Voyager
Sudhir Nallam(psn240): Part-time master's student at CDS in last semester. I have 7+ years of work experience in coding with Python and Java. Presently I am working as software engineer at IBM Watson Research Center. I work on predictive analysis and deep learning. My interests are working in deep learning(NLP and/or Vision), Inference problems in unsupervised settings, time-series data and predictive analysis. Apart from core classes I have taken Deep Learning, NLP with Deep Learning, Inference and Representation etc., classes.
Xiaoyu Wang (xw1435): I'm currently a second year master of data science student at CDS. My background is in Applied Mathematics and Statistics. The past summer I was working with a project on ventricular tachycardia origins determination through modeling electrocardiogram signals both in supervised and unsupervised learning settings. My interest lies in interpreting and understanding deep neural networks. Aside from core courses, I also took topological data analysis and graph signal processing, which aims at exploring data analysis from a different approach.
Yurui Mu: Yurui received her B.S. degree in Applied Mathematics and Statistics at SUNY Stony Brook. And she is now a second year full-time graduate student at NYU Center for Data Science. She has past research experience at National Supercomputing Center in Jinan, China. She has also worked as intern at MENUSIFU Inc. as data analyst. Having taken Machine Learning, Big Data, Deep Learning, Text As Data courses at CDS, she is interested in applications of machine learning in various fields of study.
Wenqing Zhu: Wenqing is also a second-year Data Science student at New York University. She has attained her B.A. degree in Mathematics and Economics at University of Illinois Urbana-Champaign. She has taken classes such as Machine Learning, Deep Learning, and Fundamentals of Algorithms for the past year. For coding, Wenqing has a programming background in Python and MapReduce.
We all share strong interests in deep learning and its application on applied physics and biomedical research.
- Any of the Breast cancer screening projects: In all the three projects we deal with major challege in computer vision, that is, handling high resolution images. In multi-view deep convolutional neural (MVDCN) network for breast screening done by prof. Kyunghyun Cho and Dr. Krzysztof J. Geras, handled this high resoltion images. By replicating their work, I will be coming up with a approach which would applied to multiple domains, where anomalies are hidden in high density data.
- Applied Bioinformatics Laboratories project: In this project we get a chance to apply deep learning techniques we learned to classifying the lung cancer sub-types.
- (Selected)Robust method for QCD RNN netowrks: Using neural network to detect the particles genrated in a particle collider.