Alexandra Constantin

Ph.D. Candidate in Computer Science
Designated Emphasis in Communication, Computation, and Statistics
University of California, Berkeley

Graduate Research Assistant
Sarah J. Nelson Lab
Department of Radiology
University of California, San Francisco

Advisors: Ruzena Bajcsy and Sarah J. Nelson

Education

Projects

I am a graduate student at UC Berkeley working towards a PhD in Computer Science with a Designated Emphasis in Communication, Computation, and Statistics. My area of specialization is statistical learning, and my research efforts focus on applying and developing multivariate pattern recognition methods for the analysis of multi-modality biomedical data, in order to assist in the clinical management and biological understanding of brain tumors. The tools I am working on are important for characterizing biological changes predictive of malignant transformations and treatment effects in gliomas, and for the early detection of disease progression and response to therapy. I investigate the potential of ex vivo and in vivo advanced magnetic resonance imaging to predict changes in pathology and physiology. These techniques provide insight into tumor biology that is often difficult or impossible to obtain using more conventional approaches. My work is highly interdisciplinary and is conducted in collaboration with researchers in the Nelson Biomedical Imaging and Radiology Laboratory at UCSF. This labroratory is a very exciting place to work. It offers an interactive, collaborative environment, where scientists with very different backgrounds work together to identify relevant clinical and biological questions and to develop the required tools to answer those questions.

Education

University of California, Berkeley

Ph.D. in Computer Science with a Designated Emphasis in Communication, Computation, and Statistics, 2012
Ph.D. Thesis: Multivariate pattern analysis of anatomic, physiologic, and metabolic imaging data for improved management of patients with gliomas [Link]
Preliminary exam in Artificial Intelligence
Qualifying exam areas: Statistical Learning/Pattern Recognition, Medical Imaging Analysis, Brain Tumor Diagnosis and Prognosis
M.S. in Computer Science, 2009
M.S. Thesis: Automatic Segmentation of Brain Tissue in Patients with Gliomas

Williams College

B.A. in Computer Science and Mathematics and Statistics, 2007
Thesis: Brain-Computer Interface for the Classification of Motor Imagery

Projects

Identification of low grade gliomas that transformed to a higher grade using in vivo magnetic resonance imaging and spectroscopy
Linking ex vivo and in vivo glioma biomarkers for guiding biopsy site selection and studying glioma heterogeneity
Identification of metabolites that are predictive of malignant transformations in gliomas using HRMAS spectra from image guided tissue samples
Identification of metabolic changes associated with treatment effect in gliomas using HRMAS from image guided tissue samples
Metabolic characterization of glioma populations
Serial analysis of newly diagnosed GBMs

Old Projects

Automatic segmentation of brain tissue in patients with newly diagnosed gliomas
Solar power modelling, anomaly detection and short-term forecasting [Link]
Fingerspelling recognition
Brain-computer interface for the classification of motor imagery
Statistical machine translation [ Link ]
Evaluating arm movement imitation [ Link ]

Publications

A. Constantin, L. Jalbert, A. Elkhaled, R. Parvataneni, A. Molinaro, J. Phillips, S. Cha, S. M. Chang, and S. J. Nelson, “Multivariate Analysis of In Vivo MR Imaging Parameters for Detecting Transformations to a Higher Grade in Patients with Recurrent Low Grade Gliomas” , ISMRM, 2012. [Abstract]
A. Constantin, A. Elkhaled, L. Jalbert, K. Smith, T. McKnight, A. Molinaro, J. Phillips, S. M. Chang, and S. J. Nelson, “Effects of Treatment on the Metabolic Characteristics of Grade 2 and Grade 3 Gliomas” , ISMRM, 2012. [Abstract]
A. Constantin, A. Elkhaled, L. Jalbert, R. Srinivasan, S. Cha, S. M. Chang, R. Bajcsy, and S. J. Nelson, “ Identifying Malignant Transformations in Recurrent Low Grade Gliomas using High Resolution Magic Angle Spinning Spectroscopy” , Journal of Artificial Intelligence in Medicine, 55(1):61-70, 2012. [Link]
A. Elkhaled, L. Jalbert, A. Constantin, J. Phillips, H. Yoshihara, R. Srinivasan, G. Bourne, S. M. Chang, S. Cha, and S. J. Nelson, “Metabolic Characterization of Glioma Populations” , Neuro-Oncology 13:iii84, 2011.
A. Constantin, A. Elkhaled, L. Jalbert, R. Srinivasan, S. Cha, S. M. Chang, R. Bajcsy, and S. J. Nelson, “Multivariate Pattern Analysis for Identification of Metabolites that are Predictive of Malignant Transformations in Gliomas using HRMAS Spectra from Image Guided Tissue Samples”, ISMRM, 2011. [Abstract] [Poster]
A. Constantin, S. J. Nelson, R. Bajcsy, “Modeling Tumor Cellularity in Newly Diagnosed GBMs using MR Imaging and Spectroscopy”, MICCAI 2010 Workshop on Computational Imaging Biomarkers for Tumors: From Qualitative to Quantitative, 2010. [ PDF]
A. Constantin , R. Bajcsy, S. J. Nelson, “Unsupervised Segmentation of Brain Tissue in Multivariate MRI” , IEEE International Symposium on Biomedical Imaging, 2010. [PDF]
A. Constantin, S. J. Nelson (advisor), R. Bajcsy (advisor), “ Automatic Segmentation of Brain Tissue in Patients with Gliomas”, UC Berkeley M.S. Thesis, 2009.
A. Constantin , A. Danyluk (advisor), “A Brain-Computer Interface for the Classification of Motor Imagery”, Williams College Honors Thesis, 2007. [ Library Link] [ PDF ]
P. Koehn, H. Hoang, A. Birch, C. Callison-Burch, M. Federico, N. Bertoldi, B. Cowan, W. Shen, C. Moran, R. Zens, C. Dyer, O. Bojar, A. Constantin, E. Herbst, “Moses: Open Source Toolkit for Statistical Machine Translation”, Annual Meeting of the Association for Computational Linguistics (ACL), demonstration session, Prague, Czech Republic, June 2007. [PDF]
P. Koehn, M. Federico, W. Shen, N. Bertoldi, O. Bojar, C. Callison-Burch, B. Cowan, C. Dyer, H. Hoang, R. Zens, A. Constantin, C. Moran, E. Herbst, “Open Source Toolkit for Statistical Machine Translation: Factored Translation Models and Confusion Network Decoding”, Johns Hopkins Center for Language and Speech Processing (CLSP) Engineering Workshop, 2006. [PDF]
A. Constantin and M. J. Mataric, “Evaluating Arm Movement Imitation”, American Journal of Undergraduate Research, 4(4), 2006, 9-16. [PDF] [CRAW DMP Website]
A. Constantin and M. J. Mataric, “Evaluating Arm Movement Imitation”, USC Center for Robotics and Embedded Systems Technical Report, CRES-05-009, Apr 2005. [PDF]

Selected Courses

University of California, Berkeley

Bayesian Modeling and Inference
Statistical Learning Theory
Longitudinal Data Analysis
Medical Image Processing
Clinical Trial Design
Computer Vision
FMRI Methods
Neural Motor Control
Statistical Natural Language Processing
Intro to SAS
Intermediate SAS

Williams College

Machine Learning
Artificial Intelligence
Bayesian Statistics
Advanced Mathematical Methods in Statistical Inference
Regression and Forecasting
Categorical Data Analysis
Biostatistics
Experimentation and Statistics
Statistical Design of Experiments
Advanced Probability Topics
Operations Research
Ergodic Theory
Real Analysis
Linear Algebray
Discrete Math
Computer Graphics

Teaching

CS 70: Discrete Mathematics and Probability Theory, Fall 2010.
Outstanding Graduate Student Instructor Award, 2010 - 2011

Contact Information

alexandra (at) berkeley (dot) edu