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Hoon (Hyunghoon) ChoDepartment of Computer Science |
Education
M.S. in Computer Science, Stanford University, 03/2012 - 06/2013
B.S. in Computer Science with Honors, Stanford University, 09/2009 - 06/2013
Honors Thesis: Unraveling the genetics of human diseases by integrating patterns for epistasis detection. [ PDF ]
Korea Science Academy of KAIST, 03/2006 - 12/2008
Publications
Patterns of interaction in the genetics of complex human traits and guided discovery from diverse genomic assays. Alexis Battle, Hyunghoon Cho and Daphne Koller. Submitted to Genome Research (under review). 2012.
Research
Identifying parent-specific gene/isoform expressions using long-read RNA-seq with Alexis Battle and Prof. Stephen Montgomery. 09/2012 - present.
I am currently working on this project with Ph.D candidate Alexis Battle and Prof. Stephen Montgomery. RNA-seq provides a more direct way of studying human transcriptome and its underlying regulatory processes. In this project, we aim to study the benefits of RNA-seq data with longer read lengths in various settings, including the ability to disambiguate genes and isoforms and determining which parent's haplotype each read belongs to. Then we identify interesting parent-specific expression patterns, which will inform us about different modes of differential regulation between parental haplotypes.
Patterns of epistasis and guided adaptive interaction testing with Alexis Battle and Prof. Daphne Koller. 04/2011 - 09/2012.
One of the biggest challenges in modeling the genetics of complex human diseases is in discovering important interactions (non-additive effects) of multiple genetic variants such as single nucleotide polymorphisms. Because of the combinatorial explosion in the number of interaction hypotheses to consider, most naive approaches suffer from computational burden and the loss of the ability to detect small, but important, interactions due to multiple hypothesis testing correction. We developed a method that incorporates several important patterns of gene-gene interactions and learns how to prioritize candidate interactions. This resulted in a discovery of hundreds of significant interactions in several datasets that would not have been statistically significant if we took the naive approach.
Worked on a preliminary version of this project for Stanford CURIS, Summer 2011. [ Poster ]
Honors research project. [ Thesis ]
Submitted to Genome Research (under review). [ Paper ]
Using the Deformable Part Model with autoencoded feature descriptors for object detection with David Wu, Adam Coates and Prof. Andrew Ng. 09/2010 - 01/2011.
The Deformable Part Model (DPM) is widely regarded to be one of the state-of-the-art object detection algorithms. We considered substituting the human-engineered Histogram of Oriented Gradients descriptors used by DPM for features learned in an unsupervised fashion by a single-layered, sparse autoencoder. The results indicated that the unsupervised feature learning-backed DPM achieves a comparable performance as the original HOG-based system but does not show significant improvement.
Final project for CS229: Machine Learning. [ Report, Poster ]
Frequency dependence of radiation patterns of earthquakes on rough faults with Prof. Eric Dunham. 06/2010 - 12/2010.
The focus of this project was to understand far-field ground motion from simulations of rupture propagation on rough faults. The observations suggested that the directivity effect (which states that the ground motion in the forward direction of the rupture propagation tends to be larger than that in other directions) is generally only present at frequencies less than about 1 Hz, and that at higher frequencies, the directivity effect vanishes and the far-field radiation pattern changes from the usual double-couple pattern to an isotropic one.
Poster presentation at Southern California Earthquake Center 2010 Annual Meeting. [ Poster ]
Teaching
Section Leader for CS 106A/X, Stanford Computer Science Department, 01/2011 - 12/2011.
Taught weekly sections for Stanford's introductory computer science courses, graded programming assignments and exams, and helped students working in the computer cluster debug their code.
Work
Business Development Intern, Palantir Technologies, Summer 2012.
Worked on a genomic analysis platform with a focus on seamlessly integrating different data sources and publicly available analytical tools.
Awards, Honors, and Distinctions
Frederick Emmons Terman Engineering Scholastic Award, 2013
Stanford Tau Beta Pi Engineering Honor Society, 2012 - present.
President's Award for Academic Excellence in the Freshman Year, 2010.
Seventh Place in ACM ICPC Pacific Northwest Regional, 2010.
Kwanjeong Educational Foundation Scholarship for Undergraduate Studies, 2009.
Second Award in Intel ISEF, 2008.
Other Experiences
Cellist in Stanford Symphony Orchestra, 2009 - 2010 and Summer 2012.
President of Stanford Hwimori (traditional Korean drumming group), 2012 - 2013.