchical Learning of Curves:
Application to Guidewire Localization in Fluoroscopy. CVPR 2007 (pdf)
- A. Barbu, S.C. Zhu. Generalizing Swendsen-Wang
for Image Analysis. J. Comp. Graph. Stat. 16, No 4, 2007 (pdf)
- A. Barbu, S.C. Zhu. Generalizing Swendsen-Wang
to sampling arbitrary posterior probabilities, PAMI, 27,
August 2005 (pdf)
- A. Barbu,
S.C. Zhu. Multigrid and Multi-level
Swendsen-Wang Cuts for Hierarchic Graph Partition, CVPR 2004 (pdf)
- 2011 Thomas A. Edison Patent Award. System and Method for Segmenting Chambers of a Heart in a Three Dimensional Image.
Patent No. 7,916,919. video
- Fundamental Limits of Learning, DARPA, $142,000, 09/14/2016-12/31/2017. (PI on Subcontract from UCLA).
- Learning Homogeneous Knowledge Representation from Heterogeneous Data for Quantitative and Qualitative Reasoning in Autonomy.
DARPA, $42,000, 06/29/2015- 07/28/2016. (PI on Subcontract from UCLA)
- A Novel Platform for Biological Information Integration and Knowledge Discovery, NSF, $70,000. 07/01/2014 - 06/30/2015, 2015 (Co-PI)
- SEE on a Unified Foundation for Representation, Inference and Learning, DARPA, $257,000. (PI on subcontract from UCLA)
- MCS: Research on Detection and Classification of 2D and 3D Shapes in Cluttered Point Clouds. NSF, $400,000. (CO-PI)
- Statistical and Semantic Approaches for Object, Activity and Intent Recognition. ONR, $443,000 (CO-PI)
- Landmark Detection Using Discriminative Anatomical Network And Active Random Fields. Siemens, $31,000 (PI)
- Cooperative Systems: Task Allocation for Heterogeneous Agent Teams Via Stochastic Clustering Auctions. ARO, $16,000 (subcontract)
- Artificial Intelligence and the Future of Humanity, CWT Solutions Group Meeting, Miami Beach, FL, February 2016.
- Face Detection with a 3D Model. UCLA, June 19, 2015
- Feature Selection with Annealing for Big Data Learning. Johns Hopkins University, October 28, 2014
- Feature Selection with Annealing for Regression and Classification. Temple University, October 15, 2014
- The Artificial Prediction Market, ICML Workshop on Markets, Mechanisms and Multi-Agent Models,
Edinburgh, July 1st, 2012 (pdf)
- Hierarchical Object Parsing from Noisy Point Clouds, Siemens Corporate Research, August 16th, 2011
- Artificial Prediction Markets for Classification, Regression and Density Estimation, UCLA, August 11th, 2011
- Automatic Detection and Segmentation of Lymph Nodes. NIH, December 8th 2010
- Supervised Aggregation of Classifiers using Artificial
Prediction Markets, SRCOS 2010 (pdf)
- Supervised Aggregation using Artificial Prediction Markets.
UCLA, November 10th, 2009
- Marginal Space Learning for Fast Object Detection in Medical Imaging.
Tutorial on Discriminative Learning Methods in Medical Imaging, MICCAI 2009
- Training an Active Random Field for Real-Time Image
Denoising. Max Plank Institute, Saarbrucken, Germany, July 16th, 2008
- The Swendsen-Wang Cuts Algorithm with Applications in
Computer Vision, Georgia Tech University, June 2008
- Active Random Fields for Real-Time Image Denoising, Siemens
Corporate Research, May 2008
- Hierarchical Image-Motion Segmentation using Swendsen-Wang Cuts,
Third Cape Cod MCMC Workshop
, Harvard, 2007
- A General Clustering Sampling Method for Bayesian Inference, Joint Statistical Meetings,
Minneapolis, August 10, 2005
- Swendsen-Wang for Perceptual Grouping.
Second Cape Cod Workshop on Monte Carlo Methods, 2004
- J. Anaya, A. Barbu. System and Method for Image Processing using Automatically Estimated Tuning Parameters.
Patent no. 10,032,256
- J. Anaya, A. Barbu. System and Method for Generating a Dataset for Real Noise Reduction Evaluation.
Patent no. 9,591,240
- Y. Zheng, A. Barbu, B. Georgescu, M. Lynch, M. Scheuering, D. Comaniciu.
Method and system for generating a four-chamber heart model. Patent no 9,275,190
- A. Barbu. Systems and Methods for Training an Active Random Field for Real-Time Image Denoising.
Patent no 8,866,936
- A. Barbu, W. Zhang, N. Strobel, A. Galant, U. Bill, D. Comaniciu.
Method and system for catheter detection and tracking in a fluoroscopic image sequence. Patent no 8,396,533
- A. Barbu, M. Suehling, X. Xu, D. Liu, S.K. Zhou, D. Comaniciu.
Method and System for Automatic Detection and Segmentation of Axillary Lymph Nodes. Patent no 8,391,579
- W. Zhang, Y. Zhu, A. Barbu, R. Socher, S. Boehm, P. Durlak, D. Comaniciu.
Methods and Apparatus for Virtual Coronary Mapping. Patent 8,355,550
- L. Lu, A. Barbu, M. Wolf, S. Lakare, L. Bogoni, M. Salganicoff, D. Comaniciu.
Method and System for Polyp Segmentation for 3D Computed Tomography Colonography.
- L. Lu, A. Barbu, M. Wolf, S. Lakare, L. Bogoni, M. Salganicoff, D. Comaniciu.
User Interface for Polyp Annotation, Segmentation and Measurement in 3D Computed Tomography Colonography.
- R. Socher, A. Barbu, B. Georgescu, W. Zhang, P. Durlak, S. Bohm, D. Comaniciu.
Method and system for vessel segmentation in fluoroscopic images. Patent 8,121,367
- Y. Zhu, W. Zhang, A. Barbu, S. Prummer, M. Ostermeier, C. Reddy, D. Comaniciu.
System and Method for Coronary Digital Subtraction Angiography. Patent 8,094,903
- W. Zhang, A. Barbu, S. Prummer, M. Ostermeier and D. Comaniciu.
Method and System for Evaluating Image Segmentation Based on Visibility. Patent 8,086,006
- A. Barbu, L. Lu, L. Bogoni, M. Salganicoff, D. Comaniciu.
Method and System for Detection and Registration of 3D Objects Using Incremental Parameter Learning.
- A. Barbu, V. Athitsos, B. Georgescu, P. Durlak, D. Comaniciu.
System and Method for Online Optimization of Guidewire Visibility in Fluoroscopic Systems.
- A. Barbu, Y. Zheng, Y. Zhing, B. Georgescu, D. Comaniciu.
System and Method for Detecting an Object in a High Dimensional Space.
- B. Georgescu, P. Durlak, V. Athitsos, A. Barbu, D. Comaniciu.
System and Method for Simultaneously Subsampling Fluoroscopic Images and Enhancing Guidewire Visibility.
- W. Zhang, A. Barbu, S. Prummer, M. Ostermeier, C. Reddy, D. Comaniciu.
System and Method for Coronary Digital Subtraction Angiography. Patent 7,940,971
- Y. Zheng, A. Barbu, B. Georgescu, M. Scheuering, D. Comaniciu.
System and Method for Segmenting Chambers of a Heart in a Three Dimensional Image.
- S.K. Zhou, J. Shao, J. Dowdall, A. Barbu, B. Georgescu, D. Comaniciu.
System and Method for Using a Similarity Function to Perform Appearance Matching in Image Pairs.
- A. Barbu, V. Athitsos, B. Georgescu, P. Durlak, S. Boehm,
D. Comaniciu. System and Method for Detecting and Tracking
a Guidewire In A Fluoroscopic Image Sequence. Patent 7,792,342
- A. Barbu, L. Lu, M. Wolf, L. Bogoni, M. Salganicoff. Interface Utilisateur pour une
Annotation, une Segmentation et une Mesure de Polype en Colonoscopie Virtuelle 3D.
Europe Patent WO/2009/042034
- A. Barbu, L. Bogoni, D. Comaniciu. System and Method For
Detecting A Three Dimensional Flexible Tube In An Object. Patent 7,783,097
- Z. Tu, A. Barbu. Probabilistic
Boosting Tree Framework for Learning Discriminative Models. Patent 7,702,596
- Z. Tu, X. Zhou, D. Comaniciu, L. Bogoni, A. Barbu. System
and Method for Using Learned Discriminative Models to Segment Three dimensional Colon Image Data.
- Z. Tu, A. Barbu, D. Comaniciu. Method for Detecting Polyps in a Three Dimensional Image Volume. Patent 7,558,413
- Statistical Computing with Python - STA 5934-0002 (syllabus) Spring 2019
- Applied Machine Learning - STA 4634/5635 (syllabus) Spring 2008-2016, Fall 2016-present
- Applied Linear Regression - STA 4203/5207 (syllabus) Fall 2007-2013,2015-2016
- ANOVA and Design of Experiments - STA 4202/5206 (syllabus) Spring 2016-2017
- Introduction to Applied Statistics - STA 5126 (syllabus) Fall 2012
- Medical Image Analysis, (syllabus) Spring 2010,2012
2000-2005: Ph.D. Computer
Science, University of California,
1995-2000: Ph.D. Mathematics,
1990-1995: B.Sc. Mathematics,
University of Bucharest, Romania
Weather in Tallahassee:
If you want to
reach me, my address
Department of Statistics
Florida State University
Tallahassee, FL 32306
E-mail: email@example.com (remove all