BME2211: Biomedical Data Analysis and Programming
Learn to program with MATLAB and analyze real biomedical data sets using data analysis methods including dimensionality reduction, classification, clustering, and regression.
BME595L: Machine Learning for Biomedical Informatics
A probabilistic graphical model approach to statistical machine learning. Learn theoretical and practical aspects of statistical inference and their application to biomedical data analysis problems.
Patrick Flaherty , Principal Investigator
Patrick is broadly interested in scalable, accurate algorithms for gaining understanding from massive biomedical data.
Hachem Saddiki, Graduate Student
Hachem is focusing on developing efficient inference algorithms for Bayesian statistical models to identify biomarkers from genomic assays on heterogeneous tumor samples. He is generally interested in machine learning methods for large-scale genomic data sets.
Fan Zhang , Graduate Student
Fan graduated with a master degree majored in Bioinformatics from Jilin University, China in 2012. Then she worked as Research Assistant focused on bio-signal processing in Chinese Academy of Sciences. She is interested in next generation sequencing data analysis, and biomarkers based on microarray data. Her current work is concentrated on rare single nucleotide variant detection on NGS data using Bayesian statistical models.
Chuangqi Wang, Graduate Student
Chuangqi Wang earned his master degree with concentration in robot motion planning in Electronics Engineering & Computer Science (EECS) from Peking University in 2012. There, he focused on image processing and robotics in Chinese Academy of Sciences (CAS). Currently, he is interested in statistical machine learning methods for large-scale biomedical data.
Erin Esco , Undergraduate Student
Erin is a sophomore majoring in Computer Science at WPI. She is interested in working with large data sets - developing analysis pipelines and finding solutions for storing and mining data.