From Computational Chemistry to Graduate School
I learned to conduct independent research, program algorithms, and present my ideas effectively to multiple audiences.
Major: Math and Chemistry Minor
Research Group: Gomez Lab
Internships: National Institute for Mathematical and Biological Synthesis, Researcher; Centers for Disease Control and Prevention, Research intern
Graduate School: Computational Biology, Carnegie Mellon University, University of Pittsburgh
In my graduate research, I have been developing computer vision and machine learning algorithms to encode the visual process undertaken by pathologists to identify important cues for diagnosis. In addition, I have been collaborating with multiple pathologists from the UPMC to collect training data and build a benchmark dataset for tissue segmentation and identification in Hematoxylin & Eosin images.
During my time at Mount Holyoke, I worked on computational chemistry under the supervision of Professor Maria Gomez. I learned to conduct independent research, program algorithms, and present my ideas effectively to multiple audiences.
My experience with the chemistry department was awesome and I have always carried the Mount Holyoke spirit with me everywhere I go.
Publications and Presentations
Undergraduate Research
M. A. Gomez, D. Shepardson, Luong T. Nguyen ’12, Tolu Kehinde ‘13, “Periodic long range proton conduction pathways in pseudo-cubic and orthorhombic perovskites,” Solid State Ionics, 213, 8 (2012).
Journal papers
L. Nguyen, D. L. Taylor, S. C. Chennubhotla. Opponent Color Stain Normalization in Hematoxylin and Eosin Images. Computational Method for Medical Imaging Workshop, Medical Image Computing and Computer Assisted Intervention, Boston, M.A. September 2014.
Nguyen, L., Tosun, B., Fine, J., Taylor, L., Chennubhotla, C. (2016) Spatial statistics for segmenting histological structures in H&E stained tissue images, In revision IEEE Trans. Med. Im.
Nguyen, L., Tosun, B., Ma, T., Fine, J., Taylor, L., Chennubhotla, C. (2017) Statistical Color Appearance Normalization for Histological Images. In preparation IEEE Trans. Med. Im.
Peer-reviewed conference/workshop papers
Nguyen, L., Spagnolo, D., Bauer, J., Palekar, A. Pejchal, M., Fine, J., Taylor, L.,Chennubhotla, C. (2016) Determining histological tissue image origins with convolutional neural networks Int. Conf. Machine Learning Workshop on Computational Biology, June 24, 2016, NY.
Nguyen, L., Tosun, B., Fine, J., Taylor, L., Chennubhotla, C. (2017) Architectural patterns for differential diagnosis of proliferative breast lesions from histopathological images, IEEE Int. Symp. on Biomedical Imaging Accepted: Jan 9, 2017
Nguyen, L., Tosun, B., Fine, J., Taylor, L., Chennubhotla, C. (2016) Novel approaches to segmenting a broad class of histological structures in H&E stained tissue images. Workshop in Computer Vision and Pattern Recognition: Women in Computer Vision. Las Vegas, June 2016.
Abstracts
Terrell Jones, Luong Nguyen, Akif Burak Tosun, S. Chakra Chennubhotla and Jeffrey Fine (2017)
Computational Pathology versus Manual Microscopy: Comparison Based on Workflow Simulations of Breast Core Biopsies. USCAP 106th Annual Meeting, March 4 - 10, 2017 in San Antonio, TX.